Land use Land cover Change Detection

Farid Khah
1.Vi|aya Lakshmi
Land use Iand cover change
deIecIion
Lahd use ahd lahd cover chahge has become a cehIral compohehI ih
currehI sIraIegies !or mahagihg haIural resources ahd mohiIorihg
ehvirohmehIal chahges. Urbah expahsioh has broughI serious losses o!
agriculIure lahd, vegeIaIioh lahd ahd waIer bodies. Urbah sprawl is
respohsible !or a varieIy o! urbah ehvirohmehIal issues like decreased air
qualiIy, ihcreased ruho!! ahd subsequehI !loodihg, ihcreased local
IemperaIure, deIerioraIioh o! waIer qualiIy, eIc. lh Ihis work we have
Iakeh Rahgareddy DisIricI, GhaIkesar Mahdal as case Io sIudy Ihe urbah
expahsioh ahd lahd cover chahge IhaI Iook place ih a spah o! 05 years
!rom 2006 Io 2011. RemoIe sehsihg meIhodology is adopIed Io sIudy Ihe
geographical lahd use chahges occurred durihg Ihe sIudy period. SaIelliIe
lmagery- lRS1D, LlSS-lll+PAN FUSED o! Iwo di!!erehI year are Iakeh ihIo
cohsideraIioh. A!Ier image pre-processihg, uh-supervised classi!icaIioh has
beeh per!ormed Io classi!y Ihe images ih Io di!!erehI lahd use caIegories.
Classi!icaIioh accuracy is also esIimaIed usihg Ihe !ield khowledge obIaihed
!rom !ield surveys. lh!ormaIioh oh urbah growIh, lahd use ahd lahd cover
chahge sIudy is very use!ul Io local goverhmehI ahd urbah plah
Farid Khan
Farid Khah,secured M.1ech ih EhvirohmehIal MahagemehI !rom
Jawaharlal Nehru 1echhological UhiversiIy Hyderabad.He has also dohe
MasIers ih PlahI Sciehces !rom Hyderabad CehIral UhiversiIy.PresehIly he is
servihg Ahurag Group o! ihsIiIuIiohs,GhaIkesar as AssisIahI Pro!essor ih
DepI. O! Chemical.ParIicipaIed ih haIiohal ahd ihIerhaIiohal coh!erehces.
978-3-8473-3038-7
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Farid Khan
1.Vijaya Lakshmi
Land use Iand cover change deIecIion
Farid Khan
1.Vijaya Lakshmi
Land use Iand cover change deIecIion
LAP LAMßFß1 Academic PubIishing
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LAP LAM8ER1 Academic Publishihg
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Hyderabad,lhdia,2012
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Alle RechIe vorbehalIeh. / All righIs reserved. Saarbrückeh 2013
1
CONTENTS PAGE NO
________________________________________________________________________
CHAPTER-I- INTRODUCTION 06 - 24
1.1 GENERAL 6
1.2 STUDY OBJECTIVES 9
1.3 STUDY AREA DESCRIPTION 9
1.3.1 Rivers 12
1.3.2 Forest and fauna 13
1.3.3 Climate 14
1.3.4 Rain-Fall 14
1.3.5 Temperature 14
1.3.6 Humidity 15
1.3.7 Winds 15
1.3.8 Special weather phenomena 15
1.3.9 Soils: 16
1.3.10 Minerals 16
1.3.11. Transport and communication 17
1.3.11.1 The Jawaharlal Nehru Inner Ring Road 17
1.3.11.2 The Jawaharlal Nehru Outer Ring Road: 18
1.3.12 Animal Husbandry 18
1.3.13 Cropping Pattern 19
1.3.14 Irrigation 19
1.3.15 Health & Medical Facilities: 19
1.3.16 Industries 20
1.3.16.1 Special Economic Zones 20
1.4 SIGNIFICANCE OF THE STUDY 21
1.5. JUSTIFICATION FOR THE STUDY 21
CHAPTER-II REVIEWOF LITERATURE 25-57
2.1 GENERAL 25
2.2 THE PURPOSE FOR LAND USE CHANGE 29
2.3 DEFINING LAND, LAND COVER, LAND USE, LAND COVER
CHANGE AND LAND USE CHANGE 30
2
2.4 LAND USE AND LAND COVER 32
2.5 LAND USE CHANGE: ENVIRONMENTAL AND
SOCIO-ECONOMIC IMPACTS 35
2.6 LAND USE AND LAND COVER CLASSIFICATION SYSTEMS 41
2.7 CASE STUDIES 48
CHAPTER-III MATERIALS AND METHDOLOGY 58-85
3.1 GENERAL 58
3.1.1 Basic Concepts of Land Use 59
3.1.2 Objectives of Classification 59
3.2 LAND USE / LAND COVER CLASSIFICATION 60
3.2.1 Objectives of Land Use / Land Cover Map 61
3.2.2 Methodology For Land Use/Land Cover Mapping 63
3.3 PREPARATION OF SPATIAL DATA 67
3.3.1 Acquisition and Processing of Topomaps and Satellite Data 67
3.3.2 Satellite Data Processing 68
3.3.3 Digital Image Enhancement of LISS III data 68
3.3.4 Image Interpretation 72
3.3.5 Elements of Image Characteristics 72
3.3.6 visual image Interpretation 72
3.4 GENERATION OF THEMATIC LAYERS 77
3.4.1 Base Map 78
3.4.2 Drainage Map 79
3.4.3 Significance of drainage analysis 80
3.4.4 Transportation map 80
3.4.5 Slope map 81
3.4.6 Land Use / Land Cover Map 83
3.4.6.1 Basic Concepts of Land Use 84
3.4.6.2 Objectives of Land Use / Land Cover Map 84
3.4.6.3 Application of Remote sensing techniques for Lu/Lc 85
3.4.6.4 Methodology for land use/land cover mapping 85
CHAPTER-IV RESULTS AND DISCUSSION 86-104
4.1 GENERAL 86
3
4.2 CHANGE DETECTION RESULT AND ANALYSIS 93
4.3 GHATKESAR MANDAL LU/LC OF2006 ANALYSIS 100
4.4 GHATKESAR MANDAL LU/LC OF 2011: ANALYSIS 101
4.5 CHANGE DETECTION ANALYSIS (2006-2011) 102
CHAPTER ±V CONCLUSION AND RECOMMENDATION 105-108
5.1 CONCLUSION 105
5.2 RECOMMENDATION 107
REFERENCES 109-110
4
LIST OF TABLES
1.1 List of villages in Ghatkesar Mandal 10
1.2 Data from MRO 22
3.1 NRSC Land Use / Land Cover Classification System 61
3.2 Details of LISS III of IRS-1D 65
3.3 Slope categories 82
4.1 Overall change detection (2006-2011) 93
4.2 Land Use Land cover of Ghatkesar Mandal in Hectares - 2006 95
4.3 Land Use Land cover of Ghatkesar Mandal in Percentage ± 2006 96
4 .4 Land Use Land cover of Ghatkesar Mandal in Hectares - 2011 97
4.5 Land Use Land cover of Ghatkesar Mandal in Percentage - 2011 98
4.6 Change Detection (2006-2011) comparison 99
5
LIST OF FIGURES
3.1 flow chart of methodology 66
3.2 satellite imagery 2006 70
3.3 satellite imagery 2011 71
4.1 Base map 87
4.2 Drainage map 88
4.3 Transportation map 89
4.4 Slope map 90
4.5 LU/LC 2006 91
4.6 LU/LC 2011 92
4.7 Pie chart ±Change detection (2006-2011) 94

6
CHAPTER-I
INTRODUCTION
1.1 GENERAL
Studies have shown that there remains only few landscapes on the Earth that are
still in their natural state. Due to anthropogenic activities, the Earth surface is
being signiIicantly altered in some manner and man`s presence on the Earth and
his use of land has had a profound effect upon the natural environment thus
resulting into an observable pattern in the land use/land cover over time.
