APPLICATION OF REMOTE SENSING AND GIS - …shodhganga.inflibnet.ac.in/bitstream/10603/27945/9/09_chapter3.pdf · Chapter 3 : Application of Remote Sensing and GIS 29 Many researchers

Chapter 3 : Application of Remote Sensing and GIS

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3.1 INTRODUCTION

Water as natural resources play a crucial role not only for agriculture and industry

but because daily availability of potable drinking water eludes many people in our

country. The scope of optimal utilization of water resources has become bleak and

warrants judicious utilization. The erratic and irregular distribution of monsoon

rainfall usually results in flood or drought situations in different parts of the

country. Therefore, information on the extent and nature of flood plains is

important to protect life and property in flood-affected area. So the knowledge of

potential locations of storage of water in surface and ground water aquifer is

essential for making available sustainable supply of water for domestic,

agriculture and industrial use in water scarcity area. Also information on surface

water bodies and location of potential ground water areas are very important tasks

having high priority in water scarcity areas. Remote sensing with synoptic view

and repetitive coverage of extensive inaccessible areas has a great potential to

provide a wide range of data for water resources development & management

namely for their inventory, forecasting and design. At present, for studying

different components of water resources, the use of remote sensing is at different

stages of operationalization.

The main sources of river pollution are usually point sources originated from

household and industrial discharges as well as diffuse pollution generated by

agricultural and urban runoff. Characterizing pollutants requires extensive

knowledge of the area’s geography and non point sources; therefore the possible

point and diffuse sources of pollution must be identified and located in order to be

assessed.

CHAPTER-3

APPLICATION OF REMOTE SENSING AND GIS


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Remote Sensing (RS) and Geographical Information System (GIS) are the most

advanced tools for the watershed development.

The latest advances in Remote Sensing (RS) techniques provide spatial

information that is normally difficult to obtain. GIS is also capable of

quantification of heterogeneity of a watershed by discretizing it into sub-areas,

each having approximately homogenous characteristics. Thus, integration of RS

and GIS technologies has proven to be an efficient tool and has been successfully

used by various investigators for the watershed development.

Remote sensing and GIS techniques can be used for generating development plans

for the watershed area in consonance with the production potential and limitation

of terrain resources, and can also be used for assessing the impact of these

measures before actual implementation in the field. Holistic integrated planning,

involving remote sensing and GIS has been found to be effective in planning for

regional development based on watershed approach.

With the development of GIS and remote sensing techniques, the growing useful

information on spatial data is provided. Hence the hydrological watershed modes

have been more physically based and distributed to enumerate various interactive

hydrological process considering spatial heterogeneity.

The watershed hydrologic responses that lead to the generation of surface runoff

are governed by the interaction of precipitation with the topographic land use and

soil physical properties of the land surface. Therefore, the use of Geographic

Information System (GIS) is preferred over the traditional techniques such as

quantity surface runoff by storing and analysing the factors responsible for runoff.

The estimation process becomes more efficient, interactive and less cumbersome

when the GIS is based for storing, interpreting and displaying the data required in

CN-based runoff estimation techniques. Remote sensing and GIS is very reliable

technique for the preparation of most of the input data required by the SCS curve

number model.


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Many researchers have used an integrated approach to combine RS and GIS

techniques to elucidate the effects of landuse change on runoff using a simple Soil

Conservation Service (SCS) model. Thus, the integration of RS and GIS

technologies with SCS-CN model has proven to be an efficient tool and has been

successfully used by various investigators for runoff estimation (Tejram Nayak,

Verma M. K. and Hema Bindu S, 2012; BO XIAO, Qing-Hai WANG, Jun

FAN, Feng-Peng HAN and Quan-Hou DAI, 2011; P. Sundar Kumar, Dr. M.

J. Ratna Kanth Babu, Dr. T. V. Praveen and Venkata Kumar, Vagolu, 2010;

Tharapong Phetprayoon, Sunya Sarapirome, Charlie Navanugraha and

Sodchol Wonprasaid, 2009; J. P. Patil, A Sarangi, A. K. Singh and T. Ahmad,

2008).

