Land Cover and Land Use change Research in India

M.S.R. Murthy

HyderabadIndia

AutomatedSemi automatedVisual methods

Geospatial &Process MODELS

Information Systems

Multi SENSORSystems

ExtensiveGROUND Database

USER DrivenSystemsNational

RegionalLocal D’base

Different Temporal

scales

Socio Economic Imperatives Ecological Imperatives

FoodSecurity

WaterSecurity

HabitatConservation

Carbon &Hydrology

BiodiversityChange

AtmosphericStudies

I G B PN N R M S

SPOTWIFS

1998/2000

National Database

Phenological Naturalformations

Biome levelClassification

Broad land use1:1 M

IRSAWIFS

2004,’05,’06,’07

National Database

Phenological Naturalformations

Cropping PatternsSurface water,Land use

1:250K

Annual Product

LULC Planning and monitoring Carbon & Trace Gas InventoryBiodiversity Change,DisatersRiver Basin Land cover Dynamics

IRSL IV / CARTO

Case/NeedBased Specific

Database for Hotspots, NUIS

Composition/speices level

Topography

Micro level L Use

>1:25 k

Urban Planning,CDMsAffor/ReforestationBiodiv. Conservation

IRSLISS III

MARCH 09

National DatabaseNR Census (6themes)Phenological &Compositionformations

Detailed Land-use database

1:50 k

Five year product

Integrated LU Mgt.Biodiversity ChangeAffor/Reforestation

•Climatic vegetation types

•climate change - vegetation studies

LAND COVER and LAND USE DATA BASES – 1:1 M

SPOT (1km)

GLC database BIS (www.bisindia.org)

WiFS (180m)

•Biome level delineation

•Climate change - vegetation studies

December 2003January 2004February 2004March 2004December 2003April 2004National LULC mapping using Multitemporal IRS Awifs

IRS P6 Awifs Sensor with 56m spatial resolution, four multispectral bands,800x800km swath facilitate rapid national level monitoring (1:250,000)

National Land use Land cover Map using Multi-temporal AWiFs data

• Monthly AWiFS data used Temporal Signature Discriminant Used

• 18 LULC classes amenable to digital retrieval were delineated

• Intra and Inter annual changes - Cropping, forest cover and surface water

2004-05

2005-06

2006-07

2007-08

-8

-6

-4

-2

0

2

4

6

-80 -60 -40 -20 0 20 40 60

% Change in Rainfall

% C

han

ge in

NS

A Hariyana

West UP

Arunachal

Rayalaseema

North Karnataka

Uttarakhand

Assam & Meghalaya

South Karnataka

East MP & UP

HP

TN & PondicherryKonkan & Goa

Telangana

Kerala

Punjab

Coastal AP

Marathwada

Vidarbha

Gujarat, Daman & Diu

Coastal KarnatakaMadhya Maharashtra

Bihar

Saurashtra, Kutch & Diu Orissa

WestMP

Jharkhand

East Rajasthan

Gangetic West Bengal

J&K

West RajasthanChattisgarhNagaland

India (IN) 1615

United States (US) 64

United Kingdom (GB) 10

Netherlands (NL) 5

Australia (AU) 4

Portugal (PT) 3

Germany (DE) 3

Thailand (TH) 3

Sri Lanka (LK) 3

New Zealand (NZ) 2

China (CN) 2

United Arab Emirates (AE) 2

France (FR) 2

Austria (AT) 1

Sweden (SE) 1

Canada (CA) 1

Iran, Islamic Republic of (IR) 1

Brazil (BR) 1

Argentina (AR) 1

Saudi Arabia (SA) 1

Nepal (NP) 1

Korea, Republic of (KR) 1

Asia/Pacific Region (AP) 1

Turkey (TR) 1

Others 320+

BHOO SAMPADA – LULC WEB SITE

National Forest cover assessment done on biannual basis, since two decades

Forest cover assessed in terms of Very Dense (> 70%), Moderately Dense (40 -70 %) and Open (10-40%) crown density classes using digital approaches