Definition of terms:
a) Land use: The term land use relates to the human activity or economic
function associated with a specific piece of land.
b) Land cover: The term land cover relates to the type of feature present on the
surface of the earth.
c) Change detection: involves the use of multitemporal data sets to
discriminate areas of land cover change between dates of imaging.
Land use reIers to 'man`s activities and various uses, which are carried
on land (such as agriculture, settlements, industry etc)¨. Land cover reIers to the
material present e.g. vegetation, water bodies, rocks/soils and other resulting
from land transformations. Although land use is generally inferred based on the
cover, yet both the terms land use and land cover being closely related are
interchangeable. For example buildings/ settlement is cover but if we include
whether it is being used for residence or industrial activity, it shows the land use
component. Land use/cover Change detection is very essential for better
understanding of landscape dynamic during a known period of time having
sustainable management. Land use/cover changes is a dynamic, widespread and
7
accelerating process, mainly driven by natural phenomena and anthropogenic
activities, which in turn drives changes that would impact natural ecosystem.
Change detection is one of the landscape ecological aims. Preparing
landscape Characteristics maps can help to change detection. Understanding
landscape patterns, changes and interactions between human activities and
natural phenomenon are essential for proper land management and decision
improvement. Land use refers to man`s activities and the varied uses which are
Carried on over land and land cover refers to natural vegetation, water bodies,
rock/soil, artificial Cover and others noticed on the land (NRSA, 1989). Land
Cover, defined as the assemblage of Biotic and biotic components on the earth`s
surface is one of the most crucial properties of the Earth system. Land cover is
that which covers the surface of the earth and land use describes how the land
cover is modified. Land cover includes: water, snow, grassland, forest, and bare
Soil. Land Use includes agricultural land, built up land, recreation area, wildlife
management area etc.
The Land cover reIlects the biophysical state oI the earth`s surIace and
immediate subsurface, thus embracing the soil material, vegetation, and water.
Land use refers to man's activities on land which are directly related to the land.
Land use and land cover are dynamic. Changes may involve the nature or
intensity of change but may also include spatial (forest abatement at village
level, or for a large scale agro industrial plant), and time aspects. Land use/ Land
cover changes also involve the modification, either direct or indirect, of natural
habitats and their impact on the ecology of the area. The land use/land cover
pattern of a region is an outcome of natural and socio economic factors and
their utilization by man in time and space. Land is becoming a scarce resource
due to immense agricultural and demographic pressure. Hence, information on
land use / land cover and possibilities for their optimal use is essential for the
8
selection, planning and implementation of land use schemes to meet the
increasing demands for basic human needs and welfare. This information also
assists in monitoring the dynamics of land use resulting out of changing
demands of increasing population.
Land use and land cover change has become a central component in
current strategies for managing natural resources and monitoring environmental
changes. The advancement in the concept of vegetation mapping has greatly
increased research on land use land cover change thus providing an accurate
evaluation oI the spread and health oI the world`s Iorest, grassland, and
agricultural resources has become an important priority. Viewing the Earth from
space is now crucial to the understanding oI the inIluence oI man`s activities on
his natural resource base over time. In situations of rapid and often unrecorded
land use change, observations of the earth from space provide objective
information of human utilization of the landscape. Over the past years, data
Irom Earth sensing satellites has become vital in mapping the Earth`s Ieatures
and infrastructures, managing natural resources and studying environmental
change.
Remote Sensing (RS) and Geographic Information System (GIS) are now
providing new tools for advanced ecosystem management. The collection of
remotely sensed data facilitates the synoptic analyses of Earth - system
function, patterning, and change at local, regional and global scales over time;
such data also provide an important link between intensive, localized ecological
research and regional, national and international conservation and management
of biological diversity (Wilkie and Finn, 1996).
Therefore, attempt will be made in this study to map out the status of land
use land cover of Hyderabad District between 2006 and 2011 with a view to
detect the changes that has taken place in this status particularly in the built-up
land so as to predict possible changes that might take place in this status in
10
coordinates ranging between 17
0
27´14' N and 78
0
41´11' E. It has an average
elevation of 469 meters (1541 feet)
Boundaries:
The District is bounded on the North by Medak District, East by Nalgonda
District, South by Mahaboobnagar District and West by Gulbarga District &
North West of Bidar District of Karnataka State. Ranga reddy district covers an
area of 7564.88 Sq. Kms. Ghatkesar Mandal covers a geographical area of
16689 Hectares. There are 21 villages and panchayats in Ghatkesar mandal.
Table 1.1 List of villages in Ghatkesar Mandal
S.No VILLAGE NAME TOTAL AREA
(Ha)
1 ANKUSHAPUR
559.0815
2 ANNOJIGUDA
862.3206
3 AUSHAPUR
388.353
4 BANKNALGUDA
909.5505
5 CHENGICHERLA
890.0244
6 CHERRLAPALLI
728.4749
7 EDULABAD
1510.355
8 GHATKESAR
787.0532
9 GODAMKUNTA
521.1975
10 GONAPURAM
932.4144
11 HAJJALGUDA
602.6398
12 KONDAPURAM
617.493
13 KORREMULA
564.422
14 MADHARAM
798.9024
15 MARPALLIGUDA
1237.156
16 MEDIPALLY
1161.221
11
17 NARAPALLY
582.613
18 NEMAGMALA
982.9821
19 POCHARAM
625.0031
20 RAMPALLY
694.7631
21 YEMNAPET
732.9809
Total
16689
History:
Ranga Reddy District is at the cross roads of India geographically, historically
and has been the meeting ground for the fusion of various civilizations,
religions, races, cultures, languages and traditions with the twin cities of
Hyderabad and Secunderabad as its core. This District including present
Hyderabad Urban District was formerly known as Atrafe-Balda District and was
a part of the Gulshanabad, Medak Division (Subah). In 1931-34 Baghat taluk
from Atraf-e-Balda District. was made a separate Baghat District under the
Commissioner (Subedar) of Medak Division. After police Action in 1948. Atraf-
a-Balda and Baghat District were merged to from the Hyderabad District. Later
in 1978, it was split into Hyderabad Urban District and Hyderabad Rural District
or Ranga Reddy District
Administrative Divisions:
Prior to 25-5-1985, the District was administered with 3 Revenue Divisions and
11 taluks . These Taluks had been further sub-divided into 42 Fikras, Each of
which in turn consists of a Number of Villages. However 11 erstwhile Taluks
were delimited into 10 Panchayat Samithis, almost co-terminus with the taluks
except for a few minor changes in respect of Medchal, Hayathnagar,
Ibrahimpatnam, Maheshwaram and Rajendranagar Taluks. Ghatkesar Mandal
12
has separated from the erstwhile Taluka of Hayathnagar Mandal in the year
1985.It is located on NH-202, Hyderabad to Warangal road at a distance of 25
Kms from Hyderabad.
Population:
As per 2011 Census, Ghatkesar Mandal has total population of 175001 with
90512 males and 84489 females. The number of households as per 2011 Census
is 41406.
1.3.1 RIVERS
The District can be divided into three broad basins. A major part (about 65
percent) of the District is covered by the Musi River Basin Which rises in
Ananthagiri Hills. It flows from West to East, pass through Hyderabad city and
flows towards Nalgonda District within the limits of which it joins the Krishna
River near Wadapalli (Wazirabad) Use of water for irrigation purposes from
Musi has however, been banned because of the rights created for Hyderabad
City water supply in the shape of Osman Sagar and Himayath Sagar for drinking
water and irrigation rights to Musi projects in Nalgonda District. A reservoir
called Osmansagar across the Musi and another called Himayathsagar across the
Eisa River. a tributary of the Musi are situated at a distance of 19.31 and 9.66
Kms. respectively from Hyderabad. The next largest basin in the District is the
Kagna Basin, a tributary of Bhima River and all new irrigation projects are
proposed in this basin. There is good potential in this which can irrigate large
areas. This potential is not, however, fully exploited. The third basin in the
District is the Manjira basin, which is part of the Godavari basin where the area
under irrigation is very limited.
Waterbodies like Pirzadiguda chervu,Nalla Cheruvu,Rampalli cheuvu,rayapet
cheruvu,Adilabad cheruvu and Erimuli vagu comes under study area of
Ghatkesar Mandal.
13
1.3.2 FOREST AND FAUNA
Forests:
The District cannot boast of any important timber yielding forests. This is
because of the low rainfall and inhospitable soil conditions. The inferior type of
forests (from economic point of view) yield only thorn, fuel and small timber
which the soil can sustain. In the Eastern portion of the District the forests are
mostly restricted to isolated hills while in the western portion, they are confined
to the slopes of the hillocks and plateau. The Forest area of the District forms
about 7.63% of the total geographical area. The situation of the state Capital in
the midst of the District and the high density of population have great bearing on
the development of these forests in the District. The forests have therefore,
receded and generally restricted to hills and slopes where in plough cannot work
easily. The total forest area of Ghatkesar Mandal is 905 Ha.
Fauna:
It is on record that, in 1900s the District with its low shrubby jungles was the
home of leopards, bears, hyena`s and occasionally tigers while in the more
opened plains the antelope were in plenty. The game reserves for the ruling
family in the erst-while Hyderabad State and were stocked with them for the
exclusive enjoyment of the nobles.Now the forests have receded into narrow
pockets and so also the game. Blackbuck,Chital or Spotted deer and Samber can
still be seen in Rasanam (Rasanam), Dharur (Gingurthi) Tattepalli, Nagulpalle
and Thirumalapur (Thirmapur), Gokafeasalwar (Rangampally) Naskal Forest
blocks, Wildboar is found all over the forests. Jackal and fox are common even
now in the open. So also Peacock, our National bird and jungle fowl are seen in
Ananthagiri block. Patridges and wild pigeons are common, In the cold season,
wild duck, geese, teal and snipe can be seen in the small and large tanks of the
District.
14
List of Reserved forest (RF) found in study area are Narapally RF, Chengicherla
RF, Edulabad RF,Medipally RF.
1.3.3 CLIMATE:
The Climate of the District is characterized by a hot summer and is generally dry
except during the South west monsoon season. The year may be divided into
four seasons. March to May is the summer season, June to September constitutes
the South West monsoon season, October to December from the North East
monsoon season and January to February is the winter season.
The mean maximum temperature of Ranga reddy district was found to be 40.9
0
C
in month of April and the mean minimum temperature was found to be 15.6
0
C in
the month of January.
1.3.4 RAIN-FALL:
The District has a normal Rainfall of 781.0 MM and actual rainfall of 768.7 MM
in 2009-2010.The Ghatkesar Mandal received normal Rainfall of 748.4 MM and
actual rainfall of 842.6 MM showing 13% of variation.
1.3.5 TEMPERATURE:
The records at the Meteorological observatory station located in Hyderabad at
Begumpet. It is representative of the meteorological conditions prevailing in the
District. The mean maximum temperature begins to raise from the middle of
February and reaches a maximum of about 30
0
C in May. With the onset of the
south-West monsoon into the District early in June, there is appreciable drop in
temperatures and the weather becomes more pleasant. In the beginning of
November, the decrease in both the day and night temperature is rapid.
December is the coldest month with the mean daily maximum temperature at
28.6
0
C( 83.8
0
F) and the mean daily minimum Temperature at 13.6
0
C(56.5
0
F).
15
F The highest maximum temperature recorded at Begumpet was 44.4
0
C
(111.9
0
F) on the 28th May, 1985. F The lowest minimum was 6.1
0
C (43.0
0
F) on
the 8th January, 1946. Ghatkesar experiences the average high temperature of
39
0
C and average low temperature of 15
0
C.
1.3.6 HUMIDITY:
During the South-West monsoon season the relative humilities are generally
high, ranging between 70 and 80 percent on the average. Humidity decreases
from the post-monsoon season onwards. The driest part of the year is the
summer season when the humidity is generally between 30 and 35 percent in the
afternoon.