Use of RS and GIS Technologies with USLE has proven to be an efficient tool

and has been successfully used by various investigators for soil erosion

assessment (Kapil Ghosh, Sunil Kumar De, Shreya Bandyopadhyay,

Sushmita Saha, 2013; Hasan Raja Naqvi, Laishram Mirana Devi, Masood

Ahsan Siddiqui, 2012; Vipul Shide, K. N. Tiwari and Manjushree Singh,

2010; Bahadur, 2009; Ozcan et. al. 2008; Bhattari and Datta, 2007).

The amount of pollution from non-point sources flowing into the stream can be

simulated by using GIS techniques, using rainfall, landuse and soil data. Use of

RS and GIS technologies with AGNPS and other models has proven to be an

efficient tool and has been successfully used by various researchers for the

assessment of non-point source pollution (Xizhi Lv, Xinxiao Yu, Dengxing Fan

and Qingyun Li, 2012; Yong-zhong Feng, Xiao-jun Xie, Xiao-wei Qin, Gai-he

Yang, Yan-chun Cao and Shi-qi Yang, 2011; Pu, Xiang, 2009; Vyavahare,

Nilesh 2008).

Geographic information system and remote sensing are proven to be an efficient

tool for locating water harvesting structures by prioritization of micro-watersheds

through morphometric analysis. The positioning of water harvesting structures

through GIS and RS will save a lot of expenses, labor and analysis, particularly

for the remote areas.


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Various investigators (Swati Uniyal and Peeyush Gupta, 2013; Hasan Raja

Naqvi, Laishram Mirana Devi, Masood Ahsan Siddiqui, 2012; Binay Kumar,

Uday Kumar, 2011; Vipul Shinde, K. N. Tiwari and Manjushree Singh, 2010;

Akram Javed, Mohd Yousuf Khanday, Rizwan Ahmed, 2009) used RS and

GIS techniques with morphometric analysis successfully for prioritization of

watershed.

3.2 SCOPE OF THE CHAPTER

The above studies clearly suggest that the information on land use, hydro

geomorphology, soils and slope can be derived from the satellite data and this

information can be integrated using GIS software for suggesting certain measures.

As mentioned earlier the objective of the present study is to identify the problems

and potential in the watersheds and to recommend the measures for soil and water

conservation, it is decided to use the satellite data of the study area along with

other collateral data and to integrate it using GIS for fulfilling the objectives of

present study.

The chapter deals with identifying the land use/land cover classes by visual

interpretation of geocoded, false colour composite images. Multi-date data is

taken in order to identify and delineate the boundaries of the cropland in Kharif

and Rabi seasons. The interpreted details are checked on the ground to verify the

interpretation. The agricultural land and water bodies are also demarcated.

Generation of thematic maps is also discussed.

3.3 REMOTE SENSING

3.3.1 Remote Sensing Definitions

Remote sensing is the science of acquiring, processing and interpreting

images that record the interaction between electromagnetic energy and

matter.

Remote sensing is the science and art of obtaining information about an

object, area, or phenomenon through the analysis of data acquired by a device


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that is not in contact with the object, area, or phenomenon under

investigation.

Remote sensing is the instrumentation, techniques and methods to observe the

Earth’s surface at a distance and to interpret the images or numerical values

obtained in order to acquire meaningful information of particular objects on

earth.

Common to the three definitions is that data on characteristics of the Earth’s

surface are acquired by a device that is not in contact with the objects being

measured. The result is usually stored as image data (Aerial photographs are also

considered as image data). The characteristics measured by a sensor are the

electromagnetic energy reflected or emitted by the Earth’s surface. This energy

relates to some specific parts of the electromagnetic spectrum: usually visible

light, but it may also be infrared light or radio waves. There is a wide range of

remote sensing sensors. Sensors, linked to a certain platform, are classified

according to their distance from the Earth’s surface: airborne and space borne

sensors. Together, they contribute to aerospace surveying, which is the combined

use of remote sensing and ground-based methods to collect information.

3.3.2 Ground-based and Remote Sensing Methods

In principle, there are two main categories of spatial data acquisition

Ground-based methods such as making field observations, taking in situ

measurements and performing land surveying. Using ground-based methods,

you operate in the real world environment (Fig. 3.1).

Fig. 3.1: Principle of Ground-Based Methods

(Measurements and observations are performed in the real world)


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Remote-sensing methods, which are based on the use of image data acquired

by a sensor such as aerial cameras, scanners or radar. Taking a remote

sensing approach means that information is derived from the image data,

which form a (limited) representation of the real world (Fig. 3.2).