Forest Survey of India carries out the task with the technical know-how transferred in 1986 by Dept.Of Space

State of Forest cover Report (SFR) placed in Indian Parliament

Year

14.12

21.6

10.88

19.52

11.51

19.47

11.71

19.44

11.72

19.47

11.73

19.45

11.17

19.27

11.48

19.39

12.68

20.55

0

5

10

15

20

25

1972-75*

1981-83*

1985-87**

1987-89**

1989-91**

1993-95**

1995-97**

1997-99**

2001-2004

Closed forest coverTotal forest cover

Fore

st a

rea

in

per

cen

t

Year

14.12

21.6

10.88

19.52

11.51

19.47

11.71

19.44

11.72

19.47

11.73

19.45

11.17

19.27

11.48

19.39

12.68

20.55

0

5

10

15

20

25

1972-75*

1981-83*

1985-87**

1987-89**

1989-91**

1993-95**

1995-97**

1997-99**

2001-2004

Closed forest coverTotal forest cover

Fore

st a

rea

in

per

cen

t

Forest Cover of India(State of the Forest Report , 2003)

Moderately dense forest(40 % - 70 %)

Very Dense Forest (>70 %)*

Open Forest(10 % - 40 %)ScrubNonforestWaterbodiesState boundaries

Legend

Based on IRS LISS III data of 2002

*% Crown density in parenthesis

Source : Forest Survey of India

Since 1997-98 cycle mapping carried out on 1:50,000 scale

National Forest Cover Assessment

Vegetation and Land Use Databases – 1: 50 K

Two Season IRS LISS – III used : Hybrid Classification approaches followed

12,500 field plot data of 7500 species database integrated

125 Vegetation types/habitats mapped

54 M ha of natural habitats

12,500 field plot data

Biological rich ness areas delineated using geospatial modelling of disturbance regimes,economic values,ecosystem uniqueness and diversity

Provides baseline for conservation prioritization and monitoring

Complies CBDrequirements

Spatial Data - Vegetation type,Fragmentation,Disturbance and biological Rich ness area

Non Spatial Data – 25,000 species data, Plant and Animal Data

Indian Bioresources Information Net Work

in rasff

4 May 2007

Indian Forest Fire Response and Assessment System

Daily fireAlarm

Forest FireSpread

Forest FireProneness

Burnt Area

EcologicalDamage

MitigationPlanning

Forest fireDecisionsupport system

Pre-Fire

During Fire

Post fire

• Daily Fire Alerts• Burnt area

assessment for National Parks

• National Burnt area assessment

• Ecological Damage Assessment

Land Use and Land Cover Dynamics and Impact of Human Dimension in Indian River Basins

Land use / land cover dynamics for 30years

Identification of biophysical & socioeconomic

drivers affecting Land use cover change

Analysis of drivers and impact of human

dimension

To model LULC dynamics vis a vis human

development and in turn on global climate

Land use / land cover data is prepared;

Secondary layers are integrated;

Analysis of social, economic and climatic

variables are being done; and

Analysis report for the basin area is being

prepared.

Status

BiophysicalDriver

EconomicDriver

SocialDriver

OBJECTIVES

Pilot study areas

Consequences ofLULC change

Impact onbiodiversity

Soil degradation

Global warming

Impact onhuman habitability

Consequences ofLULC change

Impact onbiodiversity

Soil degradation

Global warming

Impact onhuman habitability

Extending Land use / land cover for last 30years;

Reconcilation with NRC LULC – 50K datasets;

Testing of LULC models (CLUE, Cellular Automata,

Geomod etc)

Future Plan

Change proneness Map

Agent Based Change Simulation – Endemic Habitats

Predicted Evergreen (1998)Actual Evergreen (1998)

Predicted Evergreen (2020)Predicted Evergreen (2010)

High

Low

Non forest

Forest

Legend1980

19891995 2000

20502010

Geostatistical ModelImprovement of the model by incorporating parameters like, management status, accessibility, resource utilization pattern andUrbanization / industrializationis in progress