1.3.7 WINDS:
Winds are generally light to moderate with some increase in force during May
and South West monsoon season. During the post-monsoon season winds are
light and variable in direction in the mornings and mostly North easterly in the
afternoons. During the later half of the cold season and in March & April
morning winds continue to be light and variable in direction, while the after-
noon winds are being mostly easterly to South-Westerly. Winds from Westerly
direction begin to blow from May and in the south West monsoon season winds
are mainly from Western to North Westerly direction.
1.3.8 SPECIAL WEATHER PHENOMENA
Storms and depressions which originate in the Bay of Bengal during September
and the post-monsoon months move in Westerly and North Westerly direction
across the peninsula. Some of these depressions effect the weather over the
District causing widespread to heavy rain and gustly winds. Thunder storms
occur during summer season and towards the end of the South West monsoon
and early part of the post-monsoon seasons.
16
1.3.9 SOILS:
Red soils predominate in the District followed by Black Cotton soils. The
Mandals Where more than 50% of the villages have Red-Chelka soils as the
predominate soils are Medchal. Shamirpet, Qutubllapur, Keesara, Hayathnagar,
Saroornagar, Uppal, Ghatkesar, Rajendranagar, Pargi, Doma, Shamshabad,
Serilingampally, Malkajgiri, Balanagar, Kulkacherla and Gandeed. Dubba soils
are largely found in ibrahimpatnam, Manchal, Yacharam, Maheshwaram and
Kandukur mandals besides Red Chelka soils. The mandals where the soils are
pre dominently black are Chevella, Shahbad, Vikarabad, Newabpet, Dharur,
Pudur, Tandur, Peddemul, Yalal, Basheerbad, Marpally, Mominpet and
Bantararm.
1.3.10 MINERALS:
In this District, quartz and felspar are the principal minerals. The extensively
exploitedquartz veins are in the Mandals of Medchal, Maheshwaram,
Rajendranagar, Malkajgiri and Pargi and the Felspar, the 2nd principal Mineral
is also available in the mandals of Medchal, Hayathnagar, Maheshwaram,
Rajendranagar and Malkajgiri around the District Head quarters. Puller earth is
also available in Chevella, Vikarabad and Tandur Mandals.Lime Stone is
available mostly in Tandur and Marpally Mandals. In Tandur Mandal, quarries
of Lime Stone are extensively developed and the lime is sold locally. Lime
Kanker is also available in the villages of Ibrahimpatnam Mandal and it is used
as Lime Mortar for building purposes. Clays of different type are also available
in Tandur area and these are presently being used in the ceramic Industry.
Major minerals like Amethyst,Quartz and minor minerals like Building stone
and Brick Earth are found in study area of Ghatkesar.
17
1.3.11 TRANSPORT AND COMMUNICATION:
Andhra Pradesh has national highways of 4,537 Kms in length. The position of
Ranga reddy District presents a comparatively better picture in road network.
The National High-ways passing through the District and other major roads
maintained by different agencies i.e. under state highway 260 Kms, Major
District roads 1160 Kms, and Panchayathi Raj 4370 Kms. account for 5790
KMs. of total road length. The District Head-quarters. i.e., Hyderabad is
connected by road with all mandals while 11 Mandals. viz., Malkajgiri,
Ghatkesar, Medchal, Serinligampally Shamshabad, Shankarpally, Dharur,
Vikarabad, Marpally, Basheerbad and Tandur are connected by rail also. The
District Head-quarters i.e., Hyderabad is connected by road with all mandals
while 11 Mandals, viz., Malkajgiri, Ghatkesar, Medchal, Seriligampally
Shamshabad, Shankarpally, Dharur, Vikarabad, Marpally, Basheerbad and
Tandur are connected by rail also. There are 35 railway stations on broad-guage
in the District with 192.12K.M.s About 49% of the villages are having postal
facilities.
Ghatkesar Railway station is located in Ranga reddy district of Andhra
Pradesh.It belongs to South Central Railways (SCR) junction. Neighbourhood
stations are Cherlapalli,Bibinagar.Nearby railway station in Secunderabad
railway station and nearby Airport is Rajiv Gandhi International Airport. In the
study area Number of villages with available bus facilities are 27 and with train
facilities availability are 2 in number.
1.3.11.1 THE JAWAHARLAL NEHRU INNER RING:
The Inner Ring Road or IRR is a 50 kilometer city arterial road in Hyderabad,
Andhra Pradesh, India. It was built to de-congest city roads and give way for
trucks and other commercial vehicles.IRR's master plan called as Intelligent
Transport System was done by Nippon Koei of Japan. The project which
includes the Outer Ring Road, Hyderabad, is being implemented with assistance
18
from Japanese International Cooperation Agency (JICA) and is expected to
complete by end of 2013.

The road passes through Mehdipatnam including Masab Tank, Banjara Hills,
Begumpet, Mettuguda, Tarnaka, Habsiguda, Uppal, Nagole, L B Nagar,
Santoshnagar crossroads, Chandrayangutta, Kurnool highway, Rajendranagar
bypass road, Attapur, Rethi Bowli. The inner road joins the P V Narsimha Rao
Elevated Expressway at Aramgarh.

1.3.11.2 JAWAHARLAL NEHRU OUTER RING ROAD:
The Outer Ring Road or ORR is a 158 kilometer, 8-lane ring road expressway
encircling the City of Hyderabad, AP, India. It is built by HMDA at a cost of
Rs.6696 crores,with an assistance of Rs 3,123 crores from Japan International
Cooperation Agency.The expressway is designed for speeds of 120 kmph.It
gives a proper connectivity between NH 9, NH 7, NH 4 and state highways
leading to Vikarabad, Srisailam and Nagarjunasagar.The expressway has
fencing and a two-lane service roads on either side.The road aims to improve
connectivity and decongest the traffic flow on the existing major arterials
between the outer suburbs of Greater Hyderabad. The state-run APSRTC is
planning to build 22 terminals-cum-depots (TCD) along the Outer Ring Road.
The ORR passes through the villages in Ranga Reddy, Medak and mahbubnagar
districts viz. Shamshabad, Tukkuguda, Kollur, Narsingi, Gachibowli,
Patancheru, Bowrampet, Gowdavelli, Shamirpet, Ghatkesar, Pedda Amberpet,
Bongloor and Medchal.
1.3.12 ANIMAL HUSBANDRY:
Apart from the production of Milk and Meat, the Cattle in the District are used
as drought power in Agriculture and it is an allied activity to Agriculture. As per
the Livestock Census 2007 the District has livestock population of 16,68,689
lakhs and poultry population of 1,40,99,276 Lakhs.