Fig. 3.2: Principle of Remote Sensing Based methods

(Measurement and Analysis are performed on image data)

Fig. 3.3 Relationship between the Chapters of This Textbook and the Remote

Sensing Process

3.3.3 Application of remote sensing

Remote sensing provides image data

Remote sensing provides area covering data

Remote sensing provides surface information

Remote sensing provides multipurpose image data


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3.4 ELECTROMAGNETIC ENERGY AND REMOTE SENSING

3.4.1 Introduction

Remote sensing relies on the measurement of electromagnetic (EM) energy. EM

energy can take several different forms. The most important source of EM energy

at the Earth’s surface is the Sun, which provides us, for example, with (visible)

light, heat (that we can feel) and UV-light, which can be harmful to our skin.

Fig. 3.4: A remote sensing sensor measures reflected or emitted energy. An active

sensor has its own source of energy.

Many sensors used in remote sensing measure reflected sunlight. Some sensors,

however, detect energy emitted by the Earth itself or provide their own energy

(Fig. 3.4). A basic understanding of EM energy, its characteristics and its

interactions is required to understand the principle of the remote sensor. This

knowledge is also needed in order to interpret remote sensing data correctly. For

these reasons, this topic introduces the basic physics of remote sensing.

3.4.2 Energy interaction in the atmosphere

The most important source of energy is the Sun. Before the Sun’s energy reaches

the Earth’s surface, three fundamental interactions in the atmosphere are possible

absorption, transmission and scattering. The energy transmitted is then reflected or

absorbed by the surface material.


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Absorption and transmission

Electromagnetic energy traveling through the atmosphere is partly absorbed by

various molecules. The most efficient absorbers of solar radiation in the

atmosphere are ozone (O3), water vapor (H2O) and carbon dioxide (CO2).

Fig. 3.5: Energy Interactions in the Atmosphere and on the Land

Atmospheric scattering

Atmospheric scattering occurs when the particles or gaseous molecules present in

the atmosphere cause the EM waves to be redirected from their original path. The

amount of scattering depends on several factors including the wavelength of the

radiation, the amount of particles and gases, and the distance the radiation travels

through the atmosphere. For the visible wavelengths, 100% (in case of cloud


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cover) to 5% (in case of a clear atmosphere) of the energy received by the sensor

is directly contributed by the atmosphere. Three types of scattering take place:

Rayleigh scattering, Mie Scattering and Non-selective scattering.

Rayleigh scattering

Rayleigh scattering predominates where electromagnetic radiation interacts with

particles that are smaller than the wavelength of the incoming light.

Fig. 3.6: Rayleigh Scattering is Caused by Particles smaller than the wavelength and is maximal for small wavelengths.

Fig. 3.7: Rayleigh scattering causes us to perceive a blue sky during daytime and a red sky at sunset.

Non-selective scattering

Non-selective scattering occurs when the particle size is much larger than the

radiation wavelength. Typical particles responsible for this effect are water

droplets and larger dust particles.


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Fig. 3.8 : Direct and indirect effects of clouds in optical remote sensing

3.5 SENSORS

Sensor is a device that measures and records electromagnetic energy. Sensors can

be divided into two groups. Passive sensors depend on an external source of

energy, usually the Sun (although sometimes the Earth itself). The group of

passive sensors covers the electromagnetic spectrum in the range from less than 1

picometre (gamma rays) to over 1 meter (micro and radio waves). The oldest and

most common type of passive sensor is the (photographic) camera. Active sensors

have their own source of energy. Measurements by active sensors are more

controlled because they do not depend upon the (varying) illumination conditions.

Active sensors include the laser altimeter (using infrared light) and radar. (Fig.3.9)

gives an overview of the types of the sensors that are introduced in this section.


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Fig. 3.9 : Overview of the sensors that are introduced in this chapter

3.5.1 Passive sensors

Gamma-ray spectrometer

The gamma-ray spectrometer measures the amount of gamma rays emitted by the

upper soil or rock layers due to radioactive decay. The energy measured in

specific wavelength bands provides information on the abundance of (radio

isotopes that relate to) specific minerals. Therefore, the main application is found

in mineral exploration.

