KENYA ROADS BOARD MINISTRY OF TRANSPORT, … Zone Main RICS Report... · 2019. 12. 6. · MAIN REPORT . APRIL, 2018 . Intercontinental Consultants and ... Summary on Length of Roads

KENYA ROADS BOARD MINISTRY OF TRANSPORT, INFRASTRUCTURE, HOUSING &

URBAN DEVELOPMENT

KENYA TRANSPORT SECTOR SUPPORT PROJECT

PROJECT ID: 124109

CREDIT No. 4926-KE / 5410-KE

PROVISION OF CONSULTANCY SERVICES TO

UNDERTAKE ROAD INVENTORY AND CONDITION

SURVEY FOR COASTAL ZONE IN KENYA

CONTRACT No. KRB/722/2015-2016

MAIN REPORT

APRIL, 2018

Intercontinental Consultants and Technocrats Pvt. Ltd.

A-8, Green Park, New Delhi - 110 016, India

In joint Venture

with

GEODEV (K) Ltd.

New Hurlingham plaza, 2nd Floor, Suite C3, P.O. Box 14066 00100, Nairobi, Kenya

Provision of Consultancy Services to undertake Road Inventory and

Condition Survey for Coastal Zone in Kenya

Final Road Inventory and Condition Report

April 2018

Table of Content i

TABLE OF CONTENTS

Sl. No.

Descriptions Page Nos.

EXECUTIVE SUMMARY Es-01 to Es-31

1. INTRODUCTION AND PROJECT BACKGROUND 1-1 to 1-7

1.1 General 1-1

1.2 Project Background 1-2

1.3 Contract Details 1-4

1.4 Deliverables of the Assignment 1-5

1.6 Outline Structure of Final Road Inventory and Condition

Survey Report 1-6 to 1-7

2. APPROACH AND METHODOLOGY 2-1 to 2-32

2.1 Scope of Consultancy Services 2-1

2.2 Summary of Resources Mobilised for Field Activities 2-2

2.3 Approach And Survey Methodology 2-2

2.3.1 Technical training and Survey equipment training 2-2

2.3.2 Field training on the data collection 2-2

2.4 Stakeholders Participation 2-3

2.4.1 Kick-off Work shop 2-3

2.4.2 Inaugural Steering Committee meeting 2-4

2.4.3 2nd Inter – Agency Steering Committee meeting 2-5

2.5 Field Data Collection of Classified and Narrow Roads 2-7

2.5.1 Updation of the Inventory and Condition survey

data for Classified roads 2-7

2.5.2 Inventory and Condition Survey data collection for

Narrow Road 2-9

2.6 Field Data Collection for Falling Weight Deflectometer

Measurements and Roughness Data 2-9

2.6.1 General 2-10

2.6.2 Equipment, apparatus and materials 2-11

2.6.3 Automatic data quality checks 2-11

2.6.4 Manual data quality checks 2-11

2.6.5 Calibration and Validation 2-11




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Sl. No.


2.6.6 Data collection procedure 2-12

2.6.7 Deflection survey 2-12

2.6.8 FWD Deflection test results 2-13

2.6.9 Factors affecting the test 2-13

2.6.10 Reporting 2-13

2.6.11 Data precision 2-13

2.7 Roughness Data Collection and Analysis 2-14

2.7.1 Determination of Pavement Condition Index (PCI) 2-15

2.7.2 Roughness Measurement – Longitudinal Profiling 2-15

2.7.3 Surface Regularity (Rut Depth) Measurement -

Transverse Profiling 2-16

2.7.4 Visual Condition Survey (VCS) 2-16

2.7.5 Off-Carriageway Condition and Rating 2-17

2.7.6 Road network Drainage Condition and Rating 2-18

2.7.7 Gravel roads roughness measurement 2-19

2.7.8 Roughness Value Rating 2-19

2.8 Data Processing 2-20

2.8.1 Data Downloading and Data Transferring 2-20

2.8.2 Exporting of Data file to ARCGIS Shape file 2-20

2.8.3 Data Cleaning Process 2-20

2.8.4 Merging of Individual Data 2-21

2.8.5 Extraction of Data for Interim Road Register 2-21

2.9 Proposed Road Numbering System 2-21

2.9.1. Road Numbering for Narrow Roads having road reserve less than 9m

2-21

2.9.2. Road numbering and classification of the new/upgraded roads having road reserve greater than or equal to 9m

2-22

2.9.3. Road numbering system adopted for the Dual carriageway Roads

2-23

2.9.4. Road numbering system adopted for the Narrow Roads crossing 2 or more counties

2-23




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2.9.5. Road numbering system adopted for the Diversions and Realignments to main Roads

2-23

2.9.6. Road numbering system adopted for the Service Roads/Slip Roads

2-23

2.10 Challenges Faced during Road Naming 2-23

2.11 Details of Data Collection 2-25

2.12 RICS Fieldwork Report and Progress 2-30

2.12.1 Classified Roads 2-30

2.12.2 Narrow Roads 2-30

2.13 Constraints faced during Field Activities and Mitigation Measures Implemented

2-31 to 2-32

3. FINAL ROAD REGISTER REPORT 3-1 to 3-32

3.1 Introduction 3-1

3.2 Layout of County-wise Data Summaries of Final Road Register

3-1

3.2.1 Overall Summary of surface type and Road condition

3-1

3.2.2 Overall Summary of Surface type and road condition per road class

3-1

3.2.3 Overall Summary of Roads and its Road Reserve width

3-1

3.2.4 Overall Summary of Drainage structures 3-2

3.3 County-wise Thematic Maps 3-2

3.4 Layout of Final Road Register 3-2

3.5 Summary on the Length of Roads and Drainage Structures 3-2

3.6 Clarification on Completeness of Data Collection in Classified Roads

3-8

3.7 Overall Condition of Roads County-wise 3-8

3.7.1. Garissa County 3-8

3.7.2. Kajiado County 3-9

3.7.3. Kilifi County 3-10

3.7.4. Kitui County 3-11

3.7.5. Kwale County 3-12




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3.7.6. Lamu County 3-13

3.7.7. Machakos County 3-14

3.7.8. Makueni County 3-15

3.7.9. Mombasa County 3-16

3.7.10. Nairobi County 3-17

3.7.11. Narok County 3-18

3.7.12. Taita Taveta County 3-19

3.7.13. Tana River County 3-20

3.8 Salient Features of the Road Inventory and Condition Survey

3-21

3.8.1 Classified Road Network 3-22

3.8.2 Narrow Road Network 3-25

3.8.3 Newly opened Road Network 3-29 to 3-32

4. ROUGHNESS AND FALLING WEIGHT DEFLECTOMETER MEASUREMENTS

4-1 to 4-6

4.1 Collection of Roughness Data and Falling Weight Deflectometer Measurements

4-1

4.2 Inferences On Deflection Measurements For Paved Roads 4-2

4.3 Roughness Data Collection And Analysis Interms of International Roughness Index.

4-3

4.3.1 Roughness data for Paved Roads 4-3

4.3.2 Roughness data for Gravel Roads in Good and Fair Condition only

4-6

5. RICS GEO-DATABASE AND DATA INTEGRATION 5-1 to 5-6

5.1 Introduction 5-1

5.2 Rics Geodatabase Design 5-1

5.2.1 Database Design Process 5-1

5.2.2 Data dictionary 5-2

5.2.3 Schema for the Geodatabase 5-3

5.3 Rics Data Development 5-4

5.3.1 Line Features (Roads) 5-4

5.3.2 Point Features 5-5




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5.3.3 Layers of Data Generated 5-5

5.4 Populating the Geodatabase and Enforcing Topology 5-6

6. DATA VALIDATION 6-1 to 6-25

6.1 Initiation of Data Validation Process 6-1

6.2 Schedule of Data Validation 6-1

6.3 Organogram of Road Agencies 6-5

6.4 Key Points Discussed in Validation Meetings 6-6

6.5 Concerns Raised By CRO’s and Road Agency Staff on Data Collected and Actions Taken by Consultants

6-6

6.5.1. County Governments 6-6

6.5.2. Kenya National Highway Authority (KeNHA) 6-14

6.5.3. Kenya Rural Roads Authority (KeRRA) 6-19

6.5.4. Kenya Urban Roads Authority (KURA) 6-23 to 6-25

7. CONCLUSIONS AND WAY FORWARD 7-1

7.1 Conclusions 7-1




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Table of Content vi

LIST OF TABLES

Description Page Nos.

Table 1.1: Details of Classified Road Length (as per ToR) in all 3 Geographic Zones

1-1

Table 1.2: Details of Classified Road network in Coastal Zone 1-2

Table 1.3: Contract Details of the project 1-4

Table 2.1: Deflection sensor spacing 2-12

Table 2.2: Geophone labeling 2-13

Table 2.3: Minimum data precision levels for reporting 2-14

Table 2.4: Data Collection details 2-26

Table 2.5: Summary of Structures and its Condition for Entire Coastal Zone

2-27

Table 2.6: Road Reserve details of Classified Roads 2-30

Table 2.7: Road Reserve details of Narrow and New Roads 2-30

Table 2.8: Constraints Faced and Mitigation measures 2-31

Table 3.1: Summary on Length of Roads County-wise 3-3

Table 3.2: Summary of Drainage Structures County-wise 3-4

Table 3.3: Inferences on the overall condition of Garissa County Roads

3-8

Table 3.4: Inferences on the overall condition of Kajiado County Roads

3-9

Table 3.5: Inferences on the overall condition of Kilifi County Roads 3-10

Table 3.6: Inferences on the overall condition of Kitui County Roads 3-12

Table 3.7: Inferences on the overall condition of Kwale County Roads 3-13

Table 3.8: Inferences on the overall condition of Lamu County Roads 3-14

Table 3.9: Inferences on the overall condition of Machakos County Roads

3-15

Table 3.10: Inferences on the overall condition of Makueni County Roads

3-16

Table 3.11: Inferences on the overall condition of Mombasa County Roads

3-17

Table 3.12: Inferences on the overall condition of Nairobi County Roads

3-18

Table 3.13: Inferences on the overall condition of Narok County Roads 3-19

Table 3.14: Inferences on the overall condition of Taita Taveta County Roads

3-20

Table 3.15: Inferences on the overall condition of Tana River County Roads

3-21




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Table 3.16: Summary of the Drainage structures in Classified Road Network

3-23

Table 3.17: Road reserve details of classified roads 3-25


3-26

Table 3.19: Road reserve Details for narrow roads and newly opened Roads

3-28

Table 3.20: Summary of the Drainage structures in New Road Network 3-30

Table 6.1: Schedule of Data Validation meetings 6-2

Table 6.2: Compliance matrix - County Governments 6-7

Table 6.3: Compliance matrix – KeNHA 6-14

Table 6.4: Compliance matrix – KeRRA 6-19

Table 6.5: Compliance matrix – KURA 6-23

LIST OF FIGURES


Figure 1.1: Demarcation of Zones and its Counties along with details of classified road network in each Zone

1-3

Figure 2.1: Sample of Grid map used by the field team 2-8

Figure 2.2: Sample of Index map provided along with Grid map 2-8

Figure 2.3: Snapshot of Carry Map Observer 2-9

Figure 2.4: Primax Falling weight Deflectometer 2-10

Figure 2.5: DRSP used in Paved Roads Surface Profiling 2-14

Figure 2.6: Measurement of pavement pothole 2-16

Figure 2.7: Fair shoulder collected in this survey 2-17

Figure 2.8: Poor Shoulder condition 2-18

Figure 2.9: Poor drainage condition on a road section 2-18

Figure 2.10: Roughmeter III used for gravel roads roughness measurements

2-19

Figure 2.11: Road Naming Issues in Kimana Section 2-24

Figure 2.12: Road Naming Issues in Kiserian section 2-25

Figure 2.13: Road Naming Issues in Kiserian town 2-25

Figure 2.14: Graphical presentation of Road network captured 2-31




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Figure 4.1: County Wise Average Structure Number of Paved Road Obtained From FWD Analysis

4-2

Figure 4.2: Average Structure Number of Paved Road Obtained From FWD Analysis

4-2

Figure 4.3:County wise Average Pavement Condition Index (PCI) of Paved Roads

4-4

Figure 4.4: Average Pavement Condition Index (PCI) of Paved Roads 4-4

Figure 4.5: County wide Average IRI for Paved Roads in Coastal Zone 4-5

Figure 4.6: Average IRI for Paved Roads in Coastal Zone 4-5

Figure 4.7: Countywise Average IRI for Gravel Roads for Coastal Zone 4-6

Figure 4.8: Average IRI for Gravel Roads in Coastal Zone 4-6

Figure 6.1: Organogram of Road Agencies 6-5

LIST OF ANNEXURES


Annexure 1 Field data collection manual and GPS User Guide

A1/1 to A1/40

Annexure 2 GIS data Processing Manual A2 / 1 to A2 / 116

Annexure 3 Procedure Manual for Roughness and Falling weight Deflectometer tests

A3/1 to A3/9

Annexure 4 Final Road Register map

Annexure 5 Maps For Structural Number of Road Surface (FWD Analysis)

Annexure 6 Maps for International Roughness Index (IRI) of Road Surface (Paved Roads)

Annexure 7 Maps for International Roughness Index (IRI) of Road Surface (Gravel Roads)

Annexure 8 Data Dictionary A5 / 1 to A5 / 9




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Table of Content ix

LIST OF APPENDICES


Appendix 1 County-wise Data Summaries of Interim Road Register

AP1/1 to AP1/70

Appendix 2 Road Condition Charts County-wise Data Summaries of Interim Road Register

AP2/1 to AP2/53

Appendix 3 Thematic Maps for summary on condition of Road network (County-wise)

AP3 / 1 to AP3 / 26

Appendix 4 Final Road Register for Narrow and Classified Roads (For entire Coastal Zone and County-wise)

AP4 / 1 AP4 / 2480

Appendix 5 Deflection measurement data for Paved Roads AP5 / 1 to AP5 / 219

Appendix 6 Roughness data for Paved Roads and Gravel Roads(Good/Fair condition

AP6/1 to AP6/3855

Appendix 7 Data Validation forms AP4 / 1 to AP4 / 55

Provision of Consultancy Services to undertake Road Inventory and Condition Survey for Coastal Zone in Kenya

Final Road Inventory and Condition Report April 2018

List of Abbreviations LOA-1

LIST OF ABBREVIATIONS

4WD - Four wheel drive vehicle

AASHTO - American Association of Standards for Highway Transportation Organizations

AC - Asphalt Concrete

ArcGIS - Geo-database creation and editing software

ASTM - American Standard Testing Methods

ATV - All-Terrain Vehicle

BS - British Standards

CAD - Computer Aided Design

CD - Compact Disc

CECM - County Executive Committee Member

CL - Centre line

COM - Communication

CRO - County Roads Officer

CS - Condition Survey

CSV - Comma Separated Value file

DMI - Distance Measuring Instrument

DRE - District Roads Engineer

DRSP - Digital Road Surface Profiling

DVD - Digital Video Disc

EBK - Engineers Board of Kenya

ESRI - Environmental Systems Research Institute

FWD - Falling Weight Deflectometer

GIS - Geographic Information System

GMPP - General Manager, Planning and Programming




GNSS - Global Navigation Satellite System

GoK - Government of Kenya

GPRS - General Packet Radio Service

GPS - Global Positioning System

GPX - GPS Exchange Format

GSM - Global System for Mobile communication

HDM4 - Highway Development and Management - 4

HMS - Highway Management System

HO - Head Office

HOD - Head of Department

HQ - Head Quarter

ICT - Information and Communications Technology

ICT Pvt. Ltd - Intercontinental Consultants and Technocrats Pvt. Ltd.

ID - Identification

IDA - International Development Association

IDLE - Integrated Development and Learning Environment

IRI - International Roughness Index

JV - Joint Venture

KE - Kenya

KeNHA - Kenya National Highways Authority

KeRRA - Kenya Rural Roads Authority

KES - Kenya Shilling

KFS - Kenya Forest Service

Km - Kilometre

KML - Keyhole Markup Language file




KMZ - Keyhole Markup language Zipped file

KRB - Kenya Roads Board

KTSSP - Kenya Transport Sector Support Project

KURA - Kenya Urban Roads Authority

KWS - Kenya Wildlife Services

LHS - Left Hand Side

MoR - Ministry of Roads

MoTIHUD - Ministry of Transport, Infrastructure, Housing and Urban Development

MS - Microsoft

MTR - Main Trunk Roads

MTRD - Materials Testing and Research Division

NR - Narrow Roads

ORN - Overseas Road Note

OWP - Outer Wheel Path

PC - Personal Computer

PDF - Portable Document Format

PDOP - Positional Dilution Of Precision

PFO - Pathfinder Office

PFR - Primary Feeder Roads

PPP - Public-Private Partnership

QA - Quality Assurance

QAP - Quality Assurance Plan

QAS - Quality Assurance System

RA - Road Agency

RCS - Road Condition Survey




RD - Roads Department

RDM - Road Design Manual

RHS - Right Hand Side

RI - Road Inventory

RIC - Road Inventory and Condition

RICS - Road Inventory and Condition Survey

RLP - Road Laser Profiler

RMLF - Road Maintenance Levy Fund

ROMDAS - Road Measurement Data Acquisition System

ROW - Right Of Way

RR - Road Reserve

RSP - Road Surface Profiling

RTRRM - Response Type Road Roughness Meter

SCI - Surface Condition Index

SD - Secure Digital

SHP - ArcGIS Shapefile format

SMEC - Snowy Mountains Engineering Corporation (Consultants for Western and Central Zones)

SSF - Standard Storage Format

ToR - Terms of Reference

UR - Urban Roads

URICS - Unclassified Road Inventory and Condition Survey

USB - Universal Serial Bus

USD - United States Dollar

UTM - Universal Transverse Mercator

VAT - Value Added Tax




VCI - Visual Condition Index

VHF - Very High Frequency

WGS - World Geodetic System

w.r.t - With respect to

EXECUTIVE SUMMARY




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Executive Summary Es-1

EXECUTIVE SUMMARY

0.1 INTRODUCTION

The Government of Kenya (GoK) through the ministry of roads undertook a road inventory and condition survey (RICS) between 2001 and 2004 with financing from world bank. The study mapped and classified 61,946 km of roads.

Further, between 2007 and 2009 Kenya roads board (KRB) with financing from the Nordic development fund and World Bank undertook another RICS to map the unclassified roads. This unclassified roads inventory captured a total of 98,940 km to bring the inventoried network to 160,886 km, which is held in a consolidated GIS database at KRB. The inventoried roads network covers roads with way-leave reserves of 9m width and above.

However, a large component of kenya’s road network consisting of narrows roads and tracks with road reserves between 4m and 9m which provide important access in urban and rural areas is not mapped. The network of narrow roads is estimated between 60,000km and 90,000km.

Similarly, subsequent inventory changes to the inventoried classified network (newly constructed and upgraded roads) are not fully captured while it can be expected that the road condition data in the KRB geo database is out-dated and thus requires to be updated.

Therefore, KRB intended to map and carryout the RICS of the newly constructed and upgraded roads as well narrow roads to update the road condition data for the entire road network of the country. These form the basis of the current study, which is funded by GoK through the credit received from the international development association (ida) towards the cost of Kenya-Transport Sector Support Project (KTSSP).

For the purpose of this study, the KRB has divided entire road network of the country in 3 zones namely; 1) western zone, 2) central zone and 3) coastal zone.

Intercontinental consultants and technocrats Pvt. Ltd. In joint venture with Geodev (k) ltd. Of Kenya (the consultant) has been assigned to carryout rics for the road network in coastal zone, which consists of 13 counties. The length of classified road network in coastal zone is 54,613.2 km of which approximately 4,353 km were estimated to be paved, whereas the length of narrow roads is estimated to be around 30,000 km.

Details of classified road network length in different zones are given in Table 0.1.

Table 0.1: Classified Road Network length (Zone-wise)

Sl. No. Zone No. of Counties Total length of Classified Roads

(km)

1 Western 21 53,397.4

2 Central 13 52,875.0

3 Coastal 13 54,613.2

Total 47 160,885.6




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Details of county-wise classified road network length in coastal zone is given in Table 0.2:

Table 0.2: Classified Road Network Length in Coastal Zone (County-wise)

Sl. No.

County name and number

Total Length of Classified Roads (km)

Sl.

No. County name and number

Total Length of Classified Roads (km)

1 Garissa – 7 2,999.0 8 Makueni – 17 7,744.8

2 Kajiado – 34 5,858.2 9 Mombasa – 1 964.2

3 Kilifi – 3 3,800.7 10 Nairobi – 47 2,942.1

4 Kitui – 15 8,593.1 11 Narok – 33 4,612.2

5 Kwale – 2 3,521.2 12 Taita Taveta – 6 3,954.2

6 Lamu – 5 843.4 13 Tana River – 4 2,854.2

7 Machakos – 16 5,926.0 Total Length (km) 54,613.2

0.2 CONTRACT DETAILS

The Project “Provision of Consultancy services to undertake Road Inventory and Condition survey for Coastal zone in Kenya” was launched under Kenya Transport Sector Support Project funded by World Bank.

The contract was signed between Kenya Roads Board as client and Intercontinental Consultants and Technocrats Pvt. Ltd. In Joint venture with Geodev (K) Ltd. of Kenya as Consultants on 1st August 2016 for a Lump-sum Contract price of USD 945,342 and KES 152,720,000.

As per the ToR provisions the Consultant commenced the services after 14 days of Contract signing, that is on 15th August 2016. The contract period for the completion of the consultancy services is 15 months and shall be ending on 15th November 2017.

Since signing of the Contract, 80% (i.e. 12 months) of the contract period has elapsed and the consultant has managed to complete all data collection.

Upon completion of the first 4 stages of the contract as mentioned in clause 41.2 of Special Conditions of Contract agreement the consultants had submitted their corresponding Invoices.

1st payment is being 20% of contract price as advance payment upon request by consultant and providing bank guarantee for the same which constituted for the amount of USD 189,068.40 and KES 30,544,000.

2nd payment is 15% of contract price for the submission and approval of Inception Report constituting for an amount of USD 141,801.3 and KES 22,908,000.

3rd payment is being 20% of contract price for the submission and approval of 1st Interim Road Register constituting for an amount of USD 189,068.4 and KES 30,544,000




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4th payment is being 20% of contract price for the submission and approval of 2nd Interim Road Register constituting for an amount of USD 189,068.4 and KES 30,544,000

5th payment is being 10% of contract price for the submission and approval of Draft Road Register Report constituting for an amount of USD 141,801.3 and KES 22,908,000.

The submitted invoices total to an amount of USD 850,808.3 and KES 137,448,000 which equates to 90% of the contract price. The amount has been certified and paid by the client, therefore equating to payment of 90% of USD component and 90% of KES component of the Contract Price.

0.3 SCOPE OF CONSULTANCY SERVICES

The scope of consultancy services includes carrying out Road Inventory and Condition Survey on Narrow Roads in the Zone; and capturing the Inventory and Condition changes in the classified Road Network in the Zone.

The captured data needs to be integrated with the existing RICS database.

Consultants shall also Propose Road numbering system for Narrow Roads and integrate the same into existing RICS database.

Collect Roughness data (International Roughness Index) and Falling Weight Deflectometer measurements at 1km interval for all the Paved Roads. For the Gravel Roads in Good and Fair Condition collect Roughness data (IRI).

Distribute the Maps of the data collected to field staff of Road Authorities and CROS’s for validation and make any necessary amendments.

0.4 ADOPTED SURVEY METHODOLOGY FOR FIELD DATA COLLECTION OF CLASSIFIED AND NARROW ROADS:

Field staff was trained for data collection activities both in office for theoretical knowledge on the attributes of data collection and in field for practical exposure and identification of attributes and condition rating.

Detailed review of Data Dictionary was carried out and the same was updated with value additions and submitted to client for approval.

The Geo referenced Map of high-resolution Google earth imagery Overlaid with previous RICS database maps were prepared. The maps were bifurcated into Grids covering 300 Sq. km area (15km X 20 km) scaled to 1:20,000. The Grid maps along with Index maps were distributed to field team to act as guiding boundaries and for Identification of classified Roads.

Survey was carried out using Hand held GPS device (Trimble Juno 3B). Teams were also equipped with Mobile devices uploaded with “Carry Map observer” application for the purpose of identifying the location of the team w.r.t the existing RICS database.

Narrow Roads (roads with Road Reserve less than 9m), excluded from the existing KRB RICS database, need to be mapped for Inventory and condition data of the road network. The identification of the narrow roads was done using




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satellite images and involvement of local communities. Field staff of Roads Authorities and CRO’s were also contacted for obtaining the information about identification of Narrow Roads.

Teams used a consistent procedure of surveying Roads found on one side of the accessing road in the direction of travel, before surveying the narrow roads found on other side of the accessing road.