19
According to Livestock Census 2007 Ghatkesar Mandal has 11888
sheeps,10005 goats,10 horses,51 donkeys,720 pigs,3018 dogs,22 rabbits and
1790964 poultry.
1.3.13 CROPPING PATTERN:
The variation is the fertility of the soils is the main cause for the difference in
the cropping pattern of the eastern and western regions in the District. While
white sandy loams occur in the eastern region (Hayathnagar and
Ibrahimpatnam), Black cotton soils predominate the western region(Chevella,
Pargi, Vikarabad, Marpally and Tandur).The principal crops of the District are
jowar, Paddy, Ragi, Castor and pulses. Food crops account for 83.1% and the
non foodcrops for 16.9% to the gross area sown in the District. Grape cultivation
makes the District occupy the distinct place in the state.
The major crops of Ghatkesar Mandal includes paddy which is cultivated in
1202 Hectares of land, vegetables in 91 Ha and fruits in 122 Ha.
1.3.14 IRRIGATION :
Gross irrigated area for Ranga reddy district in 2009-2010 is 78782 Hectares.
Under Ghatkesar Mandal net area irrigated under is 1791 Ha through tanks, tube
wells dug wells, lift irrigation and other sources. The area irrigated more than
once is 864 Ha and gross irrigated area is 2655 Ha. As per the Ghatkesar Mandal
revenue office report of 2011, there are 468 dug wells, 490 Tube wells and 46
Tanks in Ghatkesar Mandal.
1.3.15 HEALTH & MEDICAL FACILITIES:
There are 18 Civil Hospitals in the District besides a T.B. Sanitorium at
Anathagiri in
20
Vikarabad Mandal, (12) Ayurvedic, (15) Unani and (7) Homeopathic
dispensaries are functioning in the District.
Ghatkesar has 1 Government hospital and 1 primary health care center.
1.3.16 INDUSTRIES:
The Ranga Reddy District is playing an important role in the development of
industries in the State because of its proximity to Hyderabad City. The District is
in more advantageous position for setting up of industries as the location is
nearer to the market and also the easy availability of required technical man-
power. This District has a strong industrial base with public sector undertakings
like BHEL (R&D), ECIL, IDPL,HCL, HAL, HMT Bearings and NFC.
Ghatkesar Mandal has National research centre on meat (NRCM) at
Chengicherla,Boduppal and Central power research institute (CPRI) at
Warangal Highway.
1.3.16.1 SEZ:
A special economic zone (SEZ) is a geographical region that has economic and
other laws that are more free-market-oriented than a country`s typical or national
laws.
The category SEZ covers, including free trade zones (FTZ),Export processing
zones (EPZ),free zones (FZ),industrial parks or industrial estates (IE),free ports,
urban enterprises zone and others.
Usually the goal of a structure is to increase foreign direct investment by foreign
investors, typically a Multinational company (MNC).
Infosys technologies Pvt.Ltd, IT/ITES SEZ is in 60.94 hectares of land at
Pocharam village, Ghatkesar mandal.
21
1.4 SIGNIFICANCE OF THE STUDY
Andhra Pradesh State, Rangareddy District has witnessed remarkable
expansion, growth and developmental activities such as building, road
construction, deforestation and many other anthropogenic activities since its
inception in last few years just like many other state capitals in Andhra Pradesh.
This has therefore resulted in increased land consumption and a modification
and alterations in the status of her land use land cover over time without any
detailed and comprehensive attempt (as provided by a Remote Sensing data and
GIS) to evaluate this status as it changes over time with a view to detecting the
land consumption rate and also make attempt to predict same and the possible
changes that may occur in this status so that planners can have a basic tool for
planning. It is therefore necessary for a study such as this and its associated
problems of a growing and expanding city like many others in the world.
1.5 Justification for the Study
Indeed, attempt has been made to document the growth of Ghatkesar mandal,
Rangareddy district in the past but that from an aerial photography. In recent
times, the dynamics of Land use Land cover change detection and particularly
settlement expansion in the area requires a more powerful and sophisticated
system such as GIS and Remote Sensing data which provides a general
extensive synoptic coverage of large areas than area photography.
22
Table 1.2
Sno. Particular
1 Name of Mandal Ghatkesar
2 No. Of Revenue villages 27
3 No. Of Habitations 38
4 No. Of Gram panchayaths 21
5 No. Of Police stations 2
6 No. Of Households (as per Census 2011) 41406
7 Population particular (as per Census 2011)
Male-
Female-
Total-
90512
84489
175001
8 Education particulars
No. Of Primary schools
No. Of Upper primary schools
No. Of High schools
No. Of Junior colleges
No. Of degree colleges
No. Of Engineering and Medical colleges
49
10
12
5
3
42
9 Government Land
Extent of land assigned for agriculture
Extent of land assigned for House site
Extent of land under community services
(graveyard and shikam)
Extent of land alienated for various
institutions
Extent of land resumed under POT Act
9/77
Ac.6369-11 gts
Ac.1591-02 gts
Ac.425-12 gts
Ac.706-00 gts
Ac.563-34 gts
Ac.73-17 gts
23
10 Agriculture and irrigation
Total geographical area ( in Hectares)
Normal Rainfall
Total forest area ( in Hectares)
Major crops
Paddy ( in Hectares)
Vegetables ( in Hectares)
Fruits ( in Hectares)
No. Of Minor irrigation sources
Dug wells
Tube wells
Tanks
16689
708
905
1202
91
122
468
490
46
11 Civil supplies
No. Of Fair price shops
Total No. Of cards
White cards (21421+1021)
Pink cards
Any cards
ANNAPURNA cards
Allotment of commodities
Rice
Sugar
35
22442
-
1451
11
3532.12
112.21
12 Health
No. Of Government Hospitals
No. Of Sub-centers
No. Of Veterinary Hospital
6
6
1
13 Banking facility
SBH,Ghatkesar 13
24
SBI, Ghatkesar
Union Bank, Ghatkesar
Andhra bank, Peerzadiguda
SBI, Peerzadiguda
27
27
2
27
14 Transport and communication
No. Of Villages with post offices
No. Of Villages with Telephone facilities
13
27
15 No. Of Villages with Bus facilities
available
27
16 No. Of Villages with Train facilities
available
No. Of Villages having protected water
supply
No. Of Drinking water bore wells
No. Of polling stations
2
27
562
121
(Source M..R.O Ghatkesar )
25
CHAPTER-II
LITERATURE REVIEW
2.1 GENERAL
Land is the stage on which all human activity is being conducted and the source
of the materials needed for this conduct. Human use of land resources gives rise
to "land use" which varies with the purposes it serves, whether they be food
production, provision of shelter, recreation, extraction and processing of
materials, and so on, as well as the bio-physical characteristics of land itself.