Aerial camera

The camera system (lens and film) is mostly found in aircraft for aerial

photography. Low orbiting satellites and NASA Space Shuttle missions also apply

conventional camera techniques. The film types used in the camera enable

electromagnetic energy in the range between 400 nm and 900 nm to be recorded.

Aerial photographs are used in a wide range of applications. The rigid and regular

geometry of aerial photographs in combination with the possibility to acquire

stereo-photography has enabled the development of ‘photogrammetric

procedures’ for obtaining precise 3D coordinates. Although aerial photos are used


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in many applications, principal applications include medium and large scale

(topographic) mapping and cadastral mapping. Today, analogue photos are often

scanned to be stored and processed in digital systems. Various examples of aerial

photos are shown in (Figs. 3.10 (a), (b)).

( a ) ( b)

Fig. 3.10 : Vertical (a) and oblique (b) aerial photo of the ITC building. Photos by Paul Hofstee, 1999.

Video camera

Video cameras are sometimes used to record image data. Most video sensors are

only sensitive to the visible colours, although a few are able to record the near

infrared part of the spectrum

Multispectral scanner

The multispectral scanner is an instrument that mainly measures the reflected

sunlight in the optical domain.

Imaging spectrometer

The principle of the imaging spectrometer is similar to that of the multispectral

scanner, except that spectrometers measure only very narrow (5–10 nm) spectral

bands.


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Thermal scanner

Thermal scanners measure thermal data in the range of 10–14 µm. Wavelengths in

this range are directly related to an objects temperature. Data on cloud, land and

sea surface temperature are extremely useful for weather forecasting.

Radiometer

EM energy with very long wavelengths (1–100 cm) is emitted from the soil and

rocks on, or just below, the Earths surface. The depth from which this energy is

emitted depends on the properties, such as water content, of the specific material.

Radiometers are used to detect this energy.

3.5.2 Active sensors

Laser scanner

Laser scanners are mounted on aircraft and use a laser beam (Infrared light) to

measure the distance from the aircraft to points located on the ground. This

distance measurement is then combined with exact information on the aircraft’s

position to calculate the terrain elevation. Laser scanning is mainly used to

produce detailed, high-resolution, Digital Terrain Models (DTM) for topographic

mapping.(Fig. 3.11)

Fig. 3.11 Digital Terrain Model (5 m grid) of the St.Pietersgroeve (NL).

(Courtesy Survey Department, Rijkswaterstaat)


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Radar altimeter

Radar altimeters are used to measure the topographic profile parallel to the

satellite orbit.

Imaging radar

Radar instruments operate in the 1–100 cm domain. As in multispectral scanning,

different wavelength bands are related to particular characteristics of the Earth’s

surface. The radar backscatter (Fig. 3.12) is influenced by the illuminating signal

(microwave parameters) and the illuminated surface characteristics (orientation,

roughness, di-electric constant/moisture content).

Fig. 3.12 ERS SAR image of a delta in Kalimantan, Indonesia.

(The image allows three different forest types to be distain)

3.6 REMOTE SENSING APPLICATIONS IN WATER

RESOURCES

Space technology in the form of remote sensing can play a useful role in

harnessing country’s available water resources at a time when the task has

assumed greater significance and utmost urgency for deriving quick and lasting

benefits. There are several areas in the field of water resources wherein remote

sensing can find its way for effective applications – particularly in surveying and


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inventorying. It is contemplated that there is ample scope for the application of

remote sensing in the assessment of various components of hydrologic cycle,

quantification of these components in various environs and the fluxes of water

through these environs. In the field of snow hydrology, river morphology,

reservoir dynamics and sedimentation, watershed conservation, command area

planning, flood estimation and forecasting, water quality, environmental

protection, National Water Plans and development of irrigation projects in remote

areas, through fairly reliable, reasonably accurate and incredibly faster data

acquisition, remote sensing concomitant with conventional data would be able to

provide best management practices and facilitate proper monitoring.

3.6.1 Remote Sensing Capabilities in Water Resources

Listed under are the various applications in water resources wherein remote

sensing may substitute or complement or supplement the conventional methods:

3.6.1.1 Hydrologic studies

Rainfall Estimation, forecasting and monitoring.

Evaporation and evapotranspiration studies.

Hydrologic modeling – rainfall – runoff models etc.