Classified Paved Roads were observed first for the data collection, followed by gravel roads. Branches of these roads were surveyed at last using the methodology defined above.

Once the data collection was complete on one survey unit the data was projected onto satellite imageries and KRB RICS database was overlaid to identify any missing roads/data and geospatial co-ordinates were shared with the field teams to collect and ensure the extensiveness of every survey unit.

0.5 DATA PROCESSING:

Data collected in the field was transmitted to Nairobi office for compilation and processing.

In Compilation office, data was downloaded and backed-up. GPS Pathfinder Office Software was used to view the data and was exported in ArcGIS format for further processing and creation of Geo-database.

Data Collected has been processed by rectifying the oversights during field data collection activity such as Road geometry and alignment, Attribute information, Overshoot and Undershoots, loss of GPS Signal, Intersect other lines, Incorrect Continuation of lines, Duplicate roads/ features, Data gaps /missing features where the data was reviewed for the completeness and the same was edited to provide comprehensive data.

The errors were corrected using GIS tools and geo-tagged photographs for point features are referenced appropriately.

Individual Data files were further merged to create single shape file for each county and to create separate layer files for Paved, Gravel, Earth, Narrow Roads (9m>RR≥6m), Narrow Roads (6m>RR>4m) and for New Roads (RR≥9m).

County shape files along with layer files were loaded onto ARCGIS and using attribute table feature the database files were extracted to prepare the Final Road register.

The individual shapefiles for each county were then merged to create a single shapefile for the Coastal Zone.

0.6 DATA VALIDATION PROCESS FROM CRO’S

As per ToR provisions data validation has to be done to ascertain the accuracy/ reliability of data collected. Validation shall be done in three phases as described below:

Field visits by Key Professionals – Key Professionals like Team Leader, GPS/GIS mapping expert, database expert and RICS expert shall visit the field and




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randomly sample some of the roads already surveyed. The sampled roads and associated point features are independently re-surveyed. The data so obtained has been compared with the data collected by the field survey teams to ascertain the accuracy and authenticity of data collection.

Using KRB data – A spatial join between KRB inventory data and collected data was done. The join provides a check on the level of agreement between KRB inventory data and collected data both in geometry and attributes. Following the join, important attribute information e.g. road numbers and existing road names were verified for the collected data.

Meeting with stakeholders – After data cleaning and subsequent office processing, maps and road registers for each county were circulated and validation meetings were organized with the relevant Road Agencies in each County.

The meetings involved key stakeholders in the roads sector such as Field staff of Road authorities and County Roads Engineers etc. The objective of these meetings is to provide a forum for the stakeholders to assess the correctness and completeness of the data and to discuss the condition ratings assigned to roads.

The maps and registers were reviewed by the Road Agencies and CRO’s and the concerns were discussed to arrive at a mutual agreement.

The concerns which needed amendment were addressed and incorporated in the Final database and Road register1.

0.7 PROPOSED ROAD NUMBERING SYSTEM FOR NARROW ROADS:

For Narrow roads (roads with Road Reserve less than 9m) a road numbering system has been proposed by the consultant, which has been adopted as follows:

NR_XX_YYY whereby NR represents “Narrow Road”, XX represents the unique county reference number in accordance with the Constitution of Kenya, and YYY represents the unique number assigned to each narrow road in the county in a series that starts from 001 from South-West in a broadly clockwise towards the North-East.

Format shall be every Road number shall be suffixed with NR representing Narrow Roads followed by the underscore and County number after which an underscore followed by the road number as a 3 or 4 digit number as applicable.

The numbering shall be assigned county-wise commencing in the south-west of a County and working in a broadly clockwise direction towards the north-east.

Numbering of all Narrow roads in a county from 001 to 999 (and so on if required) starting from south-west of the county and proceeding in a broadly clockwise direction to north-east. For example, the narrow roads in the Mombasa County will have the Prefix NR followed by the Hyphen and then

1 Of the 3 processes for data validation:

Validation using KRB data has been carried out for all the counties.

Validation meetings are complete except for Coast KeNHA




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County number (i.e. 1) and then the number of the road i.e. NR_01_001 to NR_01_999.

0.8 ROAD NUMBERING AND CLASSIFICATION OF THE NEW/UPGRADED ROADS HAVING ROAD RESERVE ≥ 9M:

Road numbering and classification of the new/upgraded roads having road reserve greater than or equal to 9m has been done on the basis of the Road Classification Manual, July 2009.

After processing the field data, the identified new roads were bifurcated into Urban and Rural. Depending on the functionality of the road and observed traffic usage the class of the Road was defined. Numbering was allocated county-wise commencing in the south-west of a County and working in a broadly clockwise direction towards the north-east.

Challenges faced during Road numbering of Newly Identified Roads with Road Reserve greater than or equal to 9m

The Road classification and numbering as per Road classification manual 2009 was on Province basis. Therefore to assign sequential number for particular class of Road is not practically possible at this stage.

All the links of the classified road of that category may require renumbering in case sequential numbers are to be provided. However same classification methodology of Road class has been followed by suffixing county code (instead of province code) before the road number, and the inclusion of the word ‘NEW’.

The proposed numbering system adopted is as follows:

CoR_XX_NEW_YYY whereby CoR represents the class of the road, XX represents the unique county reference number in accordance with the Constitution of Kenya, NEW represents “newly upgraded/constructed road”, and YYY represents the unique number assigned to each new road in the county in a series that starts from 001 from South-West in a broadly clockwise towards the North-East.

The proposed numbering system shall be as “assigned Class of the Road followed by underscore and county number followed by word “NEW” which is then followed by underscore and road number which shall be starting from 001 and moves on sequentially.

Illustration: If a new road has been identified as class G in Mombasa county as per the functionality and its traffic usage that particular road shall be numbered as G_01_NEW_001 and immediate next road identified in the south west direction of same category shall be numbered in same format with next sequential number as G_01_NEW_002 and the same shall continue moving in clockwise direction towards north-east.

0.9 ROAD NUMBERING SYSTEM ADOPTED FOR THE DUAL CARRIAGEWAY ROADS:

For dual carriageway roads, the left side of such a road with it western most point as it start is taken to be the main carriage way. The right side of the dual carriage takes an abbreviation “R” appended to the road number to denote the right side of the dual carriage.




April 2018


There are some situations where a road is dualled as it passes through large urban centres and then reverts to normal two way road for other non-urban places where it passes through. Again from the start point of the road, the dual carriage sections on the right side of such a road are serialised with abbreviations R1, R2…..Rn where n denotes the nth section

0.10 ROAD NUMBERING SYSTEM ADOPTED FOR THE NARROW ROADS CROSSING 2 OR MORE COUNTIES:

For the Narrow roads crossing 2 or more counties the road naming convention shall remain same as followed for the Narrow roads; however instead of having 2 different road names for the same road in 2 different counties the road shall carry Road name and county number for that county where the road passes for it’s greatest length.

0.11 ROAD NUMBERING SYSTEM ADOPTED FOR THE DIVERSIONS AND REALIGNMENTS TO MAIN ROADS

For realignment or diversions of an existing road, abbreviations A, B, C…. have been adopted. Example A5 ( Loitoktok-Emali) appears to have abbreviations A5_A, A5_B, A5_C etc for the old sections before realignment, while the new realigned road takes A5 as the road number. The reason is because these old sections were surveyed as being used by traffic even though the realignment has been done.

0.12 ROAD NUMBERING SYSTEM ADOPTED FOR THE SERVICE ROADS/SLIP ROADS

Previously we had adopted notation S to denote service road but it was later realised that S conflicts with a Road class, and we therefore propose to use “SR” to denote service road such that taking Thika superhighway (A2S) for instance, the various sections of the service roads will be appear as follows:

A2S : Left side of the main carriage way

A2S_R: Right side of the main carriage way

A2S_SR1, A2S_SR2, A2S_SR3,……… A2S_SRn : The service roads on the left side of the road

A2S_R_SR1, A2S_R_SR2, …….. A2S_R_SRn: The service roads on the right side of the road

Where “n” denotes the nth section

0.13 CHALLENGES FACED DURING ROAD NAMING:

Road naming for Classified Roads has been provided as per the Gazetted Road List and the Road naming for Narrow Roads and New Roads are collected on the ground as per the areas or locations the Roads are connecting. In case of shorts routes connecting facilities, roads are named as per facility to facility. However Roads connecting same facility/locations are suffixed with serial numbers.

Some of the Roads in rural areas are found to be placed where no major landmarks are identified and also it has been observed that there are network of




April 2018


Roads which are branching off from those roads in such cases providing unique road names is difficult at this stage.

These roads shall be given unique road names in co-ordination with CRO’s and site staff of Roads Authorities during validation process.

0.14 BROAD FINDINGS FROM THE ROAD INVENTORY AND CONDITION SURVEY CARRIED OUT FOR THE ROAD NETWORK TILL DATE:

The consultant has completed survey of 55,001.10 Km of classified roads out of 54,613.2 Km and 35,102.67 Km out of estimated 30,000 Km of narrow roads; in totality 90,103.77 Km of Road network has been surveyed.

35,102.67 Km of Narrow Roads comprises of 17,687.90 Km of Narrow roads having Road Reserve less than 9m and 17,414.78 Km of newly opened/upgraded roads having Road Reserve width of greater than or equal to 9m.

Total of 24,091 Drainage structures were also inventoried and assessed for their conditions of which 21,270structures are found along classified roads; 1,193 along Narrow roads and 1,628are found along the newly opened/upgraded roads.

The length of Road surveyed and the details of the roads surveyed with the variation of the same w.r.t the provisions of ToR is given in Table 0.3.




April 2018


Table 0.3: County wise Details of surveyed road length

Sl No

County Name and Number

Classified Road Network length as per

ToR

Estimated Narrow Roads

network length as per

ToR

Total estimated length of

Road Network in the County

Actual Surveyed Classified

Road Network

Actual Surveyed Narrow Road network % Composition of Narrow Roads with

4m<RR<6m of total surveyed Narrow Roads

% Composition of Narrow Roads with

6m≤RR<9m of total

surveyed Narrow Roads

Total length of

Actual surveyed Narrow Roads

including New Roads

Total actual length of

Road Network

surveyed in the County

till date

(%) Progress of Classified

Roads

(%) Variation of Narrow

Roads Narrow Roads with 4m<RR<6m

Narrow Roads

with 6m≤RR<9m

Newly opened/ Upgraded Road

with RR≥9m

1 Garissa – 7 2,999.00 1,647.40 4,646.40 2,694.23 74.34 574.99 2,042 11.45% 88.55% 2,691.77 5,386.00 89.84% 63.39%

2 Kajiado – 34 5,858.20 3,218.01 9,076.21 5,762.77 206.97 1,524.01 2,126 11.96% 88.04% 3,856.86 9,619.63 98.37% 19.85%

3 Kilifi – 3 3,800.70 2,087.79 5,888.49 3,947.79 301.18 1,484.07 1,550 16.87% 83.13% 3,334.93 7,282.72 103.87% 59.73%

4 Kitui – 15 8,593.10 4,720.34 13,313.44 8,851.90 753.32 3,328.14 363 18.46% 81.54% 4,444.79 13,296.69 103.01% -5.84%

5 Kwale – 2 3,521.20 1,934.26 5,455.46 3,475.13 24.29 439.24 830 5.24% 94.76% 1,293.16 4,768.29 98.69% -33.14%

6 Lamu - 5 843.40 463.29 1,306.69 708.63 11.60 125.41 304 8.46% 91.54% 441.08 1,149.72 84.02% -4.79%

7 Machakos – 16 5,926.00 3,255.26 9,181.26 6,013.93 292.23 1,648.36 587 15.06% 84.94% 2,527.23 8,541.16 101.48% -22.36%

8 Makueni – 17 7,744.80 4,254.36 11,999.16 7,990.18 490.17 2,363.99 2,029 17.17% 82.83% 4,882.97 12,873.15 103.17% 14.78%

9 Mombasa - 1 964.20 529.65 1,493.85 777.69 26.78 89.68 142 22.99% 77.01% 258.81 1,036.50 80.66% -51.14%

10 Nairobi - 47 2,942.10 1,616.15 4,558.25 2,998.10 57.78 1,265.23 441 4.37% 95.63% 1,764.16 4,762.26 101.90% 9.16%

11 Narok – 33 4,612.20 2,533.56 7,145.76 4,998.93 89.76 1,162.89 3,794 7.17% 92.83% 5,046.62 10,045.55 108.39% 99.19%

12 Taita Taveta – 6 3,954.20 2,172.11 6,126.31 3,779.75 47.26 853.83 1,336 5.24% 94.76% 2,237.07 6,016.82 95.59% 2.99%

13 Tana River – 4 2,854.20 1,567.86 4,422.06 3,002.07 17.60 434.78 1,871 3.89% 96.11% 2,323.22 5,325.29 105.18% 48.18%

Total 54,613.30 30,000.05 84,613.35 55,001.10 2,393.27 15,294.63 17,414.78

35,102.67 90,103.77




April 2018


The number of structures captured during the survey and the condition analysed is given in Table 0.4.

Table 0.4: Summary of Structures and their Condition for Entire Coastal Zone

County Drainage Structure Type

Condition of Structure (Classified Roads) in numbers Condition of Structure (Narrow Roads) in numbers Condition of Structure (New Roads) in numbers Sub

Total Good Fair Poor Under

Construction Good Fair Poor

Under Construction

Good Fair Poor Under

Construction

Garissa

Bridge - - - - - - - - - - - - -

Pipe Culvert (Concrete) 62 124 59 - 6 2 1 - 7 23 4 - 288

Pipe Culvert (Armco) - - - - - - - - - - - - -

Pipe Culvert (Others) - - - - - - - - - - - - -

Box Culvert 4 - - - 1 - - - 1 - - - 6

Drift 3 - - - - - 2 - 2 2 2 - 11

Others - - - - - - - - - - - - -

Sub Total 69 124 59 - 7 2 3 - 10 25 6 - 305

Kajiado

Bridge 26 4 2 - 1 2 - - 1 2 - - 38

Pipe Culvert (Concrete) 1,167 389 113 - 53 9 5 - 144 72 19 - 1,971

Pipe Culvert (Armco) 55 2 2 - 1 - - - 1 - 1 - 62

Pipe Culvert (Others) 5 - - - - - - - - 2 - - 7

Box Culvert 82 3 - - 4 2 - - 4 2 - - 97

Drift 38 27 8 - - - 1 - - 1 7 - 82

Others - - - - - - - - - - - - -

Sub Total 1,373 425 125 - 59 13 6 - 150 79 27 - 2,257

Kilifi

Bridge 10 5 - - 1 2 - - - - - - 18

Pipe Culvert (Concrete) 542 614 302 - 44 13 5 - 79 79 25 - 1,703

Pipe Culvert (Armco) 6 13 3 - 2 - - - - - - - 24


Box Culvert 48 3 - - - - - - - - 2 - 53

Drift 6 19 2 - - - - - - - - - 27

Others 12 - 4 - - - - - - - - - 16

Sub Total 624 654 311 - 47 15 5 - 79 79 27 - 1,841

Kitui

Bridge 20 25 - - 2 - - - - - - - 47


Pipe Culvert (Armco) 7 12 20 - 1 - 1 - - - - - 41


Box Culvert 30 8 1 - 1 - - - 1 - - - 41




April 2018






Under Construction


Construction

Drift 186 181 80 - 46 29 12 - 10 4 2 - 550

Others - - - - - - - - - - - - -

Sub Total 1,203 1,190 804 - 202 150 44 - 59 18 7 - 3,677

Kwale

Bridge 13 12 1 - - - - - 5 - - - 31


Pipe Culvert (Armco) 25 36 17 - - - - - 2 1 - - 81

Pipe Culvert (Others) 2 - - - - - - - - - - - 2

Box Culvert 27 7 - - - - - - 2 6 - - 42

Drift 6 10 8 - - - - - 1 5 - - 30

Others - - - - - - - - - - - - -

Sub Total 887 869 323 - 1 3 4 - 68 39 1 - 2,195

Lamu

Bridge 1 1 - - - 1 - - - 1 - - 4

Pipe Culvert (Concrete) 43 99 6 - 1 - - - 22 22 2 - 195

Pipe Culvert (Armco) 1 3 - - - - - - - - - - 4


Box Culvert 8 - - - - - - - - - - - 8

Drift - 1 - - - - - - - - - - 1

Others - - - - - - - - - - - - -

Sub Total 53 104 6 - 1 1 - - 22 23 2 - 212

Machakos

Bridge 43 39 7 - - 3 - - 8 1 - - 101


Pipe Culvert (Armco) 23 31 12 - 1 - - - - 1 - - 68


Box Culvert 45 19 6 - 6 2 - - 6 - - - 84

Drift 128 148 98 - 12 16 8 - 7 1 1 - 419

Others - - - - - - - - - - - - -

Sub Total 1,165 995 592 - 103 104 56 - 63 33 22 - 3,133

Makueni

Bridge 33 11 - - - - - - 1 1 - - 46


Pipe Culvert (Armco) 31 18 2 - 1 2 - - 3 - - - 57

Pipe Culvert (Others) - - - - - - - - 1 - - - 1




April 2018






Under Construction


Construction

Box Culvert 1 - - - - - - - 1 1 - - 3

Drift 32 95 15 - - - - - 4 3 1 - 150

Others 1 - - - - - - - - - - - 1

Sub Total 1,305 768 165 - 14 13 1 - 48 44 10 - 2,368

Mombasa

Bridge 7 2 - - - - - - 2 - - - 11

Pipe Culvert (Concrete) 43 131 15 - 1 2 - - 10 11 2 - 215



Box Culvert - - - - - - - - - - - - -

Drift 1 - - - - - - - 1 1 - - 3

Others - - - - - - - - - - - - -

Sub Total 51 133 15 - 1 2 - - 13 12 2 - 229

Nairobi

Bridge 100 59 20 - 1 6 1 - 2 2 - - 191


Pipe Culvert (Armco) 1 - 1 - - - - - - - - - 2


Box Culvert 75 42 14 - 2 1 1 - 5 3 - - 143

Drift - 8 9 - - 1 1 - - - - - 19

Others - - - - - - - - - - - - -

Sub Total 585 813 626 - 41 120 104 - 39 46 17 - 2,391

Narok

Bridge 10 12 2 - - - - - 3 4 1 - 32


Pipe Culvert (Armco) 16 14 16 - - - - - - - 1 - 47


Box Culvert 47 1 - - - - - - 2 3 - - 53

Drift 2 - 1 - - - - - - - - - 3

Others - - - - - - - - 1 - - - 1

Sub Total 983 353 446 - 6 2 4 - 82 47 10 - 1,933

Taita Taveta

Bridge 9 7 - - 2 - - - 1 - - - 19


Pipe Culvert (Armco) 22 25 10 - - - - - - - - - 57




April 2018






Under Construction


Construction


Box Culvert 91 7 2 - - - - - 7 - - - 107

Drift 17 61 21 - - - 2 - 3 7 1 - 112

Others - - - - - - - - - - - - -

Sub Total 1,333 458 123 - 20 5 13 - 103 38 12 - 2,105

Tana River

Bridge 2 5 2 - - - - - 1 6 1 - 17

Pipe Culvert (Concrete) 570 410 87 - 13 7 - - 134 68 38 - 1,327

Pipe Culvert (Armco) 6 3 - - 1 - - - 1 4 2 - 17


Box Culvert 29 14 - - - - - - - - - - 43

Drift 5 20 5 - - - - - 4 4 2 - 40

Others - - - - - - - - - - - - -

Sub Total 612 452 94 - 14 7 - - 141 82 43 - 1,445

*Condition rating provided for the Drainage structures are Visual Structural condition




April 2018


The Total Road network is depicted graphically below.

0.15 CLASSIFIED ROAD NETWORK

Total of 55,001.10 Km of Classified roads are captured till in the entire Coastal

Zone.

Out of 55,001.10 Km, 5,570.2 km is Paved, 16,417.51 Km is Gravel, 30,922.99 Km

of Earth roads and 2,090.58 Km of Tracks.

45.36% of Paved Roads are in good condition, 36.74% are in fair condition,

15.64% is in poor condition and 2.26% are under construction.

8.91% of Gravel Roads are in good condition, 57.39% are in fair condition, 32.82%

is in poor condition and 0.88% is under construction.

2.67% of Earth Roads are in good condition, 42.61% are in fair condition, 54.48%


0.39% of Tracks are in good condition, 19.77% are in fair condition, 79.82% is in

poor condition and 0.02% is under construction.

The inferences mentioned above are depicted graphically below:

CLASSIFIED (Km)

NARROW ROADSWITH ROAD

RESERVEBETWEEN 4-6m

(Km)


RESERVEBETWEEN 6-9m

(Km)

NEW ROADSWITH ROAD

RESERVE MORETHAN 9m

Paved 5,570.02 9.25 139.60 237.16

Gravel 16,417.51 70.62 1,289.23 2,655.48

Earth 30,922.99 1,975.92 12,817.72 13,303.19

Other (Track) 2,090.58 337.48 1,048.08 1,218.95

Other (Track) Other (Track) Other (Track) Other (Track)

Earth

Earth

Earth Earth

Gravel

Gravel

Gravel Gravel

Paved

Paved

0

10,000

20,000

30,000

40,000

50,000

60,000




April 2018


The structures inventoried and the conditions assessed for classified roads are summarized and presented in Table 0.5:


Drainage Structure Type

Condition of Structure (Classified Roads) in numbers


Construction Sub Total

Bridge 274 182 34 0 490

Pipe Culvert (Concrete) 8,845 6,325 3,298 0 18,468

Pipe Culvert (Armco) 193 157 83 0 433

5,570.02

16,417.51

30,922.99

2,090.58

Surface Type Composition of Classified Roads

Paved

Gravel

Earth

Other (Track)

45.36%

8.91%

2.67%

36.74%

57.39%

42.61%

19.77%

15.64%

32.82%

54.48%

79.82%

2.26%

0.88%

0.24%

0.02%

Paved

Gravel

Earth

Other (Track)

Percentage

Surf

ace

typ

e

Percentage Condition per surface type (Classified Roads)

Good Fair Poor Under Construction




April 2018






Pipe Culvert (Others) 7 0 0 0 7

Box Culvert 487 104 23 0 614

Drift 424 570 247 0 1,241

Others 13 0 4 0 17

Total 10,243 7,338 3,689 0 21,270

From the above summary it is observed that 88. 90% of Drainage structures are

pipe culverts (Concrete). Box culverts constitute of 2.89% and Drifts constitute to

5.91% of the drainage structures while Bridges constitutes of 2.30%.

56% of Bridges are in good condition and 37% are in fair condition, however 7%

of them are in Poor condition

48% of Concrete Pipe Culvert is in good condition and 34% are in fair condition,

however 18% of them are in Poor condition

45% of Armco Pipe Culvert is in good condition and 36% are in fair condition,

however 19% of them are in Poor condition

100% of others/Composite Pipe Culvert are in good condition

79% of Box Culverts are in good condition and 17% are in fair condition, however

4% of them are in Poor condition

34% of Drifts are in good condition and 46% are in fair condition, however 20% of

them are in Poor condition

100% of other type of structures is in good condition.





April 2018


Road reserves obtained from the field activities for the classified road network are given in Table 0.6.

Table 0.6: Road reserve details of classified roads

CLASSFIED ROADS

Road Reserve width (m)

RR< 6m 6m≤RR<9m 9m≤RR<25m 25m≤RR<40m RR≥40m

Length (km) 0.00 16,274.83 32,235.88 3,266.18 3,224.19

55.92%

47.89%

44.57%

79.32%

34.17%

37.14%

34.25%

36.26%

16.94%

45.93%

6.94%

17.86%

19.17%

3.75%

19.90%

Bridge

Pipe Culvert (Concrete)

Pipe Culvert (Armco)

Pipe Culvert (Others)

Box Culvert

Drift

OthersPercentage

Stru

ctu

re T

ype

Percentage Condition of Structure type on Classified Roads





April 2018


0.16 NARROW ROAD NETWORK:

Narrow Road network of 35,102.67 Km consists of 17,687.90 Km of Narrow roads having

Road Reserve less than 9m and 17,414.78 Km of newly opened/upgraded roads having

Road Reserve width of greater than or equal to 9m.

Narrow Roads of 17,687.90 Km of Narrow Roads; 148.85Km is Paved, 1,359.85 Km is

Gravel, 14,793.64 Km of Earth roads and 1,385.56 Km falls under the category of tracks.

36.70% of Paved Roads are in good condition; 39.88% are in fair condition, 21.79% is in


11.15% of Gravel Roads are in good condition; 53.23% are in fair condition, 35.48% is in

poor condition and 0.14% is under construction

1.64% of Earth Roads are in good condition; 34.45% are in fair condition, 62.84% is in


1.65% of Tracks are in good condition; 30.51% are in fair condition and 67.84% is in poor

condition.