Hence, land use is being shaped under the influence of two broad sets of forces ±
human needs and environmental features and processes. Neither one of these
forces stays still; they are in a constant state of flux as change is the
quintessence of life. An increasingly common application of remotely sensed
data is for change detection. Change detection is the process of identifying
differences in the state of an object or phenomenon by observing it at different
times (Singh, 1989).
Changes in the uses of land occurring at various spatial levels and within various
time periods are the material expressions, among others, of environmental and
human dynamics and of their interactions which are mediated by land. These
changes have at times beneficial, at times detrimental impacts and effects, the
latter being the chief causes of concern as they impinge variously on human
well-being and welfare. Lay and scientific interest on land use change has a long
history as there have been no instances in which people used land and its
resources without causing any harm. Ancient writers, philosophers, scientists
and the like but also lay people have left records of the unwanted consequences
of changes in the uses of land in the form of pieces of literature, philosophy,
science and folklore.
26
The scientific study of the determinants and impacts of land use change is
not confined, however, to the international level. The subject has engaged
scientists in most countries of the world as, in almost all cases, the control of
land use and the directing of its change towards particular types were of
immediate concern to public authorities and individuals on such matters as
quality of drinking water, availability of water for agriculture, flood and other
natural hazards, fresh and sea water pollution, atmospheric pollution. This
diversity of concerns is associated inevitably with a diversity of disciplines
being involved in these studies. But the earth and life sciences are not the only
and exclusive territories of scientific activity on land use change. The social
sciences and the humanities have long explored various facets of the nature-
society interactions from the level of the individual to the level of social groups,
particular societies, and "society" as a whole. While such a diversity of
perspectives and disciplinary "encounters" on particular subjects are always
welcome, the general impression a student of land use change gets is that of a
polyphony of meanings and of approaches which express particular points of
view, definitions of the issue of land use change, and, consequently, proposed
solutions. The gap between the life or earth sciences, on the one hand, and the
humanities or social sciences, on the other, is particularly visible, intense, and
frustrating. Despite mutual acknowledgment of the close interconnections
between the bio-physical and socio-economic dimensions of land use change,
there is still considerable lack of communication between them and, hence,
limited opportunities for essential integration of their different worlds.
Researchers working on related subjects seem to have limited, inadequate, or no
knowledge and awareness of what each other are doing and how they are
studying particular aspects of the same indivisible entity; land, its uses and their
changes.
27
There would be no immediate concern and urgency for such an
integration was it not for the critical need to address the issues associated with
land use change comprehensively and holistically; i.e. in an interdisciplinary or,
better, in a trans -disciplinary way a term of a rather recent usage, a successor of
the terms multi- and interdisciplinary. Bridging the natural and the social
sciences worlds is expected to provide those necessary theoretical and modeling
frameworks and tools which will assist in the comprehensive conceptualization
and operationalization of the broad repertoire of land use change issues. A
prerequisite to this quest for integration and synthesis of the various theoretical
and modeling approaches to land use change is a thorough stock-taking of all
attempts to date towards this purpose originating in diverse areas of the terrain
of scientific knowledge. The present is a modest attempt to present
systematically and evaluate critically representative approaches to land use
change. It builds on several noteworthy past attempts as well as on the more
recent activities undertaken in the context of the LUCC research program. It is
intended to provide, on the one hand, the ground for a more comprehensive and
in-depth account of extant and evolving approaches and, on the other, the
ground for the much desired synthesis into useful spatial (land use) decision
support systems.
Reviewing and presenting systematically the extant literature on the
subject was not an easy task for a variety of reasons the most important of which
are mentioned here only. The first is, as usual, conceptual/definitional and a
matter of nomenclature. The same concept is defined differently not only in
different but, sometimes, in the same discipline or in its fields and, usually, is
given different names. Or, the same word is used with differing meanings in the
same or in different contexts. Both conceptualizations and definitions may
overlap also making analysis even more troublesome. An example which is
further analyzed in this chapter is the definition of "land use" which sometimes
28
is used synonymously with that of "land cover" especially on aggregate spatial
levels. Similarly, the term "spatial change" is used frequently to denote land use
change although spatial change has a much broader meaning as its use in a
variety of other contexts reveals. This example brings us to the second reason
why this review was not easy which is the fact that land use change is studied
explicitly or implicitly in broader contexts dealing with spatial change and, more
frequently, with environmental change. In these contexts, theorizing on and
modeling of land use change was not always straightforward or did not
constitute the principal object of study although land use was and always is the
inevitable intermediary in the nature-economy-society interactions. Hence, the
study of land use change is masked by the study of other types of changes in
which land use is unavoidably implicated. The third reason, which draws from
the previous one, is that theories of land use change may appear as derivatives of
theories of broader socio-economic and environmental changes. Similarly,
models of land use change may be either simplistic or land use change is
modeled "residually" in the context of larger models; i.e. the emphasis is on
modeling of micro- or macro- socio-economic or environmental change and land
use change is simply assessed as a consequence of these changes by using
simple proportionality coefficients. Lastly, a considerable number of important
theories and models are essentially aspatial, i.e. they take no account of the
material and geographic surroundings and constituents of human activities or
they reduce them to certain uniform, geometric characteristics that bear a remote
or no relationship to the physical characteristics of land. In this case, there is no
direct way to study land use and its changes.
For these reasons, certain decisions were made about what to include and
what not to include in this study from the broad spectrum of theoretical and
modeling approaches which relate, in one way or another, to land use and its
change. The general rule applied was that priority is given to those theories and
29
models which treat land use and, more importantly, its change explicitly.
Finally, although several of the theoretical and modeling approaches which are
included here are used (or, originate) in planning especially, physical, land use
and spatial planning, in general a host of other theories and models which are
relevant in the context of planning are not included explicitly. With this, a last,
important point is made. Land use change is driven by a variety of forces which
relate differently to one another in different spatial and temporal settings.
Holistic theories of land use change need to draw on a variety of theories
relating to the drivers of this change, first, to offer realistic and meaningful
accounts of land use change, second, to provide rigorous theoretical bases for
modeling this change, and, third, to guide action in problem solving (i.e.
planning) situations. More importantly, however, this blending and synthesis of
theories if it is ever achieved - may dissolve the present thematic boundaries
(industrial change, spatial change, institutional change, etc.) and reveal a unified
theory, a meta-theory of change.