Water balance studies.

Runoff forecasting, estimation.

3.6.1.2 Watershed Conservation, Planning and Management

Watershed delineation and characterization.

Quantitative analysis of drainage networks.

Watershed geology, forest and vegetal cover mapping.


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Land use/Land cover survey and mapping.

Soil survey and mapping.

3.6.1.3 Flood and Flood Plain Management

Flood mapping

Monitoring drainage / infiltration characterization

Flood estimation and forecasting / disaster warning system.

Flood mitigation and development of flood plain management strategy.

3.6.1.4 Water Management in Command Areas

Assessment of surface water resources

Reservoir regulation / operation

Mapping of irrigated lands and crop acreages in irrigation projects.

Identification, inventorying and assessment of irrigated crops.

Mapping and Monitoring of saline and alkali soils

Mapping and Monitoring of waterlogged areas and wet lands.

Soil moisture measurements.

Irrigation scheduling of crops (based on crops stress, crop condition, soil

moisture level evapotranspiration etc.)


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3.7 GEOGRAPHIC INFORMATION SYSTEM (GIS)

3.7.1 GIS Overview

Geographic Information System (GIS) is a computer based information system

used to digitally represent and analyze the geographic features present on the

Earth' surface and the events (non-spatial attributes linked to the geography under

study) that are taking place on it. The meaning to represent digitally is to convert

analog (smooth line) into a digital form.

"Every object present on the Earth can be geo-referenced", is the fundamental key

of associating any database to GIS. Here, term 'database' is a collection of

information about things and their relationship to each other and 'geo-referencing'

refers to the location of a layer or coverage in space defined by the co-ordinate

referencing system.

3.7.2 Geographic Information System (GIS) Definitions

GIS is defined as “An automated tool useful for capture, storage, retrieval and

manipulation, display and querying of both spatial and non-spatial data to generate

various planning scenarios for decision making.” So, what is a GIS? In a nutshell,

we can define a geographic information system as a computerized system that

facilitates the phases of data entry, data analysis and data presentation especially

in cases when we are dealing with georeferenced data.

This means that a GIS user will expect support from the system to enter

(georeferenced) data, to analyze it in various ways, and to produce presentations

(maps and other) from the data. We may distinguish three important stages of

working with geographic data:

Data entry: The early stage in which data about the study phenomenon is

collected and prepared to be entered into the system.

Data analysis: The middle stage in which collected data is carefully

reviewed, and, for instance, attempts are made to discover patterns.


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Data presentation: The final stage in which the results of earlier analysis are

presented in an appropriate way.

According to the definition, a GIS always consists of modules for input, storage,

analysis, display and output of spatial data. (Fig. 3.13) shows a diagram of these

modules with arrows indicating the data flow in the system. For a particular GIS,

each of these modules may provide many or only few functions. However, if one

of these functions would be completely missing, the system should not be called a

geographic information system.

An explanation of the various functions of the four components for data input,

storage, analysis, and output can provide a functional description of a GIS. Here,

we only briefly describe them. Beside data input (data capture), storage and

maintenance, analysis and output, geoinformation processes involve also

dissemination, transfer and exchange as well as organizational issues. The latter

define the context and rules according to which geoinformation is acquired and

processed.

Fig. 3.13 Functional Components of a GIS

Data input

The functions for data input are closely related to the disciplines of surveying

engineering, photogrammetry, remote sensing, and the processes of digitizing, i.e.,

the conversion of analogue data into digital representations. Remote sensing, in

Database


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particular, is the field that provides photographs and images as the raw base data

from which to obtain spatial data sets. Additional techniques for obtaining spatial

data are manual digitizing, scanning and sometimes semi-automatic line

following. Today, digital data on various media and on computer networks are

used increasingly. Table 3.1 lists the methods and devices used in the data input

process.

Table 3.1: Spatial Data Input Methods and Devices Used

Data output and visualization

Data output is closely related to the disciplines of cartography, printing and

publishing. Table 3.2 lists different methods and devices used for the output of

spatial data. Cartography and scientific visualization make use of these methods

and devices to produce their products. The importance of digital products (data

sets) is increasing and data dissemination on digital media or on computer

networks becomes extremely important. Both data input and data output, the

Internet has a major share. The World Wide Web plays the role of an easy to use

interface to repositories of large data sets. Aspects of data dissemination, security,

copyright, and pricing require special attention. The design and maintenance of a

spatial information infrastructure deal with these issues.