16,274.83

32,235.88

3,266.18 3,224.19

Road Reserve Ranges for Classified Road Network

6m≤RR<9m

9m≤RR<25m

25m≤RR<40m

RR≥40m




April 2018


The structures inventoried and the conditions accessed for classified roads are summarized and presented in Table 0.7:



Condition of Structure (Narrow Roads) in numbers


Construction Sub

Total

Bridge 14 1 - 24 39

Pipe Culvert (Concrete) 370 211 - 782 1,363

Pipe Culvert (Armco) 2 1 - 7 10

Pipe Culvert (Others) 0 0 - 2 2

Box Culvert 5 1 - 29 35

148.85 1,359.85

14,793.64

1,385.56

Surface Type Composition of Narrow Roads

Paved

Gravel

Earth

Other (Track)

36.70%

11.15%

1.64%

39.88%

53.23%

35.45%

30.51%

21.79%

35.48%

62.84%

67.84%

1.62%

0.14%

0.08%

0.00%

Paved

Gravel

Earth

Other (Track)Percentage

Surf

ace

typ

e

Percentage Condition per surface type (Narrow Roads)





April 2018





Construction Sub

Total

Drift 46 26 - 32 104

Others 0 0 - 1 1

Sub Total 437 240 - 877 1,554

From the above summary it is observed that 88.48% of Drainage structures are

pipe culverts (Concrete). Box culverts constitute for 2.25% and Drifts constitute

to 6.76% of the drainage structures while Bridges constitutes for 2.51% of

Drainage structures.

36% of Bridges are in good condition and 3% are in fair condition, however 62%

of them are Under Construction

27% of Concrete Pipe Culvert are in good condition and 15% are in fair condition,

however 57% of them are Under Construction

20% of Armco Pipe Culvert are in good condition and 10% are in fair condition,

however 70% of them are Under Construction

14% of Box Culverts are in good condition and 3% are in fair condition, however

83% of them are Under Construction

44% of Drifts are in good condition and 25% are in fair condition, however 31% of

them are Under Construction


39

1363

10 2 35

104

1

Composition of Structure Type on Narrow Road Network

Bridge




Box Culvert

Drift

Others




April 2018


Road reserves obtained from the field activities for the narrow road network including newly opened roads is given in Table 0.8.


NARROW ROADS AND NEW ROADS



Length (km) 2,393.27 15,294.78 17,169.77 239.00 6.30

38.89%

39.67%

57.14%

56.25%

45.39%

55.56%

37.70%

28.57%

25.00%

36.88%

5.56%

22.62%

14.29%

18.75%

17.73%

Bridge




Box Culvert

Drift

Others Percentage

Stru

ctu

re T

ype

Percentage Condition of Structure type on Narrow Roads


2,393.27

15,294.78 17,169.77

239.00 6.30

Road Reserve Ranges for Narrow and New Roads Network

RR< 6m

6m≤RR<9m

9m≤RR<25m

25m≤RR<40m

RR≥40m




April 2018


0.17 NEWLY OPENED ROAD NETWORK:

Newly opened Roads of 17,414.78 Km comprises 237.16 Km of Paved Roads,

2,655.48 Km of Gravel Roads, 13,303.19 Km of Earth roads and 1,218.95 km of

Tracks.

44.82% of Paved Roads are in good condition; 35.96% are in fair condition,

18.10% is in poor condition and 1.11% is under construction.

10.56% of Gravel Roads are in good condition; 58.31% are in fair condition,

30.52% is in poor condition and 0.61% is under construction.

2.27% of Earth Roads are in good condition; 43.65% are in fair condition, 53.76%


0.08% of Tracks are in good condition; 28.86% are in fair condition and 71.06% is

in poor condition.


237.16

2655.48

13303.19

1218.95

Surface Type Composition of Newly opened Roads

Paved

Gravel

Earth

Other (Track)




April 2018


The structures inventoried and the conditions accessed for classified roads are summarized and presented in Table 0.9:

Table 0.9: Summary of the Drainage structures in New Road Network


Condition of Structure (New Roads) in numbers



Bridge 2 0 555 0 557

Pipe Culvert (Concrete) 162 0 20,920 0 21,082



Box Culvert 2 0 680 0 682

Drift 16 0 1,447 0 1,463

Others 0 0 18 0 18

Sub Total 186 0 24,091 0 24,277

From the above summary it is observed that 88.80% of Drainage structures are

pipe culverts (Concrete). Box culverts of 2.81%, Drifts constitute to 6.10% of the

drainage structures while Bridges constitutes for 2.29% of Drainage structures.

100% of Bridges are in Poor condition

1% of Concrete Pipe Culvert are in good condition, however 99% of them are in

Poor condition

1% of Armco Pipe Culvert are in good condition, however 99% of them are in

Poor condition

44.82%

10.56%

2.27%

35.96%

58.31%

43.65%

28.86%

18.10%

30.52%

53.76%

71.06%

1.11%

0.61%

0.32%

0.00%

Paved

Gravel

Earth


Surf

ace

typ

e

Percentage Condition per surface type (Newly Opened Roads)





April 2018


100% of Others/Composite Pipe Culvert are in Poor condition

100% Box Culverts are in Poor condition

1% of Drifts are in good condition, however 99% of them are in Poor condition

100% Other type of structures are in Poor condition


The Inferences drawn above are for the currently captured road network and not for the entire zone. The same shall be updated in the subsequent submissions and shall be finalised during the final submission.

0.18 INFERENCES ON DEFLECTION MEASUREMENTS FOR PAVED ROADS

Falling weight Deflectometer measurements, Road laser Profiler and Roughness data collection has been carried out in all 13 Counties. About 4386km length has

557

21082

464 11 682 1463 18

Composition of Structure Type on New Road Network

Bridge




Box Culvert

Drift

Others

0.36%

0.77%

0.86%

0.29%

1.09%

0.00%

0.00%

0.00%

0.00%

0.00%

99.64%

99.23%

99.14%

99.71%

98.91%

Bridge




Box Culvert

Drift

OthersPercentage

Stru

ctu

re T

ype

Percentage Condition of Structure type on New Roads





April 2018


been completed for FWD measurements and roughness (using RLP) on Paved Roads and 10757km length of gravel roads are completed with Roughness data collection. The shape files were generated with the FWD data and overlaid onto the RICS database collected to have a check on the data collection manually and by FWD, the same was found to be within the range.

Average structural Number of the paved roads per Road Class is presented graphically below:

4.90 5.35 4.61

6.25

4.72 4.90 5.98

4.45 4.29 3.51

6.38

3.97

0.00

1.00

2.00

3.00

4.00

5.00

6.00

7.00

Ave

rage

Str

uct

ura

l Nu

mb

er

Road Class Average Structural…

County Wise Average Structure Number of Paved Road Obtained From FWD Analysis

5.96 4.60 4.26 3.87 3.92 4.55

3.55

8.37

0.00

1.00

2.00

3.00

4.00

5.00

6.00

7.00

8.00

9.00

A B C D E F G S

Ave

rage

Str

uct

ura

l Nu

mb

er

Road Class Average Structural Number

Average Structure Number of Paved Road Obtained From FWD Analysis




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0.19 ROUGHNESS DATA COLLECTION AND ANALYSIS INTERMS OF INTERNATIONAL ROUGHNESS INDEX

Roughness was collected using two different methodologies for paved and Gravel roads.

For Paved Roads Road laser Profiling was carried out using Digital Road surface profiler (DRSP) and along with the roughness data collection visual survey data was also collected.

For Gravel Roads Dynamic Roughness Index Measurement System (DRIMS) was used to collect only the roughness data.

0.19.1 Roughness data for Paved Roads

DRSP has been used to collect Roughness data for the Paved Roads and several analysis were carried out to determine

Pavement Condition Index (PCI) and its rating

Rut Depth in mm

IRI values and Rating

Potholes

Visual Condition Survey Index

Shoulder Rating and Drainage rating

The Average IRI PCI values and IRI values for the paved roads per road class and county is presented graphically below:

63 72

66 71 62

71 73 80

56 62 72

62 48

05

10152025303540455055606570758085

PC

I Val

ue

County PCI Value

County wise Average Pavement Condition Index (PCI) of Paved Roads




April 2018


69 81

72 64

71

57 49 52

45 52

75

05

10152025303540455055606570758085

A A_urb B B_urb C C_urb D E F G S

PC

I Val

ue

Road Class PCI Value

Average Pavement Condition Index (PCI) of Paved Roads

5.96 4.60 4.26 3.87 3.92

4.55 3.55

8.37

0.00

1.00

2.00

3.00

4.00

5.00

6.00

7.00

8.00

9.00

A B C D E F G SAve

rage

Str

uct

ura

l Nu

mb

er

Road Class

Average Structural Number

Average Structure Number of Paved Road Obtained From FWD Analysis




April 2018


3.7 3.7 4.6 4.2 4.7

6.3

4.2 4.0

10.4

5.3 3.8 4.3

6.7

0.0

2.0

4.0

6.0

8.0

10.0

12.0

Ave

rage

IR

I_m

/Km

County Average IRI

3.8 2.6

4.5 6.2

5.0

7.8 7.8 9.0

12.3

9.1

3.0

0.0

2.0

4.0

6.0

8.0

10.0

12.0

14.0


Ave

rage

IR

I_m

/Km

Road Class

Average IRI

Average IRI for Paved Roads in Coastal Zone

County wide Average IRI for Paved Roads in Coastal Zone




April 2018



Roughness data for Gravel roads in Good and fair conditions were collected using Dynamic Roughness Index Measurement System (DRIMS).

Analysis has been carried out for all counties and average IRI/Km of the county and per road class is graphically presented below:

6.8

11.0

8.2 9.1

10.0

7.0

9.3 8.8 7.4

6.4

9.3 10.4

5.1

0.0

2.0

4.0

6.0

8.0

10.0

12.0

Ave

rage

IR

I_m

/Km

County Average…

Countywise Average IRI for Gravel Roads for Coastal Zone

7.5

3.8

9.1

7.0

9.1 8.3

9.3 9.5 9.8 9.0

0.0

2.0

4.0

6.0

8.0

10.0

A A_urb B B_urb C C_urb D E F G

Ave

rage

IR

I_m

/Km

Road Class Average IRI_m/Km

Average IRI for Gravel Roads in Coastal Zone




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0.20 CONSTRAINTS FACED AND MITIGATION MEASURES ADOPTED

Matrix of Constraints faced and the corresponding Mitigation measures adopted are given in Table 0.10:

Table 0.10: Constraints Faced and Mitigation measures

Sl. No. Constraint faced Mitigation measures

1 Difficulty in organizing an all-inclusive entry-level meeting and validation meetings for all stakeholders.

Planned to meet with different stakeholders at their convenience.

2 Difficulty of some (narrow) roads not getting meaningful names.

Consultants shall put all possible efforts to obtain Road names from local interaction, and for the roads without any names shall be named as per Origin – destination/land marks connecting the road.

3 Bad weather, heavy rains Scheduling of field activities of every day with observation of weather prediction from News/websites.

4 Security Alert Zones Several security alert zones were encountered in Lamu, Garissa and Tana River County where obtaining security assistance has delayed the progress.

Consultants has liaison with the security agencies and tried to complete the survey in most part, and is still process of obtaining the security for much sensitive areas.

5 Traffic congestion Traffic Congestion in Urban areas of Nairobi, Mombasa etc. being completely unpredictable had delayed the progress to a great extent, but consultant has adopted non-peak hours to carry out the data collection to compensate on the time lost during peak hour traffic jams.




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0.21 CONCLUSIONS

The consultant has completed survey of 55,001.10 km of classified roads out of 54,613.2 km and 35,102.67 km out of estimated 30,000 km of narrow roads; in totality 90,103.77 km of road network has been surveyed.

35,102.67 km of narrow roads comprises of 17,687.90 km of narrow roads having road reserve less than 9m and 17,414.78 km of newly opened/upgraded roads having road reserve width of greater than or equal to 9m.

Total of 24,091 drainage structures were also inventoried and assessed for their conditions of which 21,270structures are found along classified roads; 1,193 along narrow roads and 1,628are found along the newly opened/upgraded roads.

It has been evident that the road network in coastal zone surveyed till date has a major portion of earth roads comprising of 65.50% of the total road length, 22.68%of the road network is captured as gravel roads and barely 6.61% paved roads, while tracks constitute only 5.21% of the road network.

On broad overview majority of paved roads are in good to fair condition (42.29% and 37.53% respectively), gravel roads are predominantly in fair to poor condition (56.31% and 32.94% respectively) and Earth roads are mostly in poor condition (72.91%).

Bridges are predominantly in good to fair condition (55.92% and 37.14% respectively) Pipe Culverts are also in good to fair condition (46.23% and 32.25% respectively), Box culverts are mostly in good condition (79.32%) and drifts also fall in good to fair condition (34.17% and 45.93% respectively).

Average SN is varying between 3.51 (Narok County Roads) to 6.38 ( Taita –Taveta) county-wise and it is varying between 3.55 ( G class ) to 8.37 ( S) for road class S to G.

For Paved IRI of Road Class S to G is varying between 3m/km to 12.3m/km and County- wise 3.7m/km to 10.4m/km. Class S Road has 3m/km average IRI where as F class road has average IRI 12.3 m/km

IRI for gravel road of Class A to G is varying between 3.8 m/km (class A) to 9.8 m/km (Class G) and county-wise between 5.1m/km (Tana River) to 11 m/km (Kajiado).

1. INTRODUCTION AND

PROJECT BACKGROUND




April 2018

Introduction and Project Background 1-1

1. INTRODUCTION AND PROJECT BACKGROUND

1.1 GENERAL

The Government of Kenya (GoK) through the Ministry of Roads undertook a Road Inventory and Condition Survey (RICS) between 2001 and 2004 with financing from the World Bank. The study mapped and classified 61,946 Km of roads. The data was stored as Geo-database for classified roads in Geographical Information System (GIS).

Further, between 2007 and 2009 Kenya Roads Board (KRB) with financing from the Nordic Development Fund and World Bank undertook another RICS to map the unclassified roads. This unclassified roads inventory captured a total of 98,940 Km to bring the total inventoried network to 160,886 Km, which is held in a consolidated GIS database at KRB.

The Inventoried roads network covers roads with way-leave reserves of 9m and above. However, large components of Kenya’s road network consisting of narrow roads and tracks with road reserves between 4m and 9m (exclusive) were not mapped. However, these roads provide important access in urban and rural areas. The network of narrow road is estimated between 60,000 Km and 90,000 Km. Similarly, subsequent inventory changes to the inventoried classified network (newly constructed and upgraded roads) are not fully captured and it is expected that the road condition data in the KRB geo database is out-dated and shall require Updation.

KRB intends to map the newly constructed and upgraded roads and to update the road condition data for the entire road network. In addition there is a need to have narrow roads mapped and brought into the planned roads regime. These form the basis of the current study, which is funded by GoK through the credit received from the International Development Association (IDA) towards the cost of Kenya Transport Sector Support Project.

For purposes of this study, the country’s road network has been packaged into three (3) geographic zones namely; 1) Western, 2) Central and 3) Coastal zones.

As per the TOR, the details of classified road network length are presented in Table 1.1.

Table 1.1: Details of Classified Road Length (as per ToR) in all 3 Geographic Zones

Sl. No. Zone No. of Counties Total length of Classified Roads (Km)

1 Western 21 53,397.4

2 Central 13 52,875.0

3 Coastal 13 54,613.2

Total 47 160,885.6




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1.2 PROJECT BACKGROUND

The Coastal Zone package of this study consists of 13 counties and is demarcated in Figure 1.1 (cyan color). The length of classified road network in Coastal Zone is 54,613.2 Km of which 4,3531 Km is paved roads. The length of narrow roads for inventory and condition survey is estimated to be around 30,000 Km in each zone.

The details of classified road network in the respective counties of Coastal zone are given in Table 1.2.

Table 1.2: Details of Classified Road network in Coastal Zone

Sl. No. County name and number Total Length of Classified Roads

(Km)

1 Garissa – 7 2,999.0

2 Kajiado – 34 5,858.2

3 Kilifi – 3 3,800.7

4 Kitui – 15 8,593.1

5 Kwale – 2 3,521.2

6 Lamu – 5 843.4

7 Machakos – 16 5,926.0

8 Makueni – 17 7,744.8

9 Mombasa – 1 964.2

10 Nairobi – 47 2,942.1

11 Narok – 33 4,612.2

12 Taita Taveta – 6 3,954.2

13 Tana River – 4 2,854.2

Total 54,613.2

1 Reference from response to question no 29; Minutes of Pre-Proposal conference held on 18th August 2015




April 2018


Figure 1.1: Demarcation of Zones and its Counties along with Details of Classified Road Network in each Zone




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1.3 CONTRACT DETAILS

The contract details of the project are given in Table 1.3.

Table 1.3: Contract Details of the project

Sl. No.

Item Details

1 Study Title Provision of Consultancy Services to Undertake Road Inventory and Condition Survey for Coastal Zone in Kenya

2 Financier Kenya Transport Sector Support Project funded by World Bank

3 Client Kenya Roads Board

4 Consultant Intercontinental Consultants and Technocrats Pvt. Ltd. In Joint venture with Geodev (K) Ltd. of Kenya.

5 Date of Award 1st August, 2016

6 Contract Price USD 945,342/- and KES 152,720,000/-

7 Revised Contract Price -

8 Commencement date 15th August, 2016

9 Original Contract Period 15 months

10 Original Completion date 15th November, 2017

11 Extension of time applied for

30th April 2018

12 Extension of time approved

30th April 2018

13 Revised Contract Period 20.5 months

14 Revised Completion date 30th April 2018

15 Time elapsed 12 months

16 Percentage Contract Period elapsed

100%

17 Percentage of assignment completed

100% Fieldwork is completed and Overall including reporting 100% progress achieved.

18 Invoices Submitted (No., Amount)

No1- USD 189,068.4/- and KES 30,544,000/-

No2- USD 141,801.3/- and KES 22,908,000/-

No3- USD 189,068.4/- and KES 30,544,000/-

No4- USD 189,068.4/- and KES 30,544,000/-

No5- USD 141,801.3/- and KES 22,908,000/-




April 2018


Sl. No.

Item Details

19 Amount Certified to date USD 850,808.3/- and KES 137,448,000/-

20 Percentage of Contract Amount Certified to date

90%

21 Amount Paid to date USD 850,808.3/- and KES 137,448,000/-

22 Percentage of Contract Amount Paid to date

90% of USD component and 90% of KES component

1.4 DELIVERABLES OF THE ASSIGNMENT

The description of deliverables during course of consultancy services as required by the TOR is given below.

Inception Report: Summarize the review of previous RICS study undertaken and specify the approach and methodology to be adopted to determine exact fact and scope of services. The Inception report was submitted on 15th September 2016.

Monthly Progress Report: This report shall be submitted on 5th of every month outlining the Project progress. It also intimates the constraints faced by the consultant while carrying out the project activity and the mitigation measures implemented to counter act them.

1st Interim Road Register for at least 10,000 Km of Narrow Roads network and with updated road conditions for at least 18,000 Km of Classified Roads in the zone. Draft 1st Interim Road Register was submitted on 21st December 2016 and the final version was submitted in 2nd March 2017.

2nd Interim Road Register for at least 20,000 Km of Narrow Road network and with updated road conditions for at least 36,000 Km of Classified Roads in the zone. Draft 2nd Interim Road Register was submitted on 3rd May 2017 and the final version was submitted in 5th June 2017.

Working Paper on the Rural population living within 2 Km of all-weather roads. Draft was submitted in 5th July 2017 upon incorporating KRB’s comments on Draft Submission a Revised Final working paper was submitted on 27th February 2018.

Draft Road Condition and Inventory data collection and update framework for Classified Roads. Draft Submission was submitted in 18th July 2017 upon incorporating KRB’s comments on Draft Submission a Final was submitted on 12th March 2018.

Final Road Condition and inventory data collection and update framework for Classified Roads. Draft was submitted on 3rd May 2017 and the final version was submitted on 4th April 2018.




April 2018


Draft Final Road Register2 containing:

Draft Final Road Register for entire Narrow Roads Network in the zone Final Road Register with updated road conditions for Classified Roads in the zone.

Book of maps (hard copy) for Narrow Roads covering the entire zone A3 size at appropriate scales for the roads and other content as agreed by the client. Softcopies in ArcGIS map format and PDF format.

Final Road Inventory and Condition Data Collection Manual for Narrow Roads and Road Inventory and Condition Data Collection Manual for Classified Roads was submitted on [].

Final Road Inventory and Condition Report.

1.5 OUTLINE STRUCTURE OF FINAL ROAD INVENTORY AND CONDITION SURVEY REPORT

The Interim Road Register Report has been prepared in accordance with the ToR requirements and has been organized into seven (7) chapters supported by Appendices and additional data in Annexures. The Report structure is as described below:


Executive Summary

Chapter 1 : Introduction and Project Background

Chapter 2 : Approach and Methodology

Chapter 3 : Final Road Register Report

Chapter 4 : Instrumental Survey

Chapter 5 : RICS Geo-database and Data Integration

Chapter 6 : Data Validation

Chapter 7 : Conclusions and Way Forward

Appendices

Appendix 1 : County-wise Data Summaries of Interim Road Register

Appendix 2 : Road Condition Charts County-wise Data Summaries of Interim Road Register

Appendix 3 : Thematic Maps for summary on condition of Road network (County-wise)

Appendix 4 : Final Road Register for Narrow and Classified Roads (For entire Coastal Zone and County-wise)

2 The submission sl no 7, 8 and 9 (indicated in TOR) was combined into 1 submission as Draft Road Register Report as per communication vide letter no KRB/PP/32.28/A (85) dated 31st July 2017.




April 2018


Appendix 5 : Deflection measurement data for Paved Roads

Appendix 6 : Roughness data for Paved Roads and Gravel Roads(Good/Fair condition

Appendix 7 : Data Validation forms

Annexures

Annexure 1 : Field data collection manual and GPS User Guide

Annexure 2 : GIS data Processing Manual

Annexure 3 : Procedure Manual for Roughness and Falling weight Deflectometer tests

Annexure 4 : Final Road Register map

Annexure 5 : Maps For Structural Number of Road Surface (FWD Analysis)

Annexure 6 : Maps for International Roughness Index (IRI) of Road Surface (Paved Roads)

Annexure 7 : Maps for International Roughness Index (IRI) of Road Surface (Gravel Roads)

Annexure 8 : Data Dictionary

For the purpose of document handling the reports are bound in 7 volumes.

Volumes

Volume 1 : Main Report and Appendix 1, 2 and 7

Volume 2 : Part 1 of Appendix 4 Coastal Zone Road Register

Volume 3 : Part 2 of Appendix 4 County-wise Road Register

Volume 4 : Appendix 5 and 6 (FWD and IRI data)

Volume 5 : Appendix 6 contd. (IRI data for gravel roads)

Volume 6 : Annexure 1, 2, 3, 4 and 8 (Procedures Manual and Road Register Maps)

Volume 7 : Appendix 3 (Thematic Maps)

Volume 8 : Annexure 5, 6 and 7 (FWD, RLP and IRI maps)

2. APPROACH AND METHODOLOGY



Final Inventory and Condition Report

April 2018

Approach and Methodology 2-1

2. APPROACH AND METHODOLOGY

2.1 SCOPE OF CONSULTANCY SERVICES

There are two distinct tasks to be carried out as per the scope of consultancy services1:

Road Inventory and Condition Survey on Narrow Roads in the Zone; and

Condition Survey on the classified Road Network in the Zone

The brief of the scope of services are given below:

Mapping of the Narrow roads with Road Reserve less than 9m by field data collection.

Conduct inventory and condition survey of all classified roads to capture the inventory and condition changes that have occurred to the network that are presently not captured in the KRB RICS database.

The information obtained has to be integrated onto existing KRB RICS database.

Collect the Inventory and condition data for structures along the Narrow roads and for the Roads that are not captured/Newly opened/upgraded; in order to update the KRB RICS database.

Review the existing data dictionary and amend for the attributes that are to be collected for the Inventory and condition survey of Roads, Bridges, Culverts, Drifts, River, Town, Institution, Railway Crossing, facilities and Maintenance Problems.

Propose Road numbering system for Narrow Roads and integrate the same into existing RICS database.

Assessment of the percentage of rural population within 2 Km of all-weather roads.

Develop a guideline for Inventory and Condition Survey and for the equipment used (for both Classified Roads and Narrow Roads).

Collect Roughness data (International Roughness Index) and Falling Weight Deflectometer measurements at 1Km interval for all the Paved Roads.