2.2 THE PURPOSE FOR LAND USE CHANGE
The approaches taken for the analysis of land use change are determined
critically by the analyst`s objectives. The deIinitions and land use classiIication
systems used, the theoretical schemata adopted and the models employed all
depend on the main questions and the user needs the analysis seeks to address;
i.e. on its purpose. Characteristic purposes of analysis are briefly discussed in
this section grouped into six main categories: description, explanation,
prediction, impact assessment, prescription and evaluation.
Descriptive studies of land use change are almost indispensable in any analytical
endeavor as a first step towards more refined analyses. Description of land use
change documents changes from one type of land use to another over a given
time period and within a given spatial entity. Changes in both the qualitative as
30
well as the quantitative characteristics of land use are described, the level of
detail conditioned by the spatial level of analysis and the availability of requisite
data. Descriptive studies of land use change have provided the impetus for more
thorough investigations of the "why" of these changes as well as for taking
actions to counteract the negative impacts of the changes identified.
Change detection is an important process in monitoring and managing
natural resources and urban development because it provides quantitative
analysis of the spatial distribution of the population of interest. Change detection
is useful in such diverse applications as land use change analysis, monitoring
shifting cultivation, assessment of deforestation, study of changes in vegetation
phenology, seasonal changes in pasture production, damage assessment, crop
stress detection, disaster monitoring, day/night analysis of thermal
characteristics as well as other environmental changes (Singh, 1989).
2.3 DEFINING LAND, LAND COVER, LAND USE, LAND COVER
CHANGE AND LAND USE CHANGE
Studies of land use change do not always employ similar definitions of the
principal terms land, land use and land use change. Definitions and descriptions
of these terms vary with the purpose of the application and the context of their
use. It is, thus, necessary to look at alternative definitions and descriptions of
these terms that are more frequently used in these studies, especially those
offered by official sources of land and land use data.
Land:
Land is the most important natural resources on which all activities are
based. Land use unlike geology, is seasonally dynamic and indeed is more
changing. The increase in population and human activities are increasing the
demand on the limited land and soil resources for agriculture, forest, pasture,
urban and industrial land uses. Information on the rate and kind of changes in
31
the use of land resources is essential for proper planning, management and to
regularise the use of such resources (Gautam N C,1983)
The Food and Agriculture Organization (FAO) defines land as an area of the
Earth`s surIace (FAO 1996). However, FAO (1995) gives a more refined and
holistic definition which was used also in the documentation for the Convention
to Combat Desertification (FAO 1995, 6 citing UN 1994):
"Land is a delineable area oI the earth`s terrestrial surIace, encompassing all
attributes of the biosphere immediately above or below this surface, including
those of the near-surface climate, the soil and terrain forms, the surface
hydrology (including shallow lakes, rivers, marshes, and swamps), the near-
surface sedimentary layers and associated groundwater reserve, the plant and
animal populations, the human settlement pattern and physical results of past
and present human activity (terracing, water storage or drainage structures,
roads, buildings, etc.), (FAO 1995, 6).
Wolman (1987) cites Stewart`s (1968) deIinition oI land: "the term land is used
in a comprehensive, integrating sense...to reIer to a wide array oI natural
resource attributes in a profile from the atmosphere above the surface down to
some meters below the land surface. The main natural resource attributes are
climate, land form, soil, vegetation, fauna and water" (Wolman 1987, 646).
Hoover and Giarratani (1984, 1999) state that land "first and foremost denotes
space... The qualities oI land include, in addition, such attributes as the
topographic, structural, agricultural and mineral properties of the site; the
climate; the availability of clean air and water; and finally, a host of immediate
environmental characteristics such as quiet, privacy, aesthetic appearance, and
so on" (Hoover and Giarratani 1984, 131).
32
FAO (1995) cites Chapter 10 of Agenda 21 (UNCED 1993) which states that
"the definition of land used to be "a physical entity in terms of its topography
and spatial nature; this is often associated with an economic value, expressed in
price per hectare at ownership transfer" (FAO 1995, 6).
It is worth noting that all definitions of land, although in general similar, differ
as to the priority given to the attributes that characterize land. The natural
sciences (FAO 1995, Wolman 1987) start from and detail the natural
characteristics of land while the social sciences, more specifically economics
(Hoover and Giarratani 1984, 1999), start from the mere element of space and
refer more abstractly to the natural features of a segment of space. These
differences in the definition of land show up in the next chapters of this study in
the ways different disciplines theorize on and model land use change.
2.4 LAND USE AND LAND COVER
The terms land use and land cover are not synonymous and the literature draws
attention to their differences so that they are used properly in studies of land use
and land cover change.
Land use reIers to man`s activities and the varied uses which are carried on over
land and land cover refers to natural vegetation, water bodies, rock/soil, artificial
cover and others noticed on the land (NRSA, 1989)
Landuse is a product of interactions between a society's cultural background,
state, and its physical needs on the one hand, and the natural potential of land on
the other (Ram and Kolarkar 1993) An increasingly common application of
remotely sensed data is for change detection. Change detection is the process of
identifying differences in the state of an object or phenomenon by observing it at
different times (Singh, 1989).
33
"Land cover is the biophysical state oI the earth`s surIace and immediate
subsurface" (Turner et al. 1995, 20). In other words, land cover "describes the
physical state of the land surface: as in cropland, mountains, or forests" (Meyer
1995, 25 cited in Moser 1996, 247). Meyer and Turner (1994) add: "it embraces,
for example, the quantity and type of surface vegetation, water, and earth
materials (Meyer and Turner 1994, 5). Moser (1996) notes that: "The term
originally referred to the type of vegetation that covered the land surface, but has
broadened subsequently to include human structures, such as buildings or
pavement, and other aspects of the physical environment, such as soils,
biodiversity, and surfaces and groundwater" (Moser 1996, 247).
"Land use involves both the manner in which the biophysical attributes of the
land are manipulated and the intent underlying that manipulation the purpose
for which the land is used" (Turner et al. 1995, 20). In a similar vein, Meyer
(1995) states that "land use is the way in which, and the purpose for which,
human beings employ the land and its resources (Meyer 1995, 25 cited in Moser
1996, 247). Briefly, land use "denotes the human employment of land" (Turner
and Meyer 1994, 5). Skole (1994) expands further and states that "Land use
itself is the human employment of a land-cover type, the means by which human
activity appropriates the results of net primary production (NPP) as determined
by a complex of socio-economic factors" (Skole 1994, 438). Finally, FAO
(1995) states that "land use concerns the function or purpose for which the land
is used by the local human population and can be defined as the human activities
which are directly related to land, making use of its resources or having an
impact on them" (FAO 1995, 21).