Method Devices

Manual digitizing Coordinate entry via keyboard

Digitizing tablet with cursor

Mouse cursor on the computer monitor (heads-up digitizing)

Digital photogrammetry

Automatic digitizing Scanner

Semi-Automatic digitizing Line following devices

Input of available digital data Magnetic tape or CD-ROM Via computer network


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Table 3.2 : Data Output and Visualization

Data storage

The representation of spatial data is crucial for any further processing and

understanding of that data. In most of the available processing systems, data are

organized in layers according to different themes or scales. They are stored either

according to thematic categories, like land use, topography and administrative

subdivisions, or according to map scales, representing map series of different

scale. An important underlying need or principle is a representation of the real

world that has to be designed to reflect phenomena and their relationships as close

as possible to what exists in reality.

Method Devices

Hard copy

Printer

Plotter (pen plotter, inkjet printer, thermal transfer printer, electrostatic plotter)

Film writer

Soft copy Computer screen

Output of digital data sets

Magnetic tape

CD-ROM

Computer network


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Table 3.3: Tessellation and Vector Representations Compared

In a spatial database, features are represented with their (geometric and non-

geometric) attributes and relationships. The geometry of features is represented

with (geometric) primitives of the respective dimension. These primitives follow

either the vector or the raster approach.

3.7.3 Other name of GIS

Geo-based Information System

Natural resource Information System

Geo-data System

Spatial Information System

3.7.4 Applications of GIS

Engineering mapping

Automated photogrammetry

Tessellation representation Vector representation

Advantages Advantages

Simple data structure

Simple implementation of overlays

Efficient for image processing

Efficient representation of Topology

Disadvantages Disadvantages

Less compact data structure

Difficult to representation Topology

Complex data structure

Overlay more difficult to implement

Inefficient for image processing


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Tax mapping

Highway mapping

Utility / facility mapping / management

Census mapping, well log data mapping

Land use planning / management

Environment impact studies

Natural resources management- forests, agriculture etc

Routing – Highway, pipelines

Urban & regional planning

3.8 GENERATION OF THEMATIC MAPS

The best known (conventional) models of the real world are maps. Maps have

been used for thousands of years to represent information about the real world.

Their conception and design has developed into a science with a high degree of

sophistication. Maps have proven to be extremely useful for many applications in

various domains.

A disadvantage of maps is that they are restricted to two-dimensional static

representations, and that they always are displayed in a given scale. The map scale

determines the spatial resolution of the graphic feature representation. The smaller

the scale, the less detail a map can show. The accuracy of the base data, on the

other hand, puts limits to the scale in which a map can be sensibly drawn. The

selection of a proper map scale is one of the first and most important steps in map

design.

A map is always a graphic representation at a certain level of detail, which is

determined by the scale. Map sheets have physical boundaries, and features


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spanning two map sheets have to be cut into pieces. Cartography as the science

and art of map making functions as an interpreter translating real world

phenomena (primary data) into correct, clear and understandable representations

for our use. Maps also become a data source for other maps. With the advent of

computer systems, analogue cartography became digital cartography. It is

important to note that whenever we speak about cartography today, we implicitly

assume digital cartography. The use of computers in map making is an integral

part of modern cartography. The role of the map changed accordingly.

Increasingly, maps lose their role as data storage. This role is taken over by

databases. What remains is the visualization function of maps.

Various thematic maps i.e. Base map, Drainage map, Watershed map, Slope map,

Soil map, Land use/land cover etc. are prepared for the present study purpose.

3.9 MATERIALS AND METHODOLOGY

Indian remote sensing satellite LISS IV data of 2010 with a spatial resolution of

5m was used for the study. For baseline mapping, Survey of India (SOI) Topo

Maps in 1:50,000 scale and watershed maps with demarcated treatment areas were

procured. For supervised land use classification, ground truth from homogeneous

areas were collected and used as training sites in digital land use classification.