Collect Roughness data (IRI) for the Gravel Roads in Good and Fair condition.

Carryout training and technology transfer for KRB and Road Agency staff.

Regulation of data collection of Narrow Roads with Road reserve width between 4m-6m:

Collect and process the narrow roads data for all roads with road reserves between 4m and 9m (exclusive). If by the time half of the area in any county is covered, the proportion of the roads with road reserve widths between 4m

1 For the details of activities to accomplish the above tasks please refer TOR.




April 2018


and 6m is more than 30%, the consultant shall inform the same to the client for a decision on whether to limit further data collection to roads with road reserves greater than 6m.

2.2 SUMMARY OF RESOURCES MOBILISED FOR FIELD ACTIVITIES

For Field data collection consultant had mobilized 20 data loggers reinforced with 3 field supervisors. Each data logger had been provided with local assistants/guides as a part of local community involvement. The local assistants/guides involved also facilitated in the identification of Narrow Roads.

20 data loggers had been grouped into 8 teams with 4 teams having 2 data loggers and 4 teams with 3 data loggers each.

Each data logger had been provided with a Handheld GPS unit and a Distometer for the data collection. For logistical movement each team was provided with double cabin 4wd vehicles along with 1 – 2 numbers of motorbikes depending on the number of data loggers in the team.

Each team was provided with a Laptop and Internet Modem for the data download/backup and data transfer.

2.3 APPROACH AND SURVEY METHODOLOGY

Technical Training for the Field Staff

Training for the field staff had been carried out from 5th October 2016 to 9th October 2016. Training was split into 2 stages for the ease of understanding and implementation by the field staff;

2.3.1 Technical training and Survey equipment training

This part of training was conducted on 5th and 6th of October 2016.

First day of the training included the Introduction to GPS survey and basics of JUNO 3B equipment. Field staffs were explained about the working methodology of the Global Positioning system (GPS) and were given hands-on exposure for the use of hand held GPS.

Second day of the training included Introduction to the RICS data dictionary. Attributes of inventory and condition survey from the data dictionary was explained to field staff by the Key Experts and condition rating of the Roads and structures were explained with the help of pictorial representation. A handbook of field survey was provided to every field team for quick reference. The key experts for the understanding of field staff explained the methodology of field survey like allocation of survey units and methodology for Identification and to conduct the survey of the narrow roads and classified roads to avoid data gaps and duplication.

2.3.2 Field training on the data collection

This fragment of the training was conducted from 7th to 9th of October 2016.

Field data collection training was conducted in Kajiado County in the Kiserian Area. The area was selected based on anticipated low traffic volume on the road. Also the area had a good mix of paved and unpaved roads and it was




April 2018


expected the area will have a rich diversity of road features and road conditions.

Field staff were accompanied by Key experts and were illustrated the attributes to be collected for the Inventory survey of the Roads and structures. Field staff were also illustrated the basis for the Condition rating of Paved, Gravel, Earth Roads and Tracks.

Data downloading and verification for the correctness and completeness was illustrated by overlaying the collected data onto KRB RICS database and satellite imageries.

Data collection procedure is detailed in Field data collection and GPS user guide attached as Annexure 1.

2.4 STAKEHOLDERS PARTICIPATION

2.4.1 Kick-off Work shop

KRB had arranged a workshop on 29th September 2016 and invited all the stakeholders of the project for the purpose of

Sensitization of the planned project works;

Introduction of the consultants to the major stakeholders of the project;

Request the roads authorities and County Government officials to provide assistance to consultants during the field data collection activities; and

To make the stakeholders understand the objectives of the study, scope of the consultant studies, major outcomes of the project and planned field activities.

Major discussions, concerns and clarifications during the workshop were:

Clearing out the initial interpretations of the stakeholders about the project activities.

Completion of the Project organization structure by the inclusion of the Project Steering Committee.

Consultants have been introduced to stakeholders for bringing in cooperative relation, which will be helpful in obtaining assistance during field project activities.

Concerns raised by the stakeholders were mainly on

Road naming system;

Road numbering system;

Mapping of private roads;

Identification of Road Reserve; and

Basis of Condition rating of the roads.

Consultants in response to the concerns had provided clarification as below:




April 2018


Road naming system to be adopted shall be as per the data collection in the field with the help of local community participation; in case of names being not available the consultant shall propose a road name based on the area/facility/landmarks connected by the roads;

Road numbering system shall be developed for the narrow roads and discussed with stakeholders to arrive at an agreement on the system to be adopted;

Consultant has explained that this exercise is to map the public roads and the private roads shall not be under the purview of the study;

Identification of Road Reserve being the biggest challenge during the field data collection, consultant requested the stakeholders mainly the Road agencies and the county government officials to share the details available with them and consultant shall validate the data collected in the field by actual measurement of Road reserve; and

Consultant has explained that the visual Condition rating shall be carried out as per the Condition rating manual developed and the Roads Authorities and CRO’s shall validate the same after the completion of the data collection activity to arrive at a mutual agreement.

A steering committee consisting of major stakeholders was formed to review the progress of the exercise.

2.4.2 Inaugural Steering Committee meeting

The inaugural RICS Steering Committee meeting was held on 8th March, 2017 at the KRB Boardroom in Nairobi.

Key points discussed during the meeting are briefly given below:

The Consultants for the 3 zones had surveyed approximately in total of 88,000 Km classified roads and approximately 39,000 Km of narrow roads;

Presentations were given on all 3 zones covering methodology, progress, findings and constraints faced;

Importance of involvement of the various road agencies during the process of data validation was explained. Validation of data collected shall clear up any discrepancies and ensure that the collected data is true and correct prior to incorporation into the Client’s geo-database;

Some parts of the country are regarded as security risk zones and the Consultants were encouraged to engage security agencies as widely as possible in order to ensure seamless execution of the project;

Stakeholders were encouraged to interact with the Consultants’ field teams as a means to facilitate the knowledge transfer process;

Rural roads which lacked Road names are proposed names on a from (Area name) – to (Area name) basis of connectivity provided by those roads, but in cases where place names prove difficult to obtain, names of facilities and institutions connected by those roads are used instead.




April 2018


Urban roads are named according to their existing gazetted street names (if available) in other case the same methodology of Road naming used for Rural Roads; and

KRB’s geo-database was presented and explained for better understanding of the project’s desired outputs.

2.4.3 2nd Inter – Agency Steering Committee meeting

Field Visit: The Inter-Agency Steering Committee Field Visit Meeting for the Coastal Zone was held on 30th May, 2017 at the Pride Inn Paradise Beach Resort, Mombasa. The meeting focused on the following:

Condition Rating Guidelines for RICS

Consultants’ data collection procedures

Field Visit to paved, gravel and earth roads

Consultants’ data processing procedures


The Consultants presented the Condition Rating Guidelines manual to participants and explained the criteria used in assigning condition ratings to roads and structures;

Field data collection procedures were outlined including equipment, software and the Data Dictionary;

The Consultants and the Client led Steering Committee members in a field visit to sample paved, gravel and earth roads in Mombasa as follows;

a) Survey Site 1 – 3rd Avenue (paved road)

b) Survey Site 2 – JCC Church Road (gravel road)

c) Survey Site 3 – Solian Estate Access Road (earth road)

Logging of attributes and road centreline data collection were demonstrated to participants at each site;

Data processing procedures were explained to participants, from downloading of raw field data to cleaning and editing of the data;

A post-visit plenary session was held to address matters arising from the field visit.

Steering Committee Meeting: The Steering Committee meeting was held on 31st May, 2017. The meeting focused on the following:

Opening remarks by the Executive Director, KRB;

Brief on field visit of 30th May, 2017;

Matters arising from Inaugural Steering Committee Meeting;

Status of RICS project;

Presentations of 2nd Interim Road Registers by Consultants;




April 2018


Plenary session;

Way forward; and

Closing remarks by the Executive Director, KRB


The Executive Director, KRB, in his opening remarks, stressed on the need for all parties to work closely in ensuring the generation of a reliable and concise geo-database;

The Executive Director, KRB urged road agencies to update their road network conditions routinely and to adopt and follow stringent update regimes. He further stressed upon the importance of road agencies being accountable for their networks and assuming ownership of their networks accordingly;

Participants were briefed on the previous day’s field visit proceedings, detailing the pre-visit briefing, the field visit, and the post-visit briefing and plenary session;

In matters arising from the Inaugural Steering Committee Meeting held on 8th March, 2017, participants went through the minutes of the meeting, highlighting points of discrepancy and requiring clarification.

The current status of the RICS exercise was explained, preceded by details of previous studies and the aims of this study. The Consultants’ submissions were detailed, as well as the constraints faced by the Consultants during data collection. Stakeholders were urged to cooperate with the Consultants particularly during the data validation exercise so as to ensure reliable data;

Team leaders of each of the 3 zones gave presentations on the 2nd Interim Road Register, detailing methodology, progress, inferences derived from the 2nd Interim Road Register, constraints faced, security concerns and the way forward. The Consultants reported that a total of 180,408.70 Km of roads had been surveyed across the 3 zones as at submission of the 2nd Interim Road Register;

A plenary session was held to address the concerns arising from the presentations.

Going forward, stakeholders were urged to participate fully in the data validation exercise.

The Executive Director, KRB, in his closing remarks, emphasised on the need for a thorough and rigorous data validation exercise so as to avoid misinformation and to produce a reliable and accurate geo-database which shall be core to planning of future maintenance regimes.




April 2018


2.5 FIELD DATA COLLECTION OF CLASSIFIED AND NARROW ROADS

2.5.1 Updation of the Inventory and Condition survey data for Classified roads

One of the major tasks as per TOR is to Conduct the Inventory and Condition survey of the Classified Roads and capture the changes that have occurred to the Road network that is presently not captured in the KRB RICS database.

In order to accomplish the task, Consultant has adopted the following procedure:

Review the KRB RICS database for the attributes to be collected.

Detailed review of Data Dictionary was carried out and the same was updated with value additions and submitted to client for approval2.

The Geo referenced Map of high-resolution Google earth imagery Overlaid with previous RICS database maps were prepared. The maps were bifurcated into Grids covering 300 Sq. Km area (15Km X 20 Km) scaled to 1:20,000. The Grid maps shall act as guiding boundaries for the field teams to carry out the field activities. Field teams were advised to maintain overlap of 100 m at the grid boundaries to avoid missing data. A sample grid map and Index map used for field survey is portrayed in Figure 2.1 and Figure 2.2.

Survey teams were also equipped with Mobile devices uploaded with “Carry Map observer” application for the purpose of identifying the location of the team w.r.t the existing RICS database. The Snapshot of which is given below in Figure 2.3.

Apart from the road network data available in KRB RICS database the field teams shall also be collecting the roads that are newly opened/upgraded to classified road standards from narrow road standards. Identification of these new roads shall be done using satellite imageries, Local community involvement and with the help of information obtained by Field staff from Roads Authorities.

2 The adopted data dictionary along with its description is presented in Annexure 1.




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Figure 2.1: Sample of Grid map used by the field team

Figure 2.2: Sample of Index map provided along with Grid map




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Figure 2.3: Snapshot of Carry Map Observer

2.5.2 Inventory and Condition Survey data collection for Narrow Road

Roads having Road reserve less than 9m are considered as Narrow roads. Narrow Roads not being part of existing KRB RICS database needs to be mapped for Inventory and condition data. The identification of the narrow roads was done using satellite images and involvement of local communities and from the information obtained from field staff of Roads Authorities and CRO’s.

The Survey teams collected the Inventory and Condition details (as per the attributes of data dictionary which was preloaded) for Road, Major structures like Bridges, cross drainage structures, towns and facilities using Trimble Juno 3B handheld GPS units.

Teams used a consistent procedure of surveying Roads found on one side of the accessing road in the direction of travel, before surveying the narrow roads found on other side of the accessing road.

Classified Paved Roads were observed first for the data collection, followed by gravel roads. Branches of these roads are surveyed using the methodology defined above.

Once the data collection is complete on one survey unit the data was projected onto satellite imageries and KRB RICS database was overlaid to identify the missing roads/data. Geospatial co-ordinates of the missing data were shared with the field teams to collect and ensure the extensiveness of every survey unit.

2.6 FIELD DATA COLLECTION FOR FALLING WEIGHT DEFLECTOMETER MEASUREMENTS AND ROUGHNESS DATA

Manuals Referred for conducting test:

ASTM D4694 – 09: Standard Test Method for Deflections with a Falling-Weight-Type;




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ASTM D 4695-96: Standard Test Method for Deflections with Impulse Load Falling-Weight Device;

Grontmij, FWD User Manual, Pri 2100 and Primax Series

2.6.1 General

Falling Weight Deflectometer is a vehicle-mounted or towed device that records pavement surface deflection bowls at discrete test points on the pavement surface. Surface deflections are measured at distances ranging from 0 mm to a user-defined maximum (to 2,100 mm) from the center of an impulse test load. The load is applied to the pavement surface through a standard loading plate; normally 300 mm in diameter, by a falling weight with a variable drop height while the FWD is at rest. Detailed procedure manual for roughness and falling weight deflectometer tests is attached as Annexure 3.

Figure 2.4: Primax Falling weight Deflectometer

Deflection measurements were conducted on outer lanes at intervals of approximately 1.0 km on the outer wheel path (OWP). At each drop point,




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readings were taken for the nine (9) consecutive geophone points of 0, 20, 30, 60, 90, 120, 150, 180, and 210 cm. The parameter recorded during a FWD test include GPS location, linear reference, deflection readings, test temperature, test load and pulse time as depicted below as a snapshot of raw data file

2.6.2 Equipment, apparatus and materials

Entire instrument for measuring deflections on flexible pavement majorly consists of following equipment/apparatus.

a) Displacement sensor: Geophone

b) Loading Cell: Strain Gauge Bridge

c) Loading plate: diameter of 300 mm with a ribbed rubber pad of at least 5 mm thickness

2.6.3 Automatic data quality checks

The data acquisition system includes software to automatically check and identify:

Decreasing deflections: a check to ensure the deflections decreases with distance from the impact;

Out of range – a check on the magnitude of the deflection;

Load variation – a check that the load is within the specified tolerance;

Deflection variation – Ensure the geophone deflections are within a specified tolerance; and

Sensor checks – automatic system checks of the load cell and deflection sensors.

2.6.4 Manual data quality checks

Further checks manual checking of the same parameters, for each test result, is permitted and carried out after the exercise.

2.6.5 Calibration and Validation

This test method requires a two-part calibration of FWD equipment, as follows:

An annual fully traceable reference calibration that must be current at time of data collection

A relative calibration performed regularly between reference calibration exercises.




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Reference calibration of the load cell, deflection and temperature sensors and Relative calibration for deflection sensors against each other has been done.

2.6.6 Data collection procedure

Test load: A target-applied stress of 707 KPa (corresponding with a load of 50 KN) has to be used. Actual test loads has been observed to be within 10% of the target load level.

Deflection sensor spacing’s: FWD devices allow for a range of deflection sensor spacing’s to be used during testing. The details of sensors used are presented in Table 2.1.

Table 2.1: Deflection sensor spacing

Number of deflection sensors

Sensor spacing’s (mm)

(Measured from the Centre of the applied load)

9 0, 200, 300, 600, 900, 1200, 1500, 1800, 2100

2.6.7 Deflection survey

Paved Roads have been identified in all the counties and Maps were prepared for identification.

The same were uploaded to mobile device using Google maps (KML files) and carry map observer to help navigation to desired locations.

FWD device mounted onto the vehicle has been transported to desired test location and the loading plate has been positioned over the test point. The test location has been cleaned of all loose stones and debris to ensure that the loading plate and deflection sensors are properly seated;

The loading plate and the sensors were lowered to ensure that they are resting on a firm and stable surface;

Loading weights were raised to the appropriate height to generate the target load level, and the weight was dropped. The peak load and the resulting peak surface deflections are recorded.

The pavement surface and ambient air temperature were measured at each test location.

Two additional load sequences were performed and the results were compared for the second and third test sequences. If the difference were found greater than 5% or 5 micron (whichever is greater) for any sensor, the test sequences were repeated to obtain consistencies.

The peak load, temperatures and deflection sensor readings resulting from the third and final drop constitute the test results.

The deflection measurements were carried out on outer lanes at intervals of approximately every 1 Km on the outer wheel path (OWP). At each drop point, readings were taken for the nine (9) consecutive geophone points of 0, 20, 30, 60, 90, 120, 150, 180, and 210 cm and have been as indicated in Table 2.2.




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Table 2.2: Geophone labeling

Geophone by offset

D0 D200 D300 D600 D900 D1200 D1500 D1800 D2100

Geophone by position

D1 D2 D3 D4 D5 D6 D7 D8 D9

Normalized geophone

naming ND1 ND2 ND3 ND4 ND5 ND6 ND7 ND8 ND9

2.6.8 FWD Deflection test results

Basic analysis by normalization was conducted on the collected data in view to report pavement response parameter of normalized pavement deflection data. FWD deflection readings were normalized to a standard pressure of 707 KPa to simulate a dual wheel assembly of 10-ton using the linear equation 3.1.

* + * +⁄

Where:

di is the deflection reading for the sensor located i mm from the center.

dn is the normalized deflection reading for the sensor located i mm from the center.

Li is the load level applied during the test

Lt is the target load level of 707 KPa based on the standard axle of 10-ton

2.6.9 Pavement strength in terms of Structural Number (Sn)

Structural number can be computed from FWD data. Based on the structural number, the comparative strength of different sections can be assessed. The structural number, sn can be computed from the formula below:

( ) ( )

Where nd1, nd5 and nd7 are deflections readings at 0mm, 900mm and 1500mm geophone offset respectively. The higher the structural number, the higher the strength.

2.6.10 Factors affecting the test

There are ranges of factors that may affect deflection measurements, and when encountered during surveys, the resultant test result has been marked and reported with a note or flag and the unusual features and events that might influence the results were recorded.

2.6.11 Reporting

The data to be collected and reported for each location shall include the following:

Location of the test point, target load level, impact peak load measured during the final (i.e. third) loading cycle; pavement deflection measured at




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each of the deflection sensors during the final loading cycle; normalized pavement deflections for each of the deflection sensors corresponding with the final loading cycle; and ambient air, surface and pavement temperature during the test.

Data precision

The precision of reported parameters should meet the minimum levels shown in Table 2.3.

Table 2.3: Minimum data precision levels for reporting

Parameter Minimum reporting precision

Impact peak load level 1 KPa

Deflection sensors 1 μm

Temperature 1°C

2.7 ROUGHNESS DATA COLLECTION AND ANALYSIS

Paved Roads: Surface condition using Digital Road surface profiler

Road surface Profiling (RSP) is conducted to assess riding quality of a road. RSP can be based on measurement of roughness, rut depth measurement and surface distress rating or a combination there of. Roughness, rutting and surface distress information in this report was collected using Hawkeye-2000 a Digital Road Surface Profiler (DRSP) shown in Figure 2.5.

Figure 2.5: DRSP used in Paved Roads Surfac` Profiling

The roughness data collected using the DRSP meets requirement of the Class 3 RTRRM equipment and Standard Test Method for Measuring the Longitudinal Profile of Travelled Surfaces with an Accelerometer Established Inertial Profiling Reference (ASTM E950/950M-09, 2009).




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2.7.1 Determination of Pavement Condition Index (PCI)

Riding quality shall be presented in terms of Pavement Condition Index (PCI). ASTM 6433 provides the standard method of determination of Pavement Condition Index (PCI) of a road pavement but is lengthy and appropriate for Project Level Analysis (PLA). Kenyan RDM Part V notes that PCI for flexible pavements may be computed from the following equations:

( ( ) ( )

Slope Variance (SV) is the mean slope variance of the in the two wheel paths, RD is the mean wheel path rut depth, C is the percentage of pavement surface with Class 2 or 3 cracking and crazing, P is the percentage of pavement surface patched and pot-holed while A, B, C, and D are coefficients depending on the equipment used for measuring slope variance.

This model for determination of PCI has been simplified further to enable determination of PCI at Network Level Analysis (NLA). The model adopted in consultation with the client for determination of PCI is as follows:

Visual Condition Index (VCI) is computed as an index ranging from 0 to 9 and based on three indices namely Potholes, general surfacing condition and Cracking each with range of 0 to 3 rating. is weighting for visual condition index which was set as 4.4. IRI is the outer wheel path roughness (m/Km) and is the IRI weighting which is set at 10. RUT is the outer wheel path rut depth (mm) and is the RUT weighting which is set at 10. The equation used for establishing the PCI is as follows:

The PCI value can range from 0 to 100 with section rated as GOOD having PCI value ranging from 0 to 25, FAIR rated section with values ranging from 25 to 45 and POOR rated section with PCI value ranging from 45 to 100. Arising from the above, the parameters to be established from the Digital Road Surface Profiler and to be used for establishing the PCI are:

IRI Roughness measurement in m/Km;

Rut Depth Measurement in mm; and

Visual Condition Survey (VCS)

2.7.2 Roughness Measurement – Longitudinal Profiling

Roughness data collected using the DRSP meets requirements of ASTM E950/950M-09. Roughness data on the DRSP is collected using a response type roads roughness method (RTRRM). For the purposes of determination of the Pavement Condition Index (PCI), roughness values ranging from 0.0 to 3.0m/Km are rated as 0, values ranging from 3.1 to 5.0 m/Km as 1, values ranging from 5.1 to 8.0m/Km as 2 and values above 8.0m/Km as 3.




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2.7.3 Surface Regularity (Rut Depth) Measurement - Transverse Profiling

Surface regularity collected using the DRSP meets requirement AASHTO PP 37-04, 1996 and ASTM E1703 / E1703M – 10, 2015. Several values of rut depth are collected using DRSP including centre and wheel paths rut depths. The values used in this report to compute pavement condition index is the outer wheel path rut depth. For the purposes of determination of the Pavement Condition Index (PCI), surface regularity values ranging from 0.0 to 8.0mm are rated as 0, values ranging from 8.1 to 16.0mm as 1, values ranging from 16.1 to 25.0mm as 2 and values above 25.0mm as 3.

2.7.4 Visual Condition Survey (VCS)

VCS was conducted to establish three main pavement surface condition parameters including the general surface condition, cracks and potholes (including patches). The defects were measured from pavement video using Hawkeye processing software as demonstrated in Figure 2.6.

Figure 2.6: Measurement of pavement pothole.

Pavement surfacing is required in order to protect the underlying pavement and support the vehicle tyres. The surface condition aspects rated include bleeding, whip off general surface condition and level of cracking rating. 0 to 3 rating scale was used with Rating 0 for the surfacing is competent with no distress, Rating 1 of for the surfacing is starting to show signs of slight ageing and minor isolated distress such as minor stripping and bleeding, Rating 2 for surfacing with scattered surfacing distress in the form of ravelling, stripping and surface cracking and Rating 3 of the surface is severely cracked and is in the process of disintegrating.

Potholes are indicative of either surface or pavement failures while patching is indicative of a pothole that has been restored. 0 to 3 rating scale with Rating of 0 for Not potholes or recent small patches, Rating of 1 for Isolated small potholes or patches, Rating of 2 for Scattered potholes of around 150 mm and several patches and Rating of 3 for General potholes or patches occur along the segment.




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Cracking and pumping can have a wide range of underlying causes but is generally indicative of a distressed pavement that needs attention. A 0 to 3 rating scale with Rating of 0 for pavement with no significant cracks, Rating of 1 for the pavement with isolated minor cracking, Rating of 2 for pavement with scattered cracking, sometimes associated with minor pumping occurs and Rating of 3 for pavement sections is generally cracked and the cracks are often associated with potholes.

2.7.5 Off-Carriageway Condition and Rating

Paved Shoulder condition and Rating

The condition of all shoulders along paved roads is to be rated as GOOD, FAIR and POOR. As the primary purpose of the shoulder is to allow vehicles to use the shoulder in case of emergencies. Good shoulder condition is which a vehicle is easily able to run completely off the lane onto the shoulder at a speed of around 1/3 of the average travel speed on the road. Edge drop is typically less than 50 mm and the shoulder width is 1.5 m and above. Shoulder condition is rated as FAIR if it can be used with minor difficulty to pull off the road. Edge drop is typically less than 75 mm and the overall width of the shoulder range around 1.0 m. Poor condition when it cannot be used by a vehicle in emergencies or can only be used partially by a vehicle with around 1.5 m or more of the vehicle remaining in the carriageway.

Figure 2.7: Fair shoulder collected in this survey




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Figure 2.8: Poor Shoulder condition.

2.7.6 Road network Drainage Condition and Rating

The condition of the drainage off the road and its surroundings is rated in view of its overall effect on the performance of the road and its users. The drainage condition is rated as GOOD if ensure effective drainage off the road, alongside the road and across the road. Longitudinal drainage channels are in a fair condition with minimal erosion and siltation being visible. Minimal or no signs of standing water alongside the road or of lush vegetation in the floor of the channels.