1970

Forest dynamics and predictions

NATCOM on trace gas emissionsL U L C C F Assessment – UNFCC Reporting

• Database for 2004-2008 available• Database of 1984 & 1994 being prepared

LULC Diversity and Changes

Complexities in Stand Characters

Bottom – Top Approaches

1984

1994

2004

2007

LCLUC for 1994-2004 as per IPCC Guidelines being prepared

Multiscale Geospatial Model

Cover type and Change Area

Stand Density, Basal Area

Mean Annual Increment

Biomass Expansion Factors

Stem Density

0

5

10

15

20

25

30

35

40

45

50

0 50 95 140 185 230 275 320 365 410 455 500Sampling Intensity

Ste

ms

Per

Plo

t

Low er Bound Estimate Upper Bound

Basal Area

0

0.5

1

1.5

2

2.5

3

0 50 95 140 185 230 275 320 365 410 455 500Sampling Intensity

Bas

al A

rea

m2

per

plot

Low er Bound Estimate Upper Bound

DENSITY, POOLED TYPES

Sph, Cutoff = 80000, Width = 7000, Nug = 0.8751, Psill distance

SQ

RT(

DE

NS

ITY

)

707

1405

1758

2106

2446

2712

2855 2626

2773

2922

2850

1

0.8

1.0

1.2

1.4

1.6

0 e+00 2 e+04 4 e+04 6 e+04 8 e+0

BASAL AREA, POOLED TYPE

Sph, Cutoff = 40000, width = 4000, nugget = 0.0184, ps distance

Log

10 B

asal

Are

a

273

589

812926

976 1229

398

1460

1

0.015

0.020

0.025

0.030

0.035

0 10000 20000 30000

Forest Stand Complexities

Community Forest Management - CDMsPLANNING MONITORING

INSTITUTIONAL PARTICIPATORY

Site IdentificationRS and GIS Based site identification

Resource assessment

Spatially explicit above ground forest carbon (5x5km) South Western Ghats

Spatially Explicit National Carbon Numbers to

place on web PORTAL – Multi scale System

Dynamic Computation with changes in areas, cover type, standing C pools

All registered users can upload their data

Similar on the lines of IBIN,GBIF

Underground Biomass measurements

Indian National Forest Carbon Accounting System

How do we quantify, understand and predict ?

Bottom - Top

Top - Bottom

Compositional FormationsSpecies Formations

Local/Regional Socio-Ecological settings

Phenological FormationsClimate Systems

Terrain Status

DETECTPREDICT

GlobalEcological

alerts

REACT

Adaptation

Mitigation

Classification of Models based on their intrinsic properties

Levins (1996), Sharp(1990)

Forest Fire69%

Biodiversity 6%

NPP7%

Change Assessment

5%

Ecological Modelling

3%

Forest Inventory

10%

SOUTH AMERICA

15%

AFRICA8%

EUROPE40%

NORTH AMERICA

21%

GLOBAL4%

AUSTRALIA4%ASIA

8%

REGIONAL66%

LOCAL29%

GLOBAL5%

Global trends in forestry studies

Is it an imbalance!

etrieval

nalysis

rocessing

ntegration

elivery

over

otspot

melioration

ative

oods

nergy

Automated

Mechanistic

Multivariate

Predictive

Data Mining

Self learning systems

Information System

SDSS

Mobile

Internet

EOS data

LTSE Data

Long termSocio

Ecological Data

Future Driving Facotrs

FutureEndeavors

High temporal Indian/ Global missions

Rapid retrieval (LULC,Burnt area, NDVI, VCF)

LCLUC regional and National forecasts

Biodiversity Change

Reclamation MODELS

Flux towers

•LIDAR, microwave, hypersepcral

DetectionPrediction

KnowledgeBase

GeospatialProducts

ADAPTATION&

MITIGATION

National Action Planon Climate Change

Energy

Greening

Water

Agriculture

Himalayas

thank you