3.9.1 Grid Base Generation, Toposheet Registration, Mosaicing of scenes & Image

Registration

Watershed wise geographic grid base 5 minutes interval was generated & output

projection was defined in Lambert Conformal Conic (LCC) of ENVI Software,

which is suitable for small area analysis. The purpose is to register the scanned

maps into real world co-ordinate system. For registration of maps with geo-

referenced grid vectors, GCP (Ground Point Control) function of PCI Geomatica

Software was used. Once a registered database with Topo Maps was created the

uncorrected raw satellite images were also registered in reference to the registered

Topo Maps with minimum permissible root mean square (rms) errors (less than

half of a pixel). As a single image does not cover the entire watershed Mosaicing


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was done with the adjoining scenes & then registration was performed. From the

Topo Sheets watershed boundary was digitized.

3.9.2 Land Use / Land Cover Classification

Land use classification was done following maximum likelihood classifier, which

classifies each pixel based on their probability of being in a class. Training sites

with known land use classes were interactively applied for training the classifier,

which subsequently classifies the whole image along with the training sets for a

classified land use output. Broadly the lands are classified into agriculture lands,

watersheds and water body & their subclasses.

3.9.3 Study Area Maps

The entire study area is covered in Survey of India (SOI) topographic map on

1:50,000 scale. The study area is delineated using watershed concept. Watershed

area is the area starting from highest point of the area (ridge line) to the outlet of

nallah or the natural stream. The watershed concept is used since watershed is a

basic manageable hydrologic unit for wholesome development, as mentioned

earlier. The watershed has a total area of 128654.55 ha. The map was then

superimposed on satellite data products and matched with the features present on

the satellite imagery for the interpretation purpose. This map is used as a base map

throughout the study. Maps of the study area are shown in (Fig. 3.14 & 3.15).

3.9.4 Drainage, Sub-watersheds and Micro-watersheds Maps

Drainage map of the study area has been delineated using satellite imagery. The

drainage map has been later used to delineate sub-watersheds boundaries. The

same concept was used while delineated micro-watersheds boundaries. The sub-

watershed is further classified as a type mini-watershed, micro-watershed etc.

Drainage map is drawn from the satellite imagery of 1:25,000 scale. The sub-

watershed and micro-watershed boundaries are delineated using drainage map.

(Fig. 3.16 to 3.18)


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3.9.5 Slope Map

In the present study slope map is prepared using SOI toposheets at scale of

1:25,000. Slopes are classified on the basis of the guide lines mentioned in

Integrated Mission for Sustainable Development (MSD) document. The study area

shows different categories of slopes ranging from 0-1%, 1-3%, 3-5%, 5-10%, 10-

15% and 15-35%. (Fig. 3.19)

3.9.6 Soil Map and Hydrologic Soil Group Maps:

Soil map prepared by the National Bureau of Soil Survey and Land Use Planning

(NBSS & LUS) is used for the study. The soil units on the soil map are the

associations of sub-groups. In study area two sub-group associations are available.

(Fig. 3.20 & 3.21)

3.9.7 Land Use / Land Cover Map:

The land use / land cover maps (Fig. 3.22 & 3.23) are generated through visual

interpretation of three season satellite data (Kharif, Rabi and Summer). The land

use map shows the spatial extent of agricultural land including cropped area

during Kharif and Rabi season, fallow land, forest plantations, various categories

of watersheds, habitations, water-bodies etc.

3.10 CLOSURE

The chapter presents the fundamental facts of Remote Sensing and GIS

applications in water resources management which have been utilized to generate

various thematic maps of the study area. The delineation of the drainage map is

made possible using satellite imagery. Grid base generation, Image registration

and preparation of Base map, Drainage map, Watershed map, Slope map, Soil

map, Land use / Land cover maps have been prepared for the present study area.


52

Fig. 3.14 : SOI Toposheets Map of Study Area


53

Fig. 3.15 : Satellite Image Map of the Study Area


54

Fig. 3.16 Drainage Map of the Study Area


55

Fig. 3.17 Sub-watersheds Map of the Study Area


56

Fig. 3.18 Micro-watersheds & Sub-watersheds Map of the Study Area


57

Fig. 3.19 Slope Map of the Study Area


58

Fig. 3.20 Soil Map of the Study Area


59

Fig. 3.21 Hydrologic Soil Group Map of the Study Area


60

Fig. 3.22 Landuse Map of the Study Area


61

Fig. 3.23 Soil-Landuse Map of the Study Area

• • •

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