FAIR rating is when road cross section is satisfactory but drainage channels are blocked or eroded. Standing water often occurs in the rainy season and lush vegetation is present in the floor of the drainage channels. POOR drainage rating is adopted when the road cross section and related drainage channels do not make sufficient provision for drainage and the road is in danger of getting washed away or becoming unpassable in the next rainy season.

Figure 2.9: Poor drainage condition on a road section




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2.7.7 Gravel roads roughness measurement

Two types of equipment used for roughness data collection are:

Dynamic Roughness Index Measurement System (DRIMS).

Roughness equipment as shown in Figure 2.10.

Figure 2.10: Roughmeter III used for gravel roads roughness measurements.

2.7.8 Roughness Value Rating

Therefore, the roughness values for gravel roads ranging from 0 to 10 m/Km shall be rated as GOOD, values ranging from 10.0 to 16.0 m/Km shall be rated as FAIR and values above 16.0 m/Km as POOR.




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2.8 DATA PROCESSING3

Data collected in field has been transferred to Nairobi office for compilation and processing. The procedure adopted is given below:

2.8.1 Data Downloading and Data Transferring

Each survey team is assigned a Laptop and an Internet Modem to facilitate data downloading, backup and Transferring. Data file is downloaded from GPS unit receiver onto Laptop. The downloaded data is backed up and a copy of it is mailed to Nairobi office for further processing.

Each data folder will contain feature data as well as feature photographs.

Standard format for file naming has been used. A typical data file name maybe A081709A*, where A- refers to Team A, 0817 refers to August, 2017 and 09A means that this was the first data file created between 9 AM to 10 AM if another data file was to be created before 10 AM it would be named as 09B and so on.4

2.8.2 Exporting of Data file to ARCGIS Shape file

In the Compilation office, data was downloaded and backed-up.

GPS Pathfinder Office Professional software was used to view the data and export it in ESRI ArcGIS format for further processing.

2.8.3 Data Cleaning Process

Data checking entailed procedures to verify and clean the data covering the following aspects:

Road geometry and alignment: Road Geometry has been reviewed in ArcGIS and corrected for any Kinks/bad data; human error (forgetting to pause after the data collection).

Satellite imageries and KRB RICS database were referred to rectify the bad sectors of alignment.

Attribute information: attributes collected were reviewed for any corrections required such as information on Road Name and Road number needs validation. Verification of such attribute information is being done from the existing RICS database and Gazetted Road Register for classified Roads and validation for Narrow roads shall be done by field staff of Roads authorities and CRO’s in due course.

Topology: Common Topology errors are:

Overshoot and Undershoots: A surveyor is unlikely to end a survey line precisely where it joins another road line, and may overshoot or undershoot. In such cases endpoints were snapped to the survey lines to remove access data/to fill the missing the connection.

3 For detailed GIS data Processing refer Annexure 2: GIS data Processing Manual

4 For details of Data Storage and security refer section 4 of Field data collection and GPS user guide

attached as Annexure 1.




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Loss of GPS Signal: The accuracy of a GPS data depends on amongst other things the strength of received Satellite signal and the number of satellites available to receiver. During the course of the survey satellite signal could be momentarily lost due to thick foliage cover, tall buildings, hillsides or interruption from strong magnetic fields by electric lines. Loss of signal for stretches less than 50mts are joined to the alignment in continuation and the stretch exceeding 50mts were resurveyed.

Intersect other lines: this occurs when the survey of a road continues without stopping at the junction with another road. Junctions were snapped and additional data was removed.

Incorrect Continuation of lines: If a surveyor pauses the GPS unit at the end of one road, and moves to a different location to start a new road and then resumes the data collection from the new location, a straight line is drawn. The straight line from pause point to resume point shall be deleted.

Duplicate roads/ features: Duplicity in data collection and features by different survey teams on overlapping sections are reviewed. Additional data from snapping point is removed.

Data gaps/missing features: Data was reviewed for the completeness using satellite imageries and KRB RICS database. Any missing data identified is being resurveyed to ensure extensiveness of the survey data.

2.8.4 Merging of Individual Data

Data merging was done for data in each team, for each day, across teams and subsequently for Particular County. Merging shall yield a single file for each county. The county shape files are used to create separate layer files for Classified Roads, Narrow roads with road reserve less than 6m, Narrow roads with road reserve between 6 and 9m and New roads with road reserve equal to or greater than 9m.

2.8.5 Extraction of Data for Interim Road Register

County shape files along with layer files were loaded onto ARCGIS and using attribute table feature the database files were extracted to prepare the Final Road Register.

2.9 PROPOSED ROAD NUMBERING SYSTEM

2.9.1. Road Numbering for Narrow Roads5 having road reserve less than 9m

For Narrow roads of road reserve less than 9m a road numbering system had been proposed by the consultant, which is as follows:

Format for every Road number shall be suffixed with NR representing Narrow Roads followed by the Hyphen and County number after which an underscore followed by the road number as a 3/4 digit number as applicable.

5 Road Numbering format for Narrow Roads was approved by KRB vide letter KRB/PP/32.28/VOL. I/A (141)

dated 21/03/2017.




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The numbering shall be assigned county-wise commencing in the south-west of a County and working in a broadly clockwise direction towards the north-east.

Numbering of all Narrow roads in a county from 001 to 999 (and so on if required) starting from south-west of the county and proceeding in a broadly clockwise direction to north-east. For example, the narrow roads in the Mombasa County will have the Prefix NR followed by the Hyphen and then County number (i.e. 1) and then the number of the road i.e. NR_01_001 to NR_01_999.

2.9.2. Road numbering and classification of the new/upgraded roads having road reserve greater than or equal to 9m6

Road numbering and classification of the new/upgraded roads having road reserve greater than or equal to 9m has been done on the basis of the Road Classification manual, July 2009.

After processing the field data, the identified new roads were bifurcated into Urban and Rural. Depending on the functionality of the road and observed traffic usage the class of the Road was defined. Numbering was allocated county-wise commencing in the south-west of a County and working in a broadly clockwise direction towards the north-east.

Challenges faced during Road numbering of Newly Identified Roads with Road Reserve greater than or equal to 9m

The Road classification and numbering as per Road classification manual 2009 was on Province base. Therefore to assign sequential number for particular class of Road is not practically possible at this stage.

All the links of the classified road of that category may require renumbering in case if sequential numbers are to be provided. However, same classification methodology of Road class has been followed by suffixing county code (instead of province code) before road number has been used, except for the inclusion of word ‘NEW’.

The proposed numbering system shall be as “assigned Class of the Road followed by Hyphen and county number followed by word “NEW” which is then followed by hyphen and road number which shall be starting from 001 and moves on sequentially.

Illustration: If a new road has been identified as class G in Mombasa county as per the functionality and its traffic usage that particular road shall be numbered as G_01_NEW_001 and immediate next road identified in the south west direction of same category shall be numbered in same format with next sequential number as G_01_NEW_002 and the same shall continue moving in clockwise direction towards north-east.

6 Road Numbering format for New Roads was decided during meeting held on dated 03/04/2017 at KRB

office.




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2.9.3. Road numbering system adopted for the Dual carriageway Roads

For dual carriageway roads, the left side of such a road with it western most point as it start is taken to be the main carriage way. The right side of the dual carriage takes an abbreviation “R” appended to the road number to denote the right side of the dual carriage.

There are some situations where a road is duelled as it passes through large urban centres and then reverts to normal two way road for other non-urban places where it passes through. Again from the start point of the road, the dual carriage sections on the right side of such a road are serialised with abbreviations R1, R2…..Rn where n denotes the nth section

2.9.4. Road numbering system adopted for the Narrow Roads crossing 2 or more counties:

For the Narrow roads crossing 2 or more counties the road naming convention shall remain same as followed for the Narrow roads; however instead of having 2 different road names for the same road in 2 different counties the road shall carry Road name for that county where the road passes for maximum length.

2.9.5. Road numbering system adopted for the Diversions and Realignments to main Roads

For realignment or diversions of an existing road, abbreviations A, B, C…. have been adopted. Example A5 (Loitoktok-Emali) appears to have abbreviations A5_A, A5_B, A5_C etc. for the old sections before realignment, while the new realigned road takes A5 as the road number. The reason is because these old sections were surveyed as being used by traffic even though the realignment has been done.

2.9.6. Road numbering system adopted for the Service Roads/Slip Roads

Previously we had adopted notation S to denote service road but it was later realised that S stands for a Road class, we propose to use “SR” to denote service road such that taking Thika superhighway (A2S) for instance, the various sections of the service roads will be appear like :

A2S : Left side of the main carriage way

A2S_R: Right side of the main carriage way

A2S_SLR1, A2S_SL2, A2S_SL3,……… A2S_SLn : The service roads on the left side of the road

A2S_R_SR1, A2S_R_SR2, …….. A2S_R_SRn: The service roads on the right side of the road

Where “n” denotes the nth section

2.10 CHALLENGES FACED DURING ROAD NAMING

Road naming for Classified Roads has been provided as per the Gazetted Road List and the Road naming for Narrow Roads and New Roads are collected in the Ground as per the areas or locations the Roads are connecting. In case of shorts




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routes connecting facilities are named as per facility to facility. However, Roads connecting same facility/locations are suffixed with the serial numbers.

Some of the Roads in rural areas are found to be placed where no major landmarks are identified and also it has been observed that there are network of Roads which are branching off from those roads in such cases providing unique road names is difficult at this stage.

These roads shall be given unique road names in co-ordination with CRO’s and site staff of Roads Authorities during validation process.

Illustrations of such cases are presented in Figure 2.11, Figure 2.12 and Figure 2.13.

Figure 2.11: Road Naming Issues in Kimana Section




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Figure 2.12: Road Naming Issues in Kiserian section

Figure 2.13: Road Naming Issues in Kiserian town

2.11 DETAILS OF DATA COLLECTION

Table 2.4 illustrates the County-wise details of data collection and the variation of actual surveyed roads w.r.t the existing KRB RICS database for classified roads and for Narrow Roads composition and variation of estimated Road network length and actual surveyed Road network length.




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Table 2.4: Data Collection details

Sl. No. County Name and

Number

Classified

Road Network length as per ToR

Estimated

Narrow Roads

network length as per ToR


Road Network

in the County


Road Network

Actual Surveyed Narrow Road network

% Composition of Narrow Roads with 4m<RR<6m

of total surveyed Narrow Roads

% Composition of Narrow Roads with 6m≤RR<9m


Total length of


including New

Roads

Total actual

length of Road

Network surveyed

in the County till date

(%) Progress

of Classified

Roads

(%) Variation of Narrow

Roads Narrow Roads with 4m<RR<6m

Narrow Roads with 6m≤RR<9m

Newly opened/Upgraded Road with RR≥9m

Completed

1 Garissa 2,999.00 1,647.40 4,646.40 2,694.23 74.00 574.99 2,042.44 11.45% 88.55% 2,691.77 5,386.00 89.84% 63.39%

2 Kajiado – 34 5,858.20 3,218.01 9,076.21 5,762.77 206.97 1,524.01 2,125.88 11.96% 88.04% 3,856.86 9,619.63 98.37% 19.85%

3 Kilifi – 3 3,800.70 2,087.79 5,888.49 3,947.79 301.18 1,484.07 1,549.68 16.87% 83.13% 3,334.93 7,282.72 103.87% 59.73%

4 Kitui – 15 8,593.10 4,720.34 13,313.44 8,851.90 753.32 3,328.14 363.33 18.46% 81.54% 4,444.79 13,296.69 103.01% -5.84%

5 Kwale – 2 3,521.20 1,934.26 5,455.46 3,475.13 24.29 439.24 829.63 5.24% 94.76% 1,293.16 4,768.29 98.69% -33.14%

6 Lamu 843.40 463.29 1,306.69 708.63 11.60 125.41 304.08 8.46% 91.54% 441.08 1,149.72 84.02% -4.79%

7 Machakos – 16 5,926.00 3,255.26 9,181.26 6,013.93 292.23 1,648.36 586.65 15.06% 84.94% 2,527.23 8,541.16 101.48% -22.36%

8 Makueni – 17 7,744.80 4,254.36 11,999.16 7,990.18 490.17 2,363.99 2,028.82 17.17% 82.83% 4,882.97 12,873.15 103.17% 14.78%

9 Mombasa 964.20 529.65 1,493.85 777.69 26.78 89.68 142.35 22.99% 77.01% 258.81 1,036.50 80.66% -51.14%

10 Nairobi 2,942.10 1,616.15 4,558.25 2,998.10 57.78 1,265.23 441.14 4.37% 95.63% 1,764.16 4,762.26 101.90% 9.16%

11 Narok – 33 4,612.20 2,533.56 7,145.76 4,998.93 89.76 1,162.89 3,793.97 7.17% 92.83% 5,046.62 10,045.55 108.39% 99.19%

12 Taita Taveta – 6 3,954.20 2,172.11 6,126.31 3,779.75 47.26 853.83 1,335.98 5.24% 94.76% 2,237.07 6,016.82 95.59% 2.99%

13 Tana River 2,854.20 1,567.86 4,422.06 3,002.07 17.60 434.78 1,870.83 3.89% 96.11% 2,323.22 5,325.29 105.18% 48.18%

Total 54,613.30 30,000.05 84,613.35 55,001.10 2,318.93 15,294.63 17,414.78 1.37 11.63 35,102.67 90,103.77 - -

The number of structures captured during the survey and the condition analysed is given Table 2.5.




April 2018


Table 2.5: Summary of Structures and its Condition for Entire Coastal Zone

Classified Roads

Drainage Structure Material type/Structure

type Structure Type

No. Total No.


Bridge -Road on structure - 211 162 30 0 403

Road under structure - 63 20 4 0 87

Sub Total 274 182 34 0 490

(%) Condition 55.92% 37.14% 6.94% 0.00% 100.00%

Pipe Culvert

Concrete

Dia≤600mm 4,973 4,659 2,644 0 12,276

600mm<dia≤900mm 3,265 1,403 600 0 5,268

Dia>900mm 607 263 54 0 924

Armco

Dia≤600mm 36 73 60 0 169

600mm<dia≤900mm 29 26 18 0 73

Dia>900mm 128 58 5 0 191

Others/Composite

Dia≤600mm 5 0 0 0 5

600mm<dia≤900mm 0 0 0 0 0

Dia>900mm 2 0 0 0 2

Sub Total 9,045 6,482 3,381 0 18,908

(%) Condition 47.84% 34.28% 17.88% 0.00% 100.00%

Box Culvert - 487 104 23 0 614

(%) Condition 79.32% 16.94% 3.75% 0.00% 100.00%

Drift - 424 570 247 0 1,241

(%) Condition 34.17% 45.93% 19.90% 0.00% 100.00%

Others - 13 0 4 0 17

(%) Condition 76.47% 0.00% 23.53% 0.00% 100.00%

Total Number of Cross Drainage Structures 10,243 7,338 3,689 0 21,270

Narrow Roads

Drainage Structure

Material type/Structure type Structure Type No.

Total No. Good Fair Poor Under Construction






April 2018


Sub Total 7 14 1 0 22

(%) Condition 31.82% 63.64% 4.55% 0.00% 100.00%

Pipe Culvert

340

71

19

328 194 0 862 0 780

41 14 0 126 0 115

1 3 0 23 0 20

2

2

3

2 1 0 5 0 4

0 0 0 2 0 1

0 0 0 3 0 2

0

0

0

0 0 0 0 0 0

0 0 0 0 0 0

0 0 0 0 0 0

Sub Total 437 372 212 0 1,021

(%) Condition 42.80% 36.43% 20.76% 0.00% 100.00%


(%) Condition 70.00% 25.00% 5.00% 0.00% 100.00%

Drift 58 46 26 0 130

(%) Condition 44.62% 35.38% 20.00% 0.00% 100.00%

Others 0 0 0 0 0

(%) Condition 0.00% 0.00% 0.00% 0.00% 0.00%

Total Number of Cross Drainage Structures 516 437 240 0 1,193

New Roads

Drainage Structure Material type/Structure type Structure Type

No.

Total No. Good Fair Poor

Under Construction



Sub Total 24 17 2 0 43

(%) Condition 55.81% 39.53% 4.65% 0.00% 100.00%

Pipe Culvert Concrete

Dia≤600mm 571 421 145 0 1,137

600mm<dia≤900mm 178 62 15 0 255

Dia>900mm 33 14 2 0 49

Armco Dia≤600mm 5 5 1 0 11




April 2018


600mm<dia≤900mm 2 1 3 0 6

Dia>900mm 0 0 0 0 0

Others/Composite

Dia≤600mm 0 0 0 0 0

600mm<dia≤900mm 1 2 0 0 3

Dia>900mm 1 0 0 0 1

Sub Total 791 505 166 0 1,462

(%) Condition 54.10% 34.54% 11.35% 0.00% 100.00%


(%) Condition 63.04% 32.61% 4.35% 0.00% 100.00%

Drift 32 28 16 0 76

(%) Condition 42.11% 36.84% 21.05% 0.00% 100.00%

Others 1 0 0 0 1

(%) Condition 100.00% 0.00% 0.00% 0.00% 100.00%

Total Number of Cross Drainage Structures 877 565 186 0 1,628




April 2018


2.12 RICS FIELDWORK REPORT AND PROGRESS

The consultant has completed survey of 55,001.10 Km of classified roads out of 54,613.2 Km and 35,102.67Km out of estimated 30,000 Km of narrow roads; in totality 90,029.43Km of Road network has been surveyed till date.

2.12.1 Classified Roads

Out of 55,001.10 km; 5,570.2 km is paved, 16,417.51 Km is Gravel, 30,922.99 Km of Earth roads and 2,080.58 Km of Tracks.

The Road Reserve ranges of the classified roads are summarized and presented in Table 2.6:

Table 2.6: Road Reserve details of Classified Roads

CLASSIFIED ROADS



Length (km) 1,420.81 14,854.02 32,235.88 3,266.18 3,224.19

2.12.2 Narrow Roads


Out of 17,687.90 Km of Narrow Roads; 148.85Km is Paved, 1,359.85 Km is Gravel, 14,793.64 Km of Earth roads and 1,385.56 Km of Tracks.

Out of 17,414.78 Km of New Roads; 237.16Km is Paved, 2,655.48Km is Gravel and 13,303.19km of Earth roads and 1,218.95Km of Tracks.

The Road Reserve ranges of the Narrow and New roads are summarized and presented in Table 2.7.

Table 2.7: Road Reserve details of Narrow and New Roads

NARROW ROADS AND NEW ROADS



Length (km) 2,393.27 15,294.78 17,169.77 239.00 6.30

The Total Road network captured is depicted graphically in Figure 2.14.




April 2018


Figure 2.14: Graphical presentation of Road network captured

2.13 CONSTRAINTS FACED DURING FIELD ACTIVITIES AND MITIGATION MEASURES IMPLEMENTED

Matrix of Constraints faced and corresponding mitigation measures implemented during the field data collection are given in Table 2.8.

Table 2.8: Constraints Faced and Mitigation measures


1 Difficulty in organizing an all-inclusive entry-level meeting and validation meetings for all stakeholders.

Planned to meet with different stakeholders at their convenience.

2 Difficulty of some (narrow) roads not getting meaningful names.

Consultants shall put all possible efforts to obtain Road names from local interaction, and for the roads without any names shall be named as per Origin – destination/land marks connecting the road.

3 Bad weather, heavy rains Scheduling of field activities of every day with observation of weather prediction from News/websites.

CLASSIFIED (Km)


RESERVEBETWEEN 4-6m

(Km)


RESERVEBETWEEN 6-9m

(Km)

NEW ROADSWITH ROAD

RESERVE MORETHAN 9m

Paved 5,570.02 9.25 139.60 237.16

Gravel 16,417.51 70.62 1,289.23 2,655.48

Earth 30,922.99 1,975.92 12,817.72 13,303.19

Other (Track) 2,090.58 337.48 1,048.08 1,218.95

Other (Track) Other (Track) Other (Track) Other (Track)

Earth

Earth

Earth Earth

Gravel

Gravel

Gravel Gravel

Paved

Paved

0

10,000

20,000

30,000

40,000

50,000

60,000




April 2018



4 Security Alert Zones Several security alert zones were encountered in Lamu, Garissa and Tana River County where obtaining security assistance has delayed the progress.

Consultants has liaison with the security agencies and tried to complete the survey in most part.

5 Traffic congestion Traffic Congestion in Urban areas of Nairobi, Mombasa etc. being completely unpredictable had delayed the progress to a great extent, but consultant has adopted non-peak hours to carry out the data collection to compensate on the time lost during peak hour traffic jams.

3. FINAL ROAD REGISTER REPORT




April 2018

Final Road Register Report 3-1

3. FINAL ROAD REGISTER REPORT

3.1 INTRODUCTION

This chapter outlines the inferences drawn from the Final Road Register for entire coastal zone.



Total of 22,670 Drainage structures were also inventoried and accessed for its conditions of which 20,126 structures are found along classified roads; 1,098 along Narrow roads and 1,446 are found along the newly opened/upgraded roads.

3.2 LAYOUT OF COUNTY-WISE DATA SUMMARIES OF FINAL ROAD REGISTER

Details of attributes collected as per agreed data dictionary are presented in the form of ARCGIS Shape files. However, Final Road Register and important information on condition is summarized and presented in Appendix 1.

The summary of information is presented for entire zone at first and reiterated county-wise. The summary of information presented shall be further bifurcated under the heads of Classified Roads, Narrow Roads and Newly opened roads separately.

3.2.1 Overall Summary of surface type and Road condition

For entire Coastal zone is presented in Table 1 and reiterated county-wise for Garissa, Kajiado, Kilifi, Kitui, Kwale, Lamu, Machakos, Makueni, Mombasa, Nairobi, Narok, Taita Taveta and Tana River County in Table 1a, 1b, 1c, 1d, 1e, 1f, 1g, 1h, 1i, 1j, 1k, 1l and 1m respectively.

3.2.2 Overall Summary of Surface type and road condition per road class


3.2.3 Overall Summary of Roads and its Road Reserve width





April 2018


3.2.4 Overall Summary of Drainage structures


3.3 COUNTY-WISE THEMATIC MAPS1

County-wise Thematic Maps are developed and attached as Appendix 3 to depict the classified roads; Narrow and New roads spread across every county. Thematic maps of roads per surface type is also presented to plant a grasp indication about the location, concentration and spread of road network per surface type across county.

3.4 LAYOUT OF FINAL ROAD REGISTER

Final Road Register shall contain Road ID, Road Class, Road Name, and length of Road within the county.

Final Road Register for entire Coastal zone is presented in Table 1 of Appendix 4 and the same is reiterated county-wise for Garissa, Kajiado, Kilifi, Kitui, Kwale, Lamu, Machakos, Makueni, Mombasa, Nairobi, Narok, Taita Taveta and Tana River County in Table 1a, 1b, 1c, 1d, 1e, 1f, 1g, 1h, 1i, 1j, 1k, 1l and 1m respectively. Final Road Register for all the above mentioned counties is attached as Appendix 4.

Book of Maps for Classified Roads and Narrow Roads are presented as per Final Road Register prepared and attached as Annexure 4.

3.5 SUMMARY ON THE LENGTH OF ROADS AND DRINAGE STRUCTURES

The summary on the Length of Roads surveyed county-wise is presented in Table 3.1 and summary of drainage structures is presented in Table 3.2.

1 A thematic map is a type of map specifically designed to show a particular theme connected with a

specific geographic area.




April 2018


Table 3.1: Summary on Length of Roads County-wise

Sl No

County Name and Number

Classified Road

Network length as per

ToR

Estimated Narrow Roads

network length as per

ToR


Road Network in the County


Road Network

Actual Surveyed Narrow Road network

% Composition of Narrow Roads with 4m<RR<6m


% Composition of Narrow Roads with

6m≤RR<9m of total

surveyed Narrow Roads

Total length of


including New Roads

Total actual length of

Road Network

surveyed in the County

till date

(%) Progress of Classified

Roads

(%) Variation of

Narrow Roads

Narrow Roads with 4m<RR<6m

Narrow Roads

with 6m≤RR<9m

Newly opened/ Upgraded Road

with RR≥9m

1 Garissa – 7 2,999.00 1,647.40 4,646.40 2,694.23 74.34 574.99 2,042 11.45% 88.55% 2,691.77 5,386.00 89.84% 63.39%

2 Kajiado – 34 5,858.20 3,218.01 9,076.21 5,762.77 206.97 1,524.01 2,126 11.96% 88.04% 3,856.86 9,619.63 98.37% 19.85%

3 Kilifi – 3 3,800.70 2,087.79 5,888.49 3,947.79 301.18 1,484.07 1,550 16.87% 83.13% 3,334.93 7,282.72 103.87% 59.73%

4 Kitui – 15 8,593.10 4,720.34 13,313.44 8,851.90 753.32 3,328.14 363 18.46% 81.54% 4,444.79 13,296.69 103.01% -5.84%

5 Kwale – 2 3,521.20 1,934.26 5,455.46 3,475.13 24.29 439.24 830 5.24% 94.76% 1,293.16 4,768.29 98.69% -33.14%

6 Lamu - 5 843.40 463.29 1,306.69 708.63 11.60 125.41 304 8.46% 91.54% 441.08 1,149.72 84.02% -4.79%

7 Machakos – 16 5,926.00 3,255.26 9,181.26 6,013.93 292.23 1,648.36 587 15.06% 84.94% 2,527.23 8,541.16 101.48% -22.36%

8 Makueni – 17 7,744.80 4,254.36 11,999.16 7,990.18 490.17 2,363.99 2,029 17.17% 82.83% 4,882.97 12,873.15 103.17% 14.78%

9 Mombasa - 1 964.20 529.65 1,493.85 777.69 26.78 89.68 142 22.99% 77.01% 258.81 1,036.50 80.66% -51.14%

10 Nairobi - 47 2,942.10 1,616.15 4,558.25 2,998.10 57.78 1,265.23 441 4.37% 95.63% 1,764.16 4,762.26 101.90% 9.16%

11 Narok – 33 4,612.20 2,533.56 7,145.76 4,998.93 89.76 1,162.89 3,794 7.17% 92.83% 5,046.62 10,045.55 108.39% 99.19%

12 Taita Taveta – 6 3,954.20 2,172.11 6,126.31 3,779.75 47.26 853.83 1,336 5.24% 94.76% 2,237.07 6,016.82 95.59% 2.99%

13 Tana River – 4 2,854.20 1,567.86 4,422.06 3,002.07 17.60 434.78 1,871 3.89% 96.11% 2,323.22 5,325.29 105.18% 48.18%

Total 54,613.30 30,000.05 84,613.35 55,001.10 2,393.27 15,294.63 17,414.78

35,102.67 90,103.77




April 2018


Table 3.2: Summary of Drainage Structures County-wise





Under Construction


Construction

Garissa

Bridge - - - - - - - - - - - - -

Pipe Culvert (Concrete) 62 124 59 - 6 2 1 - 7 23 4 - 288



Box Culvert 4 - - - 1 - - - 1 - - - 6

Drift 3 - - - - - 2 - 2 2 2 - 11

Others - - - - - - - - - - - - -

Sub Total 69 124 59 - 7 2 3 - 10 25 6 - 305

Kajiado

Bridge 26 4 2 - 1 2 - - 1 2 - - 38


Pipe Culvert (Armco) 55 2 2 - 1 - - - 1 - 1 - 62

Pipe Culvert (Others) 5 - - - - - - - - 2 - - 7

Box Culvert 82 3 - - 4 2 - - 4 2 - - 97

Drift 38 27 8 - - - 1 - - 1 7 - 82

Others - - - - - - - - - - - - -

Sub Total 1,373 425 125 - 59 13 6 - 150 79 27 - 2,257

Kilifi

Bridge 10 5 - - 1 2 - - - - - - 18


Pipe Culvert (Armco) 6 13 3 - 2 - - - - - - - 24


Box Culvert 48 3 - - - - - - - - 2 - 53

Drift 6 19 2 - - - - - - - - - 27

Others 12 - 4 - - - - - - - - - 16

Sub Total 624 654 311 - 47 15 5 - 79 79 27 - 1,841

Kitui

Bridge 20 25 - - 2 - - - - - - - 47


Pipe Culvert (Armco) 7 12 20 - 1 - 1 - - - - - 41


Box Culvert 30 8 1 - 1 - - - 1 - - - 41

Drift 186 181 80 - 46 29 12 - 10 4 2 - 550




April 2018






Under Construction


Construction

Others - - - - - - - - - - - - -

Sub Total 1,203 1,190 804 - 202 150 44 - 59 18 7 - 3,677

Kwale

Bridge 13 12 1 - - - - - 5 - - - 31


Pipe Culvert (Armco) 25 36 17 - - - - - 2 1 - - 81

Pipe Culvert (Others) 2 - - - - - - - - - - - 2

Box Culvert 27 7 - - - - - - 2 6 - - 42

Drift 6 10 8 - - - - - 1 5 - - 30

Others - - - - - - - - - - - - -

Sub Total 887 869 323 - 1 3 4 - 68 39 1 - 2,195

Lamu

Bridge 1 1 - - - 1 - - - 1 - - 4

Pipe Culvert (Concrete) 43 99 6 - 1 - - - 22 22 2 - 195

Pipe Culvert (Armco) 1 3 - - - - - - - - - - 4


Box Culvert 8 - - - - - - - - - - - 8

Drift - 1 - - - - - - - - - - 1

Others - - - - - - - - - - - - -

Sub Total 53 104 6 - 1 1 - - 22 23 2 - 212

Machakos

Bridge 43 39 7 - - 3 - - 8 1 - - 101


Pipe Culvert (Armco) 23 31 12 - 1 - - - - 1 - - 68


Box Culvert 45 19 6 - 6 2 - - 6 - - - 84

Drift 128 148 98 - 12 16 8 - 7 1 1 - 419

Others - - - - - - - - - - - - -

Sub Total 1,165 995 592 - 103 104 56 - 63 33 22 - 3,133

Makueni

Bridge 33 11 - - - - - - 1 1 - - 46


Pipe Culvert (Armco) 31 18 2 - 1 2 - - 3 - - - 57


Box Culvert 1 - - - - - - - 1 1 - - 3




April 2018






Under Construction


Construction

Drift 32 95 15 - - - - - 4 3 1 - 150

Others 1 - - - - - - - - - - - 1

Sub Total 1,305 768 165 - 14 13 1 - 48 44 10 - 2,368

Mombasa

Bridge 7 2 - - - - - - 2 - - - 11

Pipe Culvert (Concrete) 43 131 15 - 1 2 - - 10 11 2 - 215



Box Culvert - - - - - - - - - - - - -

Drift 1 - - - - - - - 1 1 - - 3

Others - - - - - - - - - - - - -

Sub Total 51 133 15 - 1 2 - - 13 12 2 - 229

Nairobi

Bridge 100 59 20 - 1 6 1 - 2 2 - - 191


Pipe Culvert (Armco) 1 - 1 - - - - - - - - - 2


Box Culvert 75 42 14 - 2 1 1 - 5 3 - - 143

Drift - 8 9 - - 1 1 - - - - - 19

Others - - - - - - - - - - - - -

Sub Total 585 813 626 - 41 120 104 - 39 46 17 - 2,391

Narok

Bridge 10 12 2 - - - - - 3 4 1 - 32


Pipe Culvert (Armco) 16 14 16 - - - - - - - 1 - 47


Box Culvert 47 1 - - - - - - 2 3 - - 53

Drift 2 - 1 - - - - - - - - - 3

Others - - - - - - - - 1 - - - 1

Sub Total 983 353 446 - 6 2 4 - 82 47 10 - 1,933

Taita Taveta

Bridge 9 7 - - 2 - - - 1 - - - 19


Pipe Culvert (Armco) 22 25 10 - - - - - - - - - 57





April 2018






Under Construction


Construction

Box Culvert 91 7 2 - - - - - 7 - - - 107

Drift 17 61 21 - - - 2 - 3 7 1 - 112

Others - - - - - - - - - - - - -

Sub Total 1,333 458 123 - 20 5 13 - 103 38 12 - 2,105

Tana River

Bridge 2 5 2 - - - - - 1 6 1 - 17

Pipe Culvert (Concrete) 570 410 87 - 13 7 - - 134 68 38 - 1,327

Pipe Culvert (Armco) 6 3 - - 1 - - - 1 4 2 - 17


Box Culvert 29 14 - - - - - - - - - - 43

Drift 5 20 5 - - - - - 4 4 2 - 40

Others - - - - - - - - - - - - -

Sub Total 612 452 94 - 14 7 - - 141 82 43 - 1,445

Provision of Consultancy Services to undertake Road Inventory

and Condition Survey for Coastal Zone in Kenya


April 2018


3.6 CLARIFICATION ON COMPLETENESS OF DATA COLLECTION IN CLASSIFIED ROADS

As an inference on the progress of classified roads depicted in Table 3.1, it is clear that data collection in counties of Garissa, Lamu, Mombasa is 89.84%, 84.02%, and 80.66%, respectively. However, in Taveta data collection is around 95.59%.

In Counties of Garissa and Lamu the huge variance is due to security alert zones mainly at the areas bordering to Somalia in the Garissa and in Lamu County areas north of Bargon Town towards the border with Garissa, where data collection couldn’t be carried out.

Mombasa has network of roads within private estates which were captured as public roads in previous RICS study for example a large portion of Nyali has network of private roads within estates where access was denied.

In Taita Taveta slight variation is due to invalid roads (Straight lines connecting two points with no actual alignment/GPS errors which weren’t corrected) in previous RICS database and the development undergone where the roads captured earlier no more exists.

3.7 OVERALL CONDITION OF ROADS COUNTY-WISE

Condition survey was carried out for Narrow Roads afresh and for classified roads to capture the condition changes on the roads in reference to the previous KRB’s RICS database.

Inference on the overall inventory and condition of roads (County-wise) has been drawn from the attributes collected during the field survey and are presented below.

The Condition charts were prepared class-wise per surface type for Classified, Narrow and New roads separately and are attached as Appendix 2.

3.7.1. Garissa County

Inferences on the overall condition of Classified Roads, Narrow Roads and Newly opened Roads are given in Table 3.3.

Table 3.3: Inferences on the overall condition of Garissa County Roads

Classified Roads Narrow Roads with 4m<RR<9m

Newly opened Roads with RR≥9m

Total of 2694.227 km of Classified roads are captured in this county

Total of 649.332 km of Narrow roads are captured in this county

Total of 2042.437 km of Newly opened roads are captured in this county




April 2018




Out of 2694.227 km; 37.874 km is Paved, 526.946 km is Gravel and 2129.145 km of Earth roads and0.262 km fall under other category of Roads.

Out of 649.332 km; 0 km is Paved, 0 km is Gravel and 596.978 km of Earth roads 52.354 km fall under other category of Roads.

Out of 2042.437 km; 2.779 km is Paved, 87.578 km is Gravel and 1757.903 km of Earth roads and 194.177km fall under other category of Roads.

83.94% of Paved Roads are in good condition,10.94% are in fair condition 5.12% is in poor condition and 0% is under construction.

NA 89.35% of Paved Roads are in good condition,10.65% are in fair condition and 0% is in poor condition and 0% is under construction

6.15% of Gravel Roads are in good condition,64.8% are in fair condition 26.05% is in poor condition and 3% is under construction.

NA 10.96% of Gravel Roads are in good condition,68.06% are in fair condition and 20.98% is in poor condition and 0% is under construction

0.25% of Earth Roads are in good condition,30.59% are in fair condition 67.42% is in poor condition and 1.74% is under construction.

0.75% of Earth Roads are in good condition, 28.81% are in fair condition and 70.43% is in poor condition and 0% is under construction.

1.89% of Earth Roads are in good condition,35.8% are in fair condition and 62.31% is in poor condition and 0% is under construction

0% of Other (Track) are in good condition,0% are in fair condition 100% is in poor condition and 0% is under construction.

0% of Other (Track) are in good condition, 2.65% are in fair condition and 97.35% is in poor condition and 0% is under construction.

0% of Other (Track) are in good condition,55.9% are in fair condition and 44.1% is in poor condition and 0% is under construction

3.7.2. Kajiado County

Overall condition of Classified Roads, Narrow Roads and Newly opened Roads are given in Table 3.4.

Table 3.4: Inferences on the overall condition of Kajiado County Roads









April 2018





Out of 1730.976 km; 3.996 km is Paved, 395.054 km is Gravel and 993.372 km of Earth roads 338.554 km fall under other category of Roads.



20.8% of Paved Roads are in good condition, 66.82% are in fair condition and 12.39% is in poor condition and 0% is under construction.

17.9% of Paved Roads are in good condition,56.47% are in fair condition and 25.63% is in poor condition and 0% is under construction

17.3% of Gravel Roads are in good condition,59.4% are in fair condition 22.93% is in poor condition and 0.37% is under construction.

22.03% of Gravel Roads are in good condition, 59.49% are in fair condition and 18.49% is in poor condition and 0% is under construction.

20.21% of Gravel Roads are in good condition,61.75% are in fair condition and 17.05% is in poor condition and 0.99% is under construction

7% of Earth Roads are in good condition,52.22% are in fair condition 40.58% is in poor condition and 0.21% is under construction.


5.04% of Earth Roads are in good condition,50.12% are in fair condition and 44.23% is in poor condition and 0.61% is under construction

1.13% of Other (Track) are in good condition, 21.11% are in fair condition 77.75% is in poor condition and 0% is under construction.

5.47% of Other (Track) are in good condition, 28.24% are in fair condition and 66.29% is in poor condition and 0% is under construction.

0.28% of Other (Track) are in good condition,29.65% are in fair condition and 70.07% is in poor condition and 0% is under construction

3.7.3. Kilifi County


Table 3.5: Inferences on the overall condition of Kilifi County Roads









April 2018







74.14% of Paved Roads are in good condition,23.29% are in fair condition 2.32% is in poor condition and 0.25% is under construction.

33.95% of Paved Roads are in good condition,66.05% are in fair condition and 0% is in poor condition and 0% is under construction.



12.9% of Gravel Roads are in good condition,50.33% are in fair condition and 36.77% is in poor condition and 0% is under construction.





0% of Other (Track) are in good condition,23.97% are in fair condition 76.03% is in poor condition and 0% is under construction.



3.7.4. Kitui County





April 2018


Table 3.6: Inferences on the overall condition of Kitui County Roads










0% of Paved Roads are in good condition,37.29% are in fair condition and 0% is in poor condition and 62.71% is under construction.

78.29% of Paved Roads are in good condition,21.71% are in fair condition and 0% is in poor condition and 0% is under construction


1.19% of Gravel Roads are in good condition,54.93% are in fair condition and 43.34% is in poor condition and 0.54% is under construction.

3.39% of Gravel Roads are in good condition,81.74% are in fair condition and 14.87% is in poor condition and 0% is under construction


0.02% of Earth Roads are in good condition, 22.96% are in fair condition and 76.85% is in poor condition and 0.18% is under construction.

0% of Earth Roads are in good condition,55.43% are in fair condition and 43.96% is in poor condition and 0.62% is under construction

0% of Other (Track) are in good condition,0% are in fair condition 100% is in poor condition and 0% is under construction.

0% of Other (Track) are in good condition, 0% are in fair condition and 100% is in poor condition and 0% is under construction.

0% of Other (Track) are in good condition,100% are in fair condition and 0% is in poor condition and 0% is under construction

3.7.5. Kwale County





April 2018


Table 3.7: Inferences on the overall condition of Kwale County Roads









50.52% of Paved Roads are in good condition,15.03% are in fair condition 30.88% is in poor condition and 3.57% is under construction.

0% of Paved Roads are in good condition,82.39% are in fair condition and 17.61% is in poor condition and 0% is under construction.


12.29% of Gravel Roads are in good condition,60.85% are in fair condition 26.86% is in poor condition and 0% is under construction.

0% of Gravel Roads are in good condition,45.17% are in fair condition and 54.83% is in poor condition and 0% is under construction.





0% of Other (Track) are in good condition,38.66% are in fair condition 61.34% is in poor condition and 0% is under construction.



3.7.6. Lamu County





April 2018


Table 3.8: Inferences on the overall condition of Lamu County Roads









0% of Paved Roads are in good condition, 100% are in fair condition 0% is in poor condition and 0% is under construction.



8.52% of Gravel Roads are in good condition, 87.17% are in fair condition 4.31% is in poor condition and 0% is under construction.

0% of Gravel Roads are in good condition, 43.62% are in fair condition and 56.38% is in poor condition and 0% is under construction.


0% of Earth Roads are in good condition, 36.61% are in fair condition 63.39% is in poor condition and 0% is under construction.



0% of Other (Track) are in good condition, 92.45% are in fair condition 7.55% is in poor condition and 0% is under construction.



3.7.7. Machakos County





April 2018


Table 3.9: Inferences on the overall condition of Machakos County Roads









53.32% of Paved Roads are in good condition, 36.7% are in fair condition 7.2% is in poor condition and 2.77% is under construction.

29.46% of Paved Roads are in good condition, 70.54% are in fair condition and 0% is in poor condition and 0% is under construction.


7.35% of Gravel Roads are in good condition, 57.97% are in fair condition 32% is in poor condition and 2.68% is under construction.



0.13% of Earth Roads are in good condition, 37.93% are in fair condition 61.93% is in poor condition and 0.02% is under construction.






3.7.8. Makueni County





April 2018


Table 3.10 Inferences on the overall condition of Makueni County Roads










0% of Paved Roads are in good condition, 19.46% are in fair condition and 80.54% is in poor condition and 0% is under construction.


7.47% of Gravel Roads are in good condition, 70.06% are in fair condition 21.88% is in poor condition and 0.59% is under construction.






0.37% of Other (Track) are in good condition, 30.03% are in fair condition 69.6% is in poor condition and 0% is under construction.

1.65% of Other (Track) are in good condition, 44.42% are in fair condition and 53.93% is in poor condition and 0% is under construction.


3.7.9. Mombasa County





April 2018


Table 3.11: Inferences on the overall condition of Mombasa County Roads









35.55% of Paved Roads are in good condition, 51.66% are in fair condition 10% is in poor condition and 2.78% is under construction.

43.6% of Paved Roads are in good condition, 45.56% are in fair condition and 8.02% is in poor condition and 2.82% is under construction.

60.88% of Paved Roads are in good condition,27.73% are in fair condition and 10.97% is in poor condition and 0.41% is under construction




0.06% of Earth Roads are in good condition, 31.67% are in fair condition 68.26% is in poor condition and 0% is under construction.

0% of Earth Roads are in good condition, 27.02% are in fair condition and 72.98% is in poor condition and 0% is under construction.

0% of Earth Roads are in good condition,18.96% are in fair condition and 79.83% is in poor condition and 1.21% is under construction




3.7.10. Nairobi County





April 2018


Table 3.12: Inferences on the overall condition of Nairobi County Roads













2.56% of Gravel Roads are in good condition, 57.47% are in fair condition and 39.58% is in poor condition and 0.39% is under construction.





0% of Other (Track) are in good condition, 0.52% are in fair condition 98.13% is in poor condition and 1.35% is under construction.



3.7.11. Narok County





April 2018


Table 3.13: Inferences on the overall condition of Narok County Roads







Out of 1252.648 km; 0 km is Paved, 34.203 km is Gravel and 1006.25 km of Earth roads 212.195 km fall under other category of Roads.



NA 14.42% of Paved Roads are in good condition,80.52% are in fair condition and 5.06% is in poor condition and 0% is under construction










3.7.12. Taita Taveta County





April 2018


Table 3.14: Inferences on the overall condition of Taita Taveta County Roads

Classified Roads Narrow Roads with

4m<RR<9m Newly opened Roads with RR≥

9m








0% of Paved Roads are in good condition, 100% are in fair condition and 0% is in poor condition and 0% is under construction.











3.7.13. Tana River County





April 2018


Table 3.15: Inferences on the overall condition of Tana River County Roads

Classified Roads Narrow Roads with

4m<RR<9m Newly opened Roads with RR≥

9m








0% of Paved Roads are in good condition, 100% are in fair condition and 0% is in poor condition and 0% is under construction.

77.02% of Paved Roads are in good condition,22.98% are in fair condition and 0% is in poor condition and 0% is under construction

0% of Gravel Roads are in good condition, 67.06% are in fair condition 32.18% is in poor condition and 0.76% is under construction.

0% of Gravel Roads are in good condition,100% are in fair condition and 0% is in poor condition and 0% is under construction.








The inference obtained above is photo shot of the current field activity and data analyzed.

3.8 SALIENT FEATURES OF THE ROAD INVENTORY AND CONDITION SURVEY





April 2018


3.8.1 Classified Road Network

Total of 55,001.10 Km of Classified roads are captured till in the entire Coastal Zone.

Out of 55,001.10 Km, 5,570.2 km is Paved, 16,417.51 Km is Gravel, 30,922.99 Km of Earth roads and 2,090.58 Km of Tracks.

45.36% of Paved Roads are in good condition, 36.74% are in fair condition, 15.64% is in poor condition and 2.26% are under construction.

8.91% of Gravel Roads are in good condition, 57.39% are in fair condition, 32.82% is in poor condition and 0.88% is under construction.

2.67% of Earth Roads are in good condition, 42.61% are in fair condition, 54.48% is in poor condition and 0.24% is under construction.

0.39% of Tracks are in good condition, 19.77% are in fair condition, 79.82% is in poor condition and 0.02% is under construction.


5,570.02

16,417.51 30,922.99

2,090.58

Surface Type Composition of Classified Roads

Paved

Gravel

Earth

Other (Track)




April 2018


The structures inventoried and the conditions accessed for classified Roads are summarized and presented in Table 3.16:





Sub Total

Bridge 274 182 34 0 490

Pipe Culvert (Concrete) 8,845 6,325 3,298 0 18,468



Box Culvert 487 104 23 0 614

Drift 424 570 247 0 1,241

Others 13 0 4 0 17

Total 10,243 7,338 3,689 0 21,270

From the above summary it is observed that 88. 90% of Drainage structures are pipe culverts (Concrete). Box culverts constitute of 2.89% and Drifts constitute to 5.91% of the drainage structures while Bridges constitutes of 2.30%.

56% of Bridges are in good condition and 37% are in fair condition, however 7% of them are in Poor condition

48% of Concrete Pipe Culvert is in good condition and 34% are in fair condition, however 18% of them are in Poor condition

45.36%

8.91%

2.67%

36.74%

57.39%

42.61%

19.77%

15.64%

32.82%

54.48%

79.82%

2.26%

0.88%

0.24%

0.02%

Paved

Gravel

Earth

Other (Track)

Percentage

Surf

ace

typ

e

Percentage Condition per surface type (Classified Roads)





April 2018


45% of Armco Pipe Culvert is in good condition and 36% are in fair condition, however 19% of them are in Poor condition

100% of others/Composite Pipe Culvert are in good condition

79% of Box Culverts are in good condition and 17% are in fair condition, however 4% of them are in Poor condition

34% of Drifts are in good condition and 46% are in fair condition, however 20% of them are in Poor condition

100% of other type of structures is in good condition.


Road reserves obtained from the field activities for the classified road network are given in Table 3.17.

55.92%

47.89%

44.57%

79.32%

34.17%

37.14%

34.25%

36.26%

16.94%

45.93%

6.94%

17.86%

19.17%

3.75%

19.90%

Bridge




Box Culvert

Drift

OthersPercentage

Stru

ctu

re T

ype

Percentage Condition of Structure type on Classified Roads





April 2018


Table 3.17: Road reserve details of classified roads

Classified Roads

Road Reserve

width (m) RR< 6m 6m≤RR<9m 9m≤RR<25m 25m≤RR<40m RR≥40m

Length (km)

0.00 16,274.83 32,235.88 3,266.18 3,224.19

3.8.2 Narrow Road Network

Narrow Road network of 35,102.67 Km consists of 17,687.90 Km of Narrow roads having Road Reserve less than 9m and 17,414.78 Km of newly opened/upgraded roads having Road Reserve width of greater than or equal to 9m.

Narrow Roads of 17,687.90 Km of Narrow Roads; 148.85Km is Paved, 1,359.85 Km is Gravel, 14,793.64 Km of Earth roads and 1,385.56 Km falls under the category of tracks.

36.70% of Paved Roads are in good condition; 39.88% are in fair condition, 21.79% is in poor condition and 1.62% is under construction.

11.15% of Gravel Roads are in good condition; 53.23% are in fair condition, 35.48% is in poor condition and 0.14% is under construction

1.64% of Earth Roads are in good condition; 34.45% are in fair condition, 62.84% is in poor condition and 0.08% is under construction.

1.65% of Tracks are in good condition; 30.51% are in fair condition and 67.84% is in poor condition.


16,274.83

32,235.88

3,266.18 3,224.19

Road Reserve Ranges for Classified Road Network

6m≤RR<9m

9m≤RR<25m

25m≤RR<40m

RR≥40m




April 2018








Bridge 14 1 - 24 39

Pipe Culvert (Concrete) 370 211 - 782 1,363

Pipe Culvert (Armco) 2 1 - 7 10

Pipe Culvert (Others) 0 0 - 2 2

Box Culvert 5 1 - 29 35

Drift 46 26 - 32 104

Others 0 0 - 1 1

Sub Total 437 240 - 877 1,554

148.85 1,359.85

14,793.64

1,385.56

Surface Type Composition of Narrow Roads

Paved

Gravel

Earth

Other (Track)

36.70%

11.15%

1.64%

39.88%

53.23%

35.45%

30.51%

21.79%

35.48%

62.84%

67.84%

1.62%

0.14%

0.08%

0.00%

Paved

Gravel

Earth


Surf

ace

typ

e

Percentage Condition per surface type (Narrow Roads)





April 2018


From the above summary it is observed that 88.48% of Drainage structures are pipe culverts (Concrete). Box culverts constitute for 2.25% and Drifts constitute to 6.76% of the drainage structures while Bridges constitutes for 2.51% of Drainage structures.

36% of Bridges are in good condition and 3% are in fair condition, however 62% of them are Under Construction

27% of Concrete Pipe Culvert are in good condition and 15% are in fair condition, however 57% of them are Under Construction

20% of Armco Pipe Culvert are in good condition and 10% are in fair condition, however 70% of them are Under Construction

14% of Box Culverts are in good condition and 3% are in fair condition, however 83% of them are Under Construction

44% of Drifts are in good condition and 25% are in fair condition, however 31% of them are Under Construction


39

1363

10 2 35

104

1

Composition of Structure Type on Narrow Road Network

Bridge




Box Culvert

Drift

Others




April 2018


Road reserves obtained from the field activities for the Narrow road network including newly opened roads is given in Table 3.19.


Narrow Roads and New Roads


RR< 6m 6m≤

RR<9m

9m≤

RR<25m 25m≤RR<40m RR≥40m

Length (km) 2,393.27 15,294.78 17,169.77 239.00 6.30

38.89%

39.67%

57.14%

56.25%

45.39%

55.56%

37.70%

28.57%

25.00%

36.88%

5.56%

22.62%

14.29%

18.75%

17.73%

Bridge




Box Culvert

Drift

Others Percentage

Stru

ctu

re T

ype

Percentage Condition of Structure type on Narrow Roads





April 2018


3.8.3 Newly opened Road Network

Newly opened Roads of 17,414.78 Km comprises 237.16 Km of Paved Roads, 2,655.48 Km of Gravel Roads, 13,303.19 Km of Earth roads and 1,218.95 km of Tracks.

44.82% of Paved Roads are in good condition; 35.96% are in fair condition, 18.10% is in poor condition and 1.11% is under construction.

10.56% of Gravel Roads are in good condition; 58.31% are in fair condition, 30.52% is in poor condition and 0.61% is under construction.

2.27% of Earth Roads are in good condition; 43.65% are in fair condition, 53.76% is in poor condition and 0.32% is under construction.

0.08% of Tracks are in good condition; 28.86% are in fair condition and 71.06% is in poor condition.


2,393.27

15,294.78 17,169.77

239.00 6.30

Road Reserve Ranges for Narrow and New Roads Network

RR< 6m

6m≤RR<9m

9m≤RR<25m

25m≤RR<40m

RR≥40m




April 2018



Table 3.20: Summary of the Drainage structures in New Road Network




Sub Total

Bridge 2 0 555 0 557

Pipe Culvert (Concrete) 162 0 20,920 0 21,082




237.16

2655.48

13303.19

1218.95

Surface Type Composition of Newly opened Roads

Paved

Gravel

Earth

Other (Track)

44.82%

10.56%

2.27%

35.96%

58.31%

43.65%

28.86%

18.10%

30.52%

53.76%

71.06%

1.11%

0.61%

0.32%

0.00%

Paved

Gravel

Earth


Surf

ace

typ

e

Percentage Condition per surface type (Newly Opened Roads)





April 2018





Sub Total

Drift 16 0 1,447 0 1,463

Others 0 0 18 0 18

Sub Total 186 0 24,091 0 24,277

From the above summary it is observed that 88.80% of Drainage structures are pipe culverts (Concrete). Box culverts of 2.81%, Drifts constitute to 6.10% of the drainage structures while Bridges constitutes for 2.29% of Drainage structures.

100% of Bridges are in Poor condition

1% of Concrete Pipe Culvert are in good condition, however 99% of them are in Poor condition

1% of Armco Pipe Culvert are in good condition, however 99% of them are in Poor condition

100% of Others/Composite Pipe Culvert are in Poor condition

100% Box Culverts are in Poor condition

1% of Drifts are in good condition, however 99% of them are in Poor condition

100% Other type of structures are in Poor condition


557

21082

464 11 682 1463 18

Composition of Structure Type on New Road Network

Bridge




Box Culvert

Drift

Others




April 2018


0.36%

0.77%

0.86%

0.29%

1.09%

0.00%

0.00%

0.00%

0.00%

0.00%

99.64%

99.23%

99.14%

99.71%

98.91%

Bridge




Box Culvert

Drift

OthersPercentage

Stru

ctu

re T

ype

Percentage Condition of Structure type on New Roads


4. INSTRUMENTAL SURVEY



Roughness and Falling Weight Deflectometer Measurements 4-1

4. ROUGHNESS AND FALLING WEIGHT DEFLECTOMETER MEASUREMENTS

4.1 COLLECTION OF ROUGHNESS DATA AND FALLING WEIGHT DEFLECTOMETER MEASUREMENTS

Pavement condition assessment is being done through the collection of falling weight Deflectometer measurement at every 1 km Interval for all Paved Roads

Roughness data (IRI)/Road surface condition on paved roads is being collected using Digital Road Surface Profiler (DRSP); and for gravel roads using Response Type Road Roughness Methods (RTRRMs);

Falling weight Deflectometer measurements, Road laser Profiler and Roughness data collection has been carried out in all 13 Counties. About 4386km length has been completed for FWD measurements and roughness ( using RLP) on Paved Roads and 10757km length of gravel roads are completed with Roughness data collection.

4.2 INFERENCES ON DEFLECTION MEASUREMENTS FOR PAVED ROADS

Basic analysis by normalization was conducted on the collected data in view to report pavement response parameter of normalised pavement deflection data. FWD deflection readings were normalized to a standard pressure of 707 KPa to simulate a dual wheel assembly of 10-ton using the linear equation 4.1.

Equation 4.1: { } { }⁄

di is the deflection reading for the sensor located i mm from the centre, dn is the normalized deflection reading for the sensor located i mm from the centre, Li is the load level applied during the test and Lt is the target load level of 707 KPa based on the standard axle of 10-ton.

Structural number has been computed from FWD data. Based on the structural number, the comparative strength of different sections can be assessed. The structural number, sn can be computed from the formula below:

sn=112*〖nd1〗^(-0.5)+47*(nd1-nd5)^(-0.5)-56*(nd1-nd7)^(-0.5)-0.4

Where nd1, nd5 and nd7 are deflections readings at 0,900 and 1500mm geophone offset respectively. The higher the structural number, the higher the strength. From the data the average sn for some roads under this zone are as follows:

A2_Nairobi to Thika – 9.1

A3_Thika – Garissa – Liboi – 4.1

B60_ Machakos – Wote – Makindu – 4.3

B63_Outer Ring- Tala- Masii – 4.3

C467_Emali – Okia – 5.1

C704_Silibwet- Olengeroune – Molo – 2.4




The shape files were generated with the FWD data and overlaid onto the RICS database collected to have a check on the data collection manually and by FWD, the same was found to be within the range.

Average SN is varying between 3.51 (Narok County Roads) to 6.38 (Taita-Taveta) county-wise and it is varying between 3.55 (G class) to 8.37 (S) for road class S to G.

Average structural Number of the paved roads per Road Class and Counties is presented in graphically Figure 4.1 and 4.2 respectively.

4.90 5.35 4.61

6.25

4.72 4.90 5.98

4.45 4.29 3.51

6.38

3.97

0.00

1.00

2.00

3.00

4.00

5.00

6.00

7.00

Ave

rage

Str

uct

ura

l Nu

mb

er


Figure 4.1: County Wise Average Structure Number of Paved Road Obtained From FWD Analysis

5.96 4.60 4.26 3.87 3.92 4.55

3.55

8.37

0.00

1.00

2.00

3.00

4.00

5.00

6.00

7.00

8.00

9.00

A B C D E F G S

Ave

rage

Str

uct

ura

l Nu

mb

er


Figure 4.2: Average Structure Number of Paved Road Obtained From FWD Analysis




4.3 ROUGHNESS DATA COLLECTION AND ANALYSIS INTERMS OF INTERNATIONAL ROUGHNESS INDEX.

Roughness was collected using two different methodologies for paved and Gravel roads.

For Paved Roads Road laser Profiling was carried out using Digital Road surface profiler (DRSP) and along with the roughness data collection visual survey data was also collected.

For Gravel Roads Dynamic Roughness Index Measurement System (DRIMS) was used to collect only the roughness data.

4.3.1 Roughness data for Paved Roads

DRSP has been used to collect Roughness data for the Paved Roads and several analysis were carried out to determine

Pavement Condition Index (PCI) and its rating

Rut Depth in mm

IRI values and Rating

Potholes

Visual Condition Survey Index

Shoulder Rating and Drainage rating

Pavement Condition Index (PCI) and its rating: Kenyan RDM Part V, notes that PCI for flexible pavements may be computed from the following equations:

) )

Where:

Slope Variance (SV) is the mean slope variance of the in the two wheel paths,

RD is the mean wheel path rut depth

C is the percentage of pavement surface with Class 2 or 3 cracking and crazing

P is the percentage of pavement surface patched and pot-holed

A, B, C, and D are coefficients depending on the equipment used for measuring slope variance.

This model for determination of PCI has been simplified further to enable determination of PCI at Network Level Analysis (NLA) and PCI is determined as follows:

Visual Condition Index (VCI) is computed as an index ranging from 0 to 9 and based on three indices namely Potholes, general surfacing condition and Cracking each with range of 0 to 3 rating. W_VCI is weighting for visual condition index which was set as 4.4. IRI is the outer wheel path roughness (m/Km) and W_i is the IRI weighting which is set at 10. RUT is the outer wheel path rut depth




(mm) and W_r is the RUT weighting which is set at 10. The equation used for establishing the PCI is as follows:

The PCI value can range from 0 to 100 with section rated as GOOD having PCI value is ranging from 0 to 25, FAIR rated section with values ranging from 25 to 45 and POOR rated section with PCI value ranging from 45 to 100.

PCI of Road Class S to G is varying between 45 to 81 and county wise between 48 to 80. IRI of Road Class S to G is varying between 3 to 12.3 and County-wise 3.7 to 10.4. Class S Road has 3m/km average IRI where as F class road has average IRI 10.4 m/km.

The Average IRI PCI values and IRI values for the paved roads per road class and county is presented graphically in Figure 4.3 to Figure 4.6.

63 72 66 71

62 71 73

80

56 62 72

62 48

05

10152025303540455055606570758085

PC

I Val

ue

County PCI…

Figure 4.3:County wise Average Pavement Condition Index (PCI) of Paved Roads




69 81

72 64

71 57

49 52 45

52

75

05

10152025303540455055606570758085


PC

I Val

ue

Road Class PCI Value

Figure 4.4: Average Pavement Condition Index (PCI) of Paved Roads

3.7 3.7 4.6 4.2 4.7

6.3

4.2 4.0

10.4

5.3 3.8 4.3

6.7

0.0

2.0

4.0

6.0

8.0

10.0

12.0

Ave

rage

IR

I_m

/Km

County Average IRI

Figure 4.5: County wide Average IRI for Paved Roads in Coastal Zone





Roughness data for Gravel roads in Good and fair conditions were collected using Dynamic Roughness Index Measurement System (DRIMS).

International accepted standards were used to rate the surface as per roughness values obtained. The roughness values for gravel roads ranging from 0 to 10 m/Km shall be rated as GOOD, values ranging from 10.0 to 16.0 m/Km shall be rated as FAIR and values above 16.0 m/Km as POOR.

Analysis has been carried out for all counties and average IRI/Km of the county and per road class is graphically presented in Figure 4.7 and Figure 4.8 respectively:

IRI for gravel road of Class A to G is varying between 3.8 m/km (Class A) to 9.8 m/km (Class G) and county-wise between 5.1 m/km (Tana River) to 11 m/km (Kajiado).

3.8 2.6

4.5 6.2

5.0

7.8 7.8 9.0

12.3

9.1

3.0

0.0

2.0

4.0

6.0

8.0

10.0

12.0

14.0


Ave

rage

IR

I_m

/Km

Road Class

Average IRI

Figure 4.6: Average IRI for Paved Roads in Coastal Zone




• • •

6.8

11.0

8.2 9.1

10.0

7.0

9.3 8.8 7.4

6.4

9.3 10.4

5.1

0.0

2.0

4.0

6.0

8.0

10.0

12.0

Ave

rage

IR

I_m

/Km

County Average…

Figure 4.7: Countywise Average IRI for Gravel Roads for Coastal Zone

7.5

3.8

9.1

7.0

9.1 8.3 9.3 9.5 9.8 9.0

0.0

2.0

4.0

6.0

8.0

10.0

A A_urb B B_urb C C_urb D E F G

Ave

rage

IR

I_m

/Km

Road Class Average IRI_m/Km

Figure 4.8: Average IRI for Gravel Roads in Coastal Zone

5. RICS GEO-DATABASE AND DATA

INTEGRATION



RICS Geo-database and Data Integration 5-1

5. RICS GEO-DATABASE AND DATA INTEGRATION

5.1 INTRODUCTION

The main deliverable of the RICS assignment is an updated geodatabase containing all the roads (routes and segments) in the Coastal Zone, associated road structures, institutions as well as facilities. In principle, these features especially the roads and road structures should be spatially connected in the geodatabase through enforcement of the topology. This chapter presents the general approach applied to realize the RICS geodatase in this study.

The geodatabase provides a structured container for holding multiple datasets i.e. data, reports and any other information collected or used in the study. These are stored in the geodatabase for quick retrieval and analysis. In general, a geodatabase provides a way of organizing data which is better than storing shapefiles in multiple folders. Among the envisaged benefits of the database are:

i. Centralized data management;

ii. Efficient data maintenance and versioning;

iii. Improved data security because access rights/ privileges can be enforced;

iv. Improved data scalability and portability;

v. Support for topological analysis;

vi. Multiuser access, especially where data is accessed on a server.

5.2 RICS GEODATABASE DESIGN

In this section we identify and describe the activities that make-up the database design process. These will then be linked to results obtained in the study in the next section.

5.2.1 Database Design Process

The design of a geodatabase generally progresses in the following phases:

i. Conceptualizing the user’s view of the world – in this phase, the designer essentially looks at the problem to address and identifies the (geographic) features (types) and the set of attributes for each feature necessary to address the problem at hand. This results in a data dictionary.

ii. Choice of feature representation – in this phase, the appropriate representation for the features is identified. Geographic phenomena may be represented as points, lines, polygons, tins, grids etc. The choice of representations is determined by, among other things, the existing expertise, software resources, other existing data and the purpose of data analysis.

iii. Define features and relationships – in this phase feature types are defined, the attributes and the relationships among the features types.

iv. Match features to geospatial database elements – In this phase, the items being described are mapped onto database concepts for structure and




organization as well as ensuring data integrity. This results in a database schema.

v. Populating the database - In this phase data is uploaded to populate the database.

Roughly, one would map the first phase to the conceptual design in the classical database design trajectory. The second and third phases would roughly map on logical design whereas phases four and five would map onto physical design. In this assignment, the geodatabase was developed in ArcGIS environment to be consistent with the Client’s GIS platform.

5.2.2 Data dictionary

A key deliverables of the conceptual design phase of the database development process is the data dictionary. The data dictionary defined the schema for data collected in the RICS survey. It identified the features of interest in the survey, and for each feature, the relevant attributes. In addition, the data type for each attribute was identified and, where possible, the acceptable range of values for the attribute. Intuitively, through the attributes identified, relationships among the features are identified and defined.

Definition of the data dictionary was a collaborative process between the Client and the Consultants. The data dictionary defined for the study is given in Annexure 8.

Data was collected on Roads and road structures i.e. bridges, drifts and culverts. Data on institutions and facilities located along the roads were also collected, mainly to assist in the naming of roads. Other data collected were maintenance problems, railway crossings and river. Details of the features, their attributes and attribute values are elaborated in the Annexure 8.

Figure 5.1 shows a preview of the environment used to create and maintain the data dictionary for the study. It shows, on the left-side, a list of features that were of interest in the study. Attributes of the road feature are listed in the middle of the figure and the on the right is the preview of the dictionary on the data collection equipment. The data dictionary was created on GPS Pathfinder Office and uploaded to the JUNO 3B running TerraSync software for field data collection. GPS Pathfinder Office, JUNO 3B and TerraSync are proprietary mapping products of Trimble.




Figure 5.1: The RICS Data Dictionary in GPS Pathfinder Office and TerraSync User Interfaces

5.2.3 Schema for the Geodatabase

In ArcGIS environment, data is organized in feature classes (layers). Feature classes which are related e.g. those used together, are often organized into Feature Datasets. Data in a feature dataset can be topologically linked.

Figure 5.2 presents the schema for the geodatabase. The figure also shows that relationships between various datasets have been enforced taking into consideration the cardinalities involved between the datasets. For instance , one to many (1:M) relationship has been effected between routes and road segments since one route could be made up of many adjoining segments with differing surface types , condition, drainage conditions ,road width and so on. It is worth noting that this database also accommodates data from the existing RICS database as base line data.

Notably, linear referencing was outside the scope of the assignment and therefore the envisaged geodatabase with linear referenced routes, segments and structures could not be delivered.




Figure 5.2: Schema for the RICS Geodatabase

5.3 RICS DATA DEVELOPMENT

The data collected from the field was primarily roads data, with data on structures, facilities, maintenance problem and other point data being collected with reference to the road and according to the data dictionary. After data was collected, it was taken through a series of processing actions before it could be uploaded into the geodatabase. The exact processing steps used depended on whether the features were line features (road) or point features (e.g. structures).

5.3.1 Line Features (Roads)

Line features in this assignment were mainly roads. Roads data from the field comprised road segments. The segmented roads data was taken through a series of processing steps as follows:

i. Cleaning the data to remove duplicates and other spurious entries;

ii. Editing the data to correct the feature geometry, the attribute values as well as enforce topology;




iii. Assign road numbers to the segments - segments with the same road number will essentially be part of the same route. The road number is the unique identifier for a route. Road numbers were assigned depending on the category of road. For classified roads, assigned road number was as per the gazette road register. For new roads i.e. roads with road reserves of at least 9m which are not captured in the existing database, the roads are assigned a class and numbered in the format NN_New_CC_NO where NN stands for the Class, CC is the County Code and NO is a serial number e.g. G_New_34_1234 identifies a new class G road in County number 34 and the road is sequentially been numbered 1234. The numbering is sequential starting from the most south westerly part in a clockwise direction. Narrow roads are roads with a road reserve of less than 9m that were previously un-documented. The numbering convention adopted for these type of roads was NR_CC_NO where NR denotes narrow roads.

iv. Creating routes from the segments;

v. Assigning road names to the routes – for classified roads, especially classes A, B and C, road names were adopted from the gazetted road register.

vi. For each County, merging with other road data in that County to create the County road network;

vii. Clipping the data to the County Boundary with edge matching being done for roads crossing Counties within the zone

5.3.2 Point Features

Point features were collected by nesting during field data collection of roads. The point features include the road structures, facilities institutions, maintenance problems, rivers. Resulting point data is taken through a series of processing steps before it is uploaded into the database. The processing steps were:

i. Cleaning the data to remove duplicates and other spurious entries;

ii. Editing the data to correct the feature geometry and the attribute values;

iii. Merging the data within the County and across the Zone;

iv. Linking the point features to their photographs.

5.3.3 Layers of Data Generated

Overall, the following layers of data were created and uploaded to populate the RICS Geodatabase:

i. Layer of data defining routes for the roads in the Coastal zone;

ii. Layer of data defining road segments in the zone;

iii. Layer containing FWD data;

iv. Layer containing Roughness data on paved Roads;

v. Layer containing Roughness data on Gravel Roads

vi. Layer containing data on Bridges;




vii. Layer containing data on Pipe Culverts;

viii. Layer containing data on Box Culverts;

ix. Layer containing data on Drifts;

x. Layer containing data on Institutions;

xi. Layer containing data on Facilities;

xii. Layer containing data on Maintenance Problems;

xiii. Layer containing data on Towns;

xiv. Layers containing data on other relevant features.

In addition, layers of data from the existing database were also included into the new database to enable comparison and change analyses.

5.4 POPULATING THE GEODATABASE AND ENFORCING TOPOLOGY

After the database schemas were developed, the cleaned datasets are then loaded. Topological rules are enforced on these datasets to eliminate invalid geometries, hanging geometries and invalid values.

Ideally, linear referencing would then be conducted on the road segments to produce routes and finally locate the drainage structures on these routes. Later these route segments would be linearly referenced on the routes. However, linear referencing was outside the scope of the assignment and therefore the envisaged geodatabase with linear referenced routes, segments and structures could not be delivered. Nonetheless, the routes formed the basis of the road register.

6. DATA VALIDATION



Data Validation 6-1

6. DATA VALIDATION

6.1 INITIATION OF DATA VALIDATION PROCESS

Upon completion of Road Inventory and Condition data collection, the data was cleaned and processed for Road Geometry, Naming and Numbering.

The Consultants prepared and compiled the processed data and provided the Road Agencies with the following for the respective counties under their jurisdiction:

Hard copies of road maps (A0 size) for the county(ies);

Soft copies (in CD) of the road maps and the Road Register(s) for the county(ies). The Road Registers include Road Number, Road Class, Road Name, Length of Road Segment, Road Surface Type, Road Surface Condition and Measured Road Reserve for each road segment;

Validation Form for the county(ies)

The above documents were dispatched to the Road Agencies via courier and the Consultants maintained a follow-up with the Road Agencies to confirm that the documents had been received.

Continuous liaison was maintained with the Road Agencies to expedite the data checking process such that a joint meeting between the Consultants and the Road Agencies to validate the data was convened as soon as was practical.

Validation of data by the Road Agencies mainly focused on:

Completeness of Surveys (any missing Roads were to be identified)

Numbering of Roads

Assignment of Classes to new Roads

Naming of Roads

Length of Roads

Surface types assigned for Roads

Surface Conditions assessed for Roads

Measured Road Reserve widths of Roads

6.2 SCHEDULE OF DATA VALIDATION

A predetermined schedule couldn’t be established due to tight scheduling of the CRO’s and Road Agency officials who were often otherwise engaged in other works. Validation meetings were therefore held as per the availability of Road Agency officials. The progress of Data Validation meetings with Road Agencies is given in Table 6.1.



Data Validation 6-2

Table 6.1: Schedule of Data Validation meetings

S/ No.

REGION / COUNTY ITEM

ROAD AGENCY

KeNHA KURA KeRRA County

Governments

1 NORTH EASTERN

(Garissa)

Documents dispatched 4/Jul/17 29/Jun/17

N/A

Validation Meeting with Road Agency

9/Nov/17 24/Aug/2017

2 LOWER EASTERN (Kitui,

Machakos, Makueni)

Documents dispatched 4/Jul/17 29/Jun/17

Validation Meeting 26/Jul/17 20/Jul/17

3 SOUTH RIFT (Kajiado,

Narok)

Documents dispatched 4/Jul/17 N/A

Validation Meeting 2/Aug/17

4 COAST (Kilifi, Kwale,

Lamu, Mombasa, Taita Taveta, Tana River)

Documents dispatched 4/Jul/17 3/Jul/17


5 NAIROBI (Nairobi) Documents dispatched 27/Jul/17 27/Jul/17

Validation Meeting 24/Aug/17 28/Dec/17

1 GARISSA Documents dispatched

N/A

29/Jun/17 5/Jul/17

Validation Meeting 24/August/17 24/August/17

2 Kajiado Documents dispatched 22/Jun/17 22/Jun/17


3 Kilifi Documents dispatched 29/Jun/17 5/Jul/17




Data Validation 6-3

S/ No.


ROAD AGENCY


Governments

4 Kitui Documents dispatched 29/Jun/17 5/Jul/17


5 Kwale Documents dispatched 29/Jun/17 5/Jul/17


6 Lamu

Documents dispatched 29/Jun/17 5/Jul/17

Validation Meeting No meeting held, validation forms

emailed

No meeting held, validation forms

emailed

7 Machakos Documents dispatched 22/Jun/17 22/Jun/17


8 Makueni Documents dispatched 29/Jun/17 5/Jul/17


9 Mombasa Documents dispatched 3/Jul/17 5/Jul/17


10 Nairobi Documents dispatched 27/Jul/17 27/Jul/17

Validation Meeting 24/Aug/17 29/Dec/17

11 Narok Documents dispatched 22/Jun/17 22/Jun/17


12 Taita Taveta Documents dispatched 30/Jun/17 5/Jul/17



Data Validation 6-4

S/ No.


ROAD AGENCY


Governments


13 Tana River

Documents dispatched 30/Jun/17 5/Jul/17

Validation Meeting No meeting held, validation forms

emailed

No meeting held, validation forms

emailed



Data Validation 6-5

6.3 ORGANOGRAM OF ROAD AGENCIES

Functional Organogram of the Road Agencies presented below in Figure 6.1.

Figure 6.1: Organogram of Road Agencies

MINISTRY OF TRANSPORT, INFRASTRUCTURE, HOUSING AND URBAN DEVELOPMENT (MoTIHUD)

KENYA NATIONAL HIGHWAYS AUTHORITY (KeNHA)

NORTH EASTERN REGION

(HEADQUARTERS GARISSA)

COASTAL ZONE COUNTIES IN REGION:

1. GARISSA

LOWER EASTERN REGION

(HEADQUARTERS MACHAKOS)

COASTAL ZONE COUNTIES IN

REGION:

1. KITUI

2. MACHAKOS

3. MAKUENI

SOUTH RIFT REGION

(HEADQUARTERS NAKURU)


REGION:

1. KAJIADO

2. NAROK

COAST REGION (HEADQUARTERS

MOMBASA)


REGION:

1. KILIFI

2. KWALE

3. LAMU

4. MOMBASA

5. TAITA TAVETA

6. TANA RIVER

NAIROBI REGION (HEADQUARTERS

NAIROBI)


1. NAIROBI

KENYA URBAN ROADS AUTHORITY (KURA)

NORTH EASTERN REGION

(HEADQUARTERS GARISSA)


1. GARISSA

LOWER EASTERN REGION

(HEADQUARTERS MACHAKOS)


REGION:

1. KITUI

2. MACHAKOS

3. MAKUENI

COAST REGION (HEADQUARTERS

MOMBASA)


REGION:

1. KILIFI

2. KWALE

3. LAMU

4. MOMBASA

5. TAITA TAVETA

6. TANA RIVER

NAIROBI REGION (HEADQUARTERS

NAIROBI)


1. NAIROBI

KENYA RURAL ROADS AUTHORITY (KeRRA)

COASTAL ZONE COUNTIES:

1. GARISSA

2. KAJIADO

3. KILIFI

4. KITUI

5. KWALE

6. LAMU

7. MACHAKOS

8. MAKUENI

9. MOMBASA

10. NAIROBI

11. NAROK

12. TAITA TAVETA

13. TANA RIVER

ROADS DEPARTMENT, COUNTY

GOVERNMENTS

COASTAL ZONE COUNTIES:

1. GARISSA

2. KAJIADO

3. KILIFI

4. KITUI

5. KWALE

6. LAMU

7. MACHAKOS

8. MAKUENI

9. MOMBASA

10. NAIROBI

11. NAROK

12. TAITA TAVETA

13. TANA RIVER

KENYA WILDLIFE SERVICE (KWS)

EASTERN CONSERVATION AREA


CONSERVATION AREA:

1. GARISSA

SOUTHERN CONSERVATION AREA


CONSERVATION AREA:

1. KAJIADO

2. MACHAKOS

3. MAKUENI

4. NAIROBI

COAST CONSERVATION AREA


CONSERVATION AREA:

1. KILIFI

2. KWALE

3. LAMU

4. MOMBASA

5. TANA RIVER

TSAVO CONSERVATION AREA


CONSERVATION AREA:

1. KITUI

2. TAITA TAVETA

CENTRAL RIFT CONSERVATION AREA


CONSERVATION AREA:

1. NAROK

* Kenya Urban Roads Authority (KURA) has no roads under its jurisdiction in the counties of Kajiado and Narok



Data Validation 6-6

6.4 KEY POINTS DISCUSSED IN VALIDATION MEETINGS

During each Validation meeting, The Consultants explained that Road Inventory and Condition Surveys (RICS) had been completed in the respective counties, subsequent to which the Consultants had prepared and dispatched to the concerned Road Agency staff and CRO’s the following documents pertaining to the county(ies):

Hard copies of road maps (A0 size) for the county(ies);

Soft copies (in CD) of the road maps and the Road Register(s) for the county(ies);

Validation Form(s) for the county(ies).

The Consultants explained that the purpose of validation is for the stakeholders to ascertain the accuracy and completeness of the collected data in relation to their respective road networks, thereby affording the Road Agencies an opportunity to own the data.

The participants then proceeded to review the submitted documents and the Consultants took note of any comments received from the Road Agency accordingly. The following items were checked for each county and comments recorded in the Validation Form(s):

Completeness of surveys (any missed roads?)

Numbering of roads

Assignment of classes to roads

Naming of roads

Length of roads

Surface types of roads

Surface conditions of roads

Measured road reserve widths

The Consultants clarified any queries raised by Road Agency staff where possible, while undertaking to incorporate any received comments in the final database for the Zone.

Upon completion of Data Validation the CRO’s and Road Agency staffs were requested to sign the validation forms with remarks on the data, which is attached as Appendix 7.

6.5 CONCERNS RAISED BY CRO’S AND ROAD AGENCY STAFF ON DATA COLLECTED AND ACTIONS TAKEN BY CONSULTANTS

A compliance matrix has been developed by the consultant on the concerns raised by CRO’s and Road Agencies and corresponding actions being taken by the consultant to address the same.

6.5.1 County Governments

The Compliance matrix for the concerns raised by County Governments is given in Table 6.2:



Data Validation 6-7

Table 6.2: Compliance matrix - County Governments

S/No. County Comments Received Comments Compliance

1 GARISSA 1. Survey not complete.

2. Naming of number of roads not clear.

3. Some roads lengths surveyed do not capture the real length.

4. More time requested for data interrogation on both surface type and surface condition.

5. Issue of road reserve especially on roads outside shopping centers where there are not well defined boundaries

1. Roads close to Kenya –Somalia border not captured due to high insecurity.

• G5035

• G5270

• Part of G5035

• G5040

• G5039

• G5255

• G5100

2. The agency committed to do a report in a weeks’ time after the meeting with proper naming and share with the consultant but the agency is yet to share the report.

3. Some Roads close to Kenya –Somalia border not fully captured due to high insecurity e.g. Part of G5035

4. The agency committed to do a report in a weeks’ time after the meeting with proper naming and share with the consultant but the agency is yet to share the report.

5. The road reserve survey was determined by existing boundary.



Data Validation 6-8


2 KAJIADO


1. Some roads in Kitengela and Ngong have changed from Earth to Paved (Cabro)

Naming of roads

Some road names misspelt. Corrections issued to Consultants. Place names to be corrected as follows:

1. Change “Olgirra” to “Oloirien”

A few road names to be changed

1. E7029 Change “Rombo-Ntilal Road 1” To “Nalasit Road”

2. G71271 Change “Emboliei Ecd Sch-Rombo Road” To “Nasipa Road”

3. D1708 Change “Mbirikani Road 8” To “Nkama-Mbirikani Road”

4. D1715 Change “Kajiado Street 1” To “Hospital Road”

5. D1714 Change “D1718 Junction-Kajiado Township Primary Road” To “Outering Road”

6. G71275 Change “Oloibor-Soit Nur Sch-Tsavo N. Park Road” To “Oloiborsoit-Intinok Road”

7. F_34_NEW_1775 Change “Kamahendu Road 1” To “Tikoshi Road”

8. F_34_NEW_1779 Change “Kamahendu Road 3” To “Endarai Road”

9. F_34_NEW_2251 Change “Rombo Mission Health Centre- Olerai Road 1” To “Elerai-Olemapin Road”

10. F_34_New_2233 Change “Border Road 1” To “Enchurai Road”

11. F_34_New_2440 Change “Kinyuamai Road” To “Lairumbe Road”

Affected roads identified and surface type corrected accordingly.

Corrected



Data Validation 6-9


12. F_34_New_2499 Change “Entarara Town Road 8” To “Wanchara Road”

3 KILIFI

Completeness of surveys

1. Some roads were said to be missing but these were not pointed out to the Consultant.

2. Some roads where identified to have a missing link

i.e. G-03-NEW 1041

1. Comment difficult to address because missing roads were not pointed out to Consultant.

2. Corrected

3. A request was made to redo the validation maps per sub-county and resubmit by the first week of September 2017.

The request is being considered

4 KITUI Naming of roads


2. Change “Ngooni” to “Nguuni”

3. Change “Kanti” to “Canteen”

4. Change “Chukune” to “Kyukune”

5. Change “Damza” to “Damsa”

6. Change “Kauma” to “Kaumu”

7. Change “Kyango” to Kyaango”

8. Change “Maskarini” to “Maskalini”

9. Change “Ngugi” to “Ngungi”

10. Change “Kungu” to “Ukungu”

11. Change “Stangela” to “St. Angela”

12. Change “Usue” to “Usueni”

13. Change “Kola” to “Kora”

14. Change “Mugusi” to “Mughusi”

15. Change “Mwongoni” to “Miwongoni”

16. Change “Kwa Mumu” to “Kwa Mumo”

17. Change “Kitoone” to “Kitooni”

18. Change “Nzongoni” to “Nthongoni”

19. Change “Kaloleni” to “Kalolini”

Corrected



Data Validation 6-10


Measured Road Reserve Widths

Some road reserve widths incorrectly indicated. Corrections issued to Consultants as follows:

1. B88 – 15m throughout

2. C418 – 15m throughout

3. D1090 – 15m throughout


5. E4126 – 15m throughout

6. E4127 to E4129 – 9m throughout








14. F4066 – 9m throughout

15. G46847 – 9m throughout



18. G46998 to G47001 – 9m throughout









27. G47215 to G47219– 9m throughout








Corrected














44. P146_Kitui – 9m throughout




5 KWALE Naming of roads

1. A few road names to be changed i.e. Change “Boma primary school” to “Bowa Primary school”.


-D1024 – “Banga- Kituu- Matope(A8

The affected roads were identified and the values corrected


2. A few surface types to be changed

Corrected

Surface conditions of road

3. The surface condition of a few roads to be changed

Corrected

Measured road reserve widths

4. The road reserve of a few roads to be changed

Corrected

6 LAMU Completeness of surveys (any missed roads?)

1. Survey not complete

Roads not captured due to high insecurity

7 MACHAKOS


1. Road Reserve widths impossible to ascertain. Indicated widths are as physically measured. Encroachment not considered

As measured

8 MAKUENI 1. Use survey maps to check alignment, road lengths and road reserves

1. Requirement not practical





2. Some towns/ road names misspelt 2. Affected names

corrected

3. Gravel/ Earth road surface condition cannot be “good”

3. Comment ignored – requires change of data dictionary

9 MOMBASA

1. Some roads are missing

2. Soft copy of shape files required

1. Missing roads identified with help of County staff and collected

• NR_01_151

• NR_01_152

• NR_01_153

• NR_01_161

• NR_01_165

• NR_01_166

• NR_01_167

• NR_01_168

• NR_01_169

• NR_01_172

• NR_01_177

• NR_01_192

• NR_01_198

• NR_01_199

• NR_01_201

• NR_01_203

• NR_01_205

• NR_01_215

• NR_01_217

• NR_01_228

• NR_01_229

• NR_01_231

• NR_01_234

• NR_01_366

2. Soft copy of shape files provided with the permission of KRB then meeting held between the





3. Naming of the roads eg k8_Mombasa-bajuni road instead of Faza-Banjun-Aga khan road.

4. Confirmation of road surface.

5. Site visit for confirmation of road conditions.

6. Road reserves

consultant and Philip Manwa (surveyor) on 20th July 17 to go through the data.

3. The consultant corrected road names with help of data provided by the agency and shared final shape file with the agency.

4. the agency raised issues on road surfaces of kazdozdo road,chembani,kwa Bulo,shanzu estate,majaoni,roads in Nyali estate,shelly beach road and Peleleza which after meeting on 20th July ,the surveyor confirmed the surface type had been correctly mapped.

5. Through sampling of various roads mentioned above in a meeting on 20th July, the surveyor agreed the data was representation of the condition on the ground.

6. The consultant informed the agency that the road reserve was determined through existing boundaries.





10 NAIROBI Completeness of survey

Some roads in access denied areas e.g. Estates and institution where missing to be collected.

Roads Collected

11 NAROK Naming of roads

1. Loita Road 1 name to be changed to Junction – Ololunga – Orkinyei

Naming of roads


Change “Simotwet” to “Mogoywet”

Corrected

12 TAITA TAVETA


1. Some County Roads and links missing e.g. NR-06-273 hanging and should connect to B56 and NR-06-260 should connect to D1099.

Missing roads identified with help of County staff and collected

Naming of roads

2. NR-06-271 wrongly names ad Wundanyi health center road.

corrected

13 TANA RIVER

No major comment N/A

6.5.2 Kenya National Highway Authority (KeNHA)

The compliance matrix for the concerns raised by KeNHA (Kenya National Highways Authority) is given in Table 6.3:

Table 6.3: Compliance matrix – KeNHA

S/No. Region County Comments Received Comments Compliance

1 North Eastern

GARISSA 1. Length of the road

2. Road reserve needed review

Part of A3 towards Kenya – Somalia border not collected due to high insecurity.

The consultant informed the agency road reserve measured from field based on defined boundaries on the ground.

2 Lower Eastern

KITUI Surface types of roads

1. A9 – Surface

Corrected





Dressing from Kanyonyo to Kitui Town; Gravel from Kitui Town to Kibwezi

2. B62 – Surface Dressing throughout

3. B64 – Replace Earth sections with Gravel


1. A3 – 60m throughout







Corrected

MACHAKOS


1. B67 – Portion in Machakos (Joska–Lukenya) missing

Section does not exist / not open. Alignment under proposal by KeNHA


1. Suggestion to assign different colours to urban and rural roads of the same class (eg. A and Au) in maps during future

Noted





validation exercises



2. B62 – 1st 25Km asphalt, remainder Surface Dressed

3. B63 – Kamulu-Kangundo Surface Dressed, Kangundo-Mwala Gravel, Mwala-Makutano Surface Dressed

Corrected




3. B62 – 40m throughout (30m in Machakos Town)

4. B63 – 40m throughout (26m in Kangundo Town)

Corrected

MAKUENI Surface types of roads


2. B61 – Surface Dressing for 3Km (from Wote). No asphalt in remaining sections

Corrected


Corrected








3 South Rift

KAJIADO Surface types of roads

1. B18 Road has sections of tarmac/paved. Please make necessary changes.

Corrected

NAROK

4 Coast KILIFI Agency failed to provide comments even after considerable prodding

KWALE

LAMU

MOMBASA

TAITA TAVETA

TANA RIVER

5 Nairobi NAIROBI Completeness of Survey

1. Segments difficult to identify on maps

- Roads were only mapped for visual assessment

Numbering of Roads

1. B33 includes both Eastern and Southern by pass that has not been administrated by KeNHA

2. Road number repetition on segment data

- Policy Issue to be addressed by KRB

- Road segmentation was done as per surface type there for different segments on road route will have same number






1. H4_Nairobi does not bear the new class Au

- Corrected

Road Naming

1. Road name repetition on segment data

- Same issue as road numbering mentioned above

Length of Roads

1. Segment difficult to identify without road chainages

- Chainages data will be provided

Road Surface type

1. A2 Asphalt thought

2. A8 Westlands-JKIA Asphalt thought

3. B19 Asphalt thought

4. B32 Asphalt thought

5. H4_Nairobi Asphalt thought

Corrected

Measured road reserve width

1. H4_Nairobi 60m thought

2. B33 60m thought

3. B19 40m thought

Corrected




6.5.3 Kenya Rural Roads Authority (KeRRA)

The compliance matrix for the concerns raised by KeRRA (Kenya Rural Roads Authority) is given in Table 6.4:

Table 6.4: Compliance matrix – KeRRA


1 GARISSA Completeness of surveys (any missed roads?)

1. C294 is in KERRA Garissa County.

Road was captured

Naming of Roads

1. Naming of C252 and C291.

Road names corrected to Bura-Hulugho and Shell Gulled-Amuma respectively.

Surface Types of Roads

1. Interchanged surface type on C251 from Garissa to Bura section is interchanged Asphalt to gravel.

The changes were effected


1. Issues with road reserve

Road reserve surveyed on defined by existing boundaries

2 KAJIADO

Assignment of classes to Roads

1. Proposal to amend class of selected classified roads

Naming of Roads/ Surface Types of Roads/ Surface Conditions of Roads

1. Not proper/ Wrongly captured

Changing of classes for classified roads is outside Consultants TOR Comments are for KRB to consider

Further clarification to be sought from the Agency on the specifics. A meeting for the same is to be arranged.

3 KILIFI Assignment of classes to Roads



Naming of Roads

1. Amendments recommended for some selected roads

C101- “Ribe- Maereni”

C232- “Mabobani- Mambrui”

C235- “Dzitsoni- Jaribuni- Tezo”

Recommended amendments effected





C236- “Parakumi-Kwandemu-Kaloleni”

4 KITUI Naming of roads

1. Some road segment names have been misplaced (different names popping up for segments of the same road)

Database glitch rectified to correct invalid pop-ups

Length of roads

1. Lengths in segments. Need to be aggregate.

Lengths aggregated in summarized road registers



As measured

5 KWALE


1. A few roads missing

Roads indicated as missing had been collected and were shown to agency officials

6 LAMU Completeness of surveys (any missed roads?)


Missing roads not collected due to high insecurity.

Assignment of classes to Roads



Naming of roads

1. C257 to be renamed to “Witu-Pandanguo-Mkunumbi”

Recommended amendments effected

7 MACHAKOS


4. C454 – Partially KURA, partially KeRRA

Policy issue

Naming of roads

1. C441 – Change name to “Lukenya-Kenol-Kathiani-Kaani”

Corrected







As measured

8 MAKUENI Naming of roads

1. Towns/ Road names misspelt

Affected towns/ roads identified and names corrected

9 MOMBASA

No major comment

N/A

10 NAIROBI Completeness of survey

1. Few roads where missing

- Missing Roads Collected

Road Naming

1. Style of naming was too wide as Utawala Access Road 1- Utawala Access Road 2

- Road names corrected using facilities and institutions where possible.

11 NAROK Naming of roads


20. Change “Simotwet” to “Mogoywet”

21. Change “Enoosane” to “Enoosaen”

Changes to names of some roads recommended

1. C708 Change “Kiptenden - Enengeetia” To “Kiptenden - Olopusur - Enengeetiai”

2. C709 Change “Enkusero - Njoro” To “Enkusero - Ololongoi”

3. C727 Change “Game Sare Road” To “Oyaani - Ogwethi- Game - Lolgorian - Gwitembe”

4. C730 Change “Shartuka- Mara” To “Shartuka- Esoit- Kirindon- Emarti- Mara”





5. C733 Change “Mara - Keekoroki” To “Aitong -Talek - Keekorok”

6. C734 Change “Kirindoni - Kamaget” To “Kabalecho- Emurua Dikirr- Murkan- Kirindoni - Kawai”

7. C735 Change “Ololulunga-Olopito 1” To “B7 Junction-Ololulunga-Nkareta - Kipangas”

8. C736 Change “Nyabitunwa- Enoosane” To “Nyabitunwa- Enoosaen”

9. C739 Change “Ololulunga-Ole Mukenyo” To “Ololulunga- Ole Mekenyo- Kipchoge”

10. C740 Change “Nyanturaga - Njipiship” To “Njipiship- Olmelil”

11. C741 Change “Kilgoris - Kiomiti” To “Kilgoris- Osopuko- Geteri”

12. C742 Change “Motonyoni - Shartuka” To “Shartuka- Romosha”


Surface conditions of roads with a few changes

1. C715 Change “Poor” To “Fair”

2. C725 Change “Poor” To “Fair”

3. C729 Change Earth “Poor” To “Fair”

Recommended changes to road names effected

Corrected

12 TAITA TAVETA

Naming of roads.

1. Some discrepancies noted on road names. E.g. Makatau-Ndii road, Fighini-Mwambirwa-Ndii road.

Corrected


1. Surface conditions of roads – a few discrepancies noted e.g. C275

Recorded as observed and felt during data collection.





should have fair surface condition.

Surface types of roads.

1. Some discrepancies noted e.g. C274 and C275 are earth road.

As observed on the ground.

Measured road reserves.

1. Adjustments needed on some roads reserve e.g. C274 should have a road reserve of 25m while C272 road reserve should be 20m.

Road reserve taken as measured physically on the ground during data collection.

13 TANA RIVER



Rhoka - Bangale

Manono - Ozi

Roads not captured due to insecurity

6.5.4 Kenya Urban Roads Authority (KURA)

The compliance matrix for the concerns raised by KURA (Kenya Urban Roads Authority) is given in Table 6.5:

Table 6.5: Compliance matrix – KURA


1 North Eastern

GARISSA


1. KRB to revise classes of roads

Naming of the roads

1. K3_Garissa from Garissa university road to Idd ground-wamberi-university loop.

2. K2_Garissa from Garissa township road 1 to Fafi road.

Changing of classes for classified roads is outside Consultants TOR –Comments are for KRB to consider.

Corrected





3. K1_Garissa from Tetu primary school road to Sankuri-Tetu-A3 junction road.

Surface Types of Roads

Update surface type as discussed with consultant.

1. K1_Garissa from Earth to gravel.

2. K2_Garissa first section from concrete blocks off approximately 700m to asphalt.

3. K4_Garissa first 700 m is Asphalt.

4. K3_Garissa near Idd ground the road is gravel and road condition varies from good to fair

Corrected

2 Lower Eastern

KITUI Completeness of surveys (any missed roads?)

1. K4_Kitui – Gap in road due to construction works

Collected and corrected

MACHAKOS Completeness of surveys (any missed roads?)

1. K10_Mavoko – Gap in road

2. K4_Mavoko – Gap in road due to swampy area

3. K5_Mavoko – Gap in connection to K4_Mavoko

1. Collected and corrected


3. Short portion collected and corrected. Remainder does not exist

4. Policy issue


6. Uncollected portion does not exist





4. D1267 – Partially KURA, partially County

5. K9_Mavoko – Gap in connection to A8

6. K1_Mavoko – Gap in connection to A8

7. C454 – Partially KURA, partially KeRRA

7. Policy issue

MAKUENI NIL - All approved N/A

3 Coast KILIFI


1. Proposal made to change class of selected roads

Naming of roads

1. Road names to be amended as per schedule provided

Changing of classes for classified roads is outside Consultants TOR –Comments are for KRB to consider

Road names corrected.

KWALE

LAMU

MOMBASA

TAITA TAVETA

TANA RIVER

4 Nairobi NAIROBI Road numbering and naming

1. KURA network not reflected in the data

Measured road reserve width

1. Incorrect road reserve indicated

- KURA network identified and routes defined in collaboration with officers of the Authority

- Value of road reserve given is only indicative and more accurate surveys may be required to obtain correct road reserve

Items listed under “Comments received” refer only to Items on the Validation Form requiring consideration. All other Items on the Validation Form are otherwise approved.

7. CONCLUSIONS AND

WAY FORWARD




April 2018

Conclusions and Way Forward 7-1

7. CONCLUSIONS AND WAY FORWARD

7.1 CONCLUSIONS



Total of 24,091 Drainage structures were also inventoried and assessed for their conditions of which 21,270 structures are found along classified roads; 1,193 along Narrow roads and 1,628 are found along the newly opened/upgraded roads.

It has been evident that the road network in coastal zone surveyed till date has a major portion of earth roads comprising of 65.50% of the total road length, 22.68% of the road network is captured as gravel roads and barely 6.61% paved roads, while tracks constitute only 5.21% of the road network.

On broad overview majority of paved roads are in good to fair condition (42.29% and 37.53% respectively), gravel roads are predominantly in fair to poor condition (56.31% and 32.94% respectively) and Earth roads are mostly in poor condition (72.91%).

Bridges are predominantly in good to fair condition (55.92% and 37.14% respectively) Pipe Culverts are also in good to fair condition (46.23% and 32.25% respectively), Box culverts are mostly in good condition (79.32%) and drifts also fall in good to fair condition (34.17% and 45.93% respectively).

Average SN is varying between 3.51 (Narok County Roads) to 6.38 (Taita –Taveta) county-wise and it is varying between 3.55 (G Class) to 8.37 (S) for road class S to G.

For Paved IRI of Road Class S to G is varying between 3m/km to 12.3m/km and County- wise 3.7m/km to 10.4m/km. Class S Road has 3m/km average IRI where as F class road has average IRI 12.3 m/km

IRI for gravel road of Class A to G is varying between 3.8 m/km (Class A) to 9.8 m/km (Class G) and county-wise between 5.1m/km (Tana River) to 11 m/km (Kajiado).