While the above definitions of land use refer mostly to larger, territorial scales,
at the urban scale, interest focuses on other aspects of the term. In the words of
Chapin and Kaiser (1979): "At territorial scales involving large land areas, there
is a strong predisposition to think of land in terms of yields of raw materials
34
required to sustain people and their activities. At these scales, land` is a
resource and land use` means resource use`. In contrast, at the urban scale,
instead of characterizing land in terms of the production potential of its soils and
its submineral content, the emphasis is more on the use potential oI the land`s
surface for the location of various activities" (Chapin and Kaiser 1979, 4). This
connotation of the term "land use" is implicit in several other texts dealing with
land use in the context of urban and regional analysis and planning.
As it was the case with the definition of the term "land" above, different
definitions of "land use" are employed at various levels of analysis and, most of
the time, by different disciplines, a fact that inhibits more holistic and integrated
approaches to the analysis of land use and its change in general. Wolman (1987)
cites Clawson (1982, 111) noting ". the diIIerence in the perception the city
planners and the agricultural experts have of land use" (Wolman 1987, 647).
The description of land use, at a given spatial level and for a given area,
usually involves specifying the mix of land use types, the particular pattern of
these land use types, the areal extent and intensity of use associated with each
type, the land tenure status (Bourne 1982, Skole 1994). Remote sensing data
with rapid in-time availability, high resolution and low cost product is an
important tool for planning activities and can be used to study the physical
characteristics of terrain depicting various land and water resources. These
maps as a reliable input can be put to a Geographic Information System (GIS)
to describe natural resources both renewable and non-renewable as well as
cultural and human resource (Anji Reddy, 2003).
35
2.5 LAND USE CHANGE: ENVIRONMENTAL AND SOCIO-
ECONOMIC IMPACTS
The second central question with which the analysis of land use change is
concerned is: "the (environmental and socio-economic) impacts of land use
change". In fact, it was the negative impacts that stimulated the scientific and
policy interest on land use change. As Kates et al. (1990) put it, "The lands of
the earth bear the most visible if not necessarily the most profound imprints of
humankind`s actions" (Kates et al. 1990, 6).
The impacts of land use change are broadly categorized into environmental and
socio-economic, the former having received more attention and publicity than
the latter. One of the reasons for this imbalance in attention may be that the
latter are more subtle, longer-term and subject to the influence of many more
complex, and less visible and verifiable, factors than the former. But, it should
be noted that the environmental and the socio-economic impacts are closely
interrelated; the former causing the latter which then feedback to the former
again, potentially causing successive rounds of land use change. A widely
publicized case of a chain of environmental and socio-economic impacts of land
use change is that of shifting cultivators in Latin America and other parts of the
world. The sequence of land use change starts with forest clearance; cultivation
follows, then heavy grazing, and, ultimately, land abandonment and movement
to another location (along newly built highways which serve oil drilling sites)
where the sequence is repeated (Blaikie and Brookfield 1987).
The impacts of land use change are usually distinguished according to the spatial
level on which they manifest themselves into global, regional and local impacts.
Note that the terms global, regional and local do not have a precise physical
meaning in studies of land use change especially as regards the regional and
local levels. For example, a region may be a subdivision of the world (e.g. Latin
36
America, China, the Sahel, large world biomes , etc.) or a subdivision of a large
nation (e.g. a state or a group of states of the USA) or, even a sub-regional
subdivision of a nation`s region. From another viewpoint, Ior the purposes oI the
analysis of the impacts of land use change, a region may be defined on the basis
of geographic and environmental characteristics like the Mediterranean region,
the Baltic Region, etc. Similar comments apply to the delineation of local areas
especially where the local is used as the opposite of the global.
As regards the global environmental impacts of land use and cover change,
Meyer and Turner (1996) note that "Land use and land cover is a relatively new
addition to the core concerns of global environmental change research. Its full
incorporation was delayed by a narrow view of what could be considered global
change, restricting it to those processes that occur in fluid global change
systems: the atmosphere, the oceans, the climate. Human impacts in this realm
have been referred to as systemic forms of global change (Turner et al. 1990);
they are incontestably global in the sense that intervention at one point can
affect the entire system, having direct physical repercussions on the other side of
the globe. The classic examples are stratospheric ozone depletion , global
climate change, through an intensified greenhouse effect, and eustatic sea-level
rise as a consequence of climate change" (Meyer and Turner 1996, 237). These
authors continue to point out that, even in the narrow, systemic meaning of
global change, land use change impacts can be global in nature as: (1) many
land uses (e.g. agriculture, grazing and forestry) release substantial amounts of
trace gases that may produce global climate change and (2) a thorough
understanding of the land-use/cover systems that are affected is required to
assess the environmental and other impacts of many global phenomena like sea-
level rise or stratospheric ozone depletion (Meyer and Turner 1996).
In addition, Meyer and Turner (1996) emphasize that land use-cover change
impacts "are basic to another class of environmental changes that can be
37
regarded as global in reach, the ones that Turner et al. (1990) call globally
cumulative. Though not physically connected through a globally operating
system, these changes can reach a global scale and status when their occurrence
in many places adds up. Deforestation, wetland drainage, and grassland
degradation have all amounted to a globally significant alteration of the land
cover class involved" (Meyer and Turner 1996, 237-238). Large scale
environmental phenomena like land degradation and desertification ,
biodiversity loss, habitat destruction and species transfer (Meyer and Turner
1996) fall in the same category as all of them are caused by land use changes. A
comprehensive review of global environmental transformations associated with
land use changes can be found in Kates et al. (1990).
At subglobal scales, what is broadly referred to as the regional level, the
environmental impacts of land use change are equally significant and widely
known. Eutrophication of water bodies, acidification of aquatic and terrestrial
ecosystems, floods, soil nitrate pollution , land degradation and desertification ,
groundwater pollution, marine and coastal pollution and many more are
environmental alterations that follow either directly or indirectly from land use
changes (see, for example, Briassoulis 1994, Brouwer et al. 1991, Blaikie and
Brookfield 1987, Jongman 1995, Laws 1983, Ortolano 1984) . The sources of
these regional impacts may not be located in the receptor region but they may be
located in more than one (frequently distant) regions. The prominent example in
this case is acidification that involves long-distance transport of acidifying gases
and substances. In addition, several of the regional impacts of land use change
take a long time to show up as it is the case of chemical soil pollution and the
phenomenon of the so- called "chemical time bombs". These are defined as
possible chains of events responding to slow environmental alterations, resulting
in the delayed and sudden occurrence of harmful effects due to the mobilization
38
of chemicals stored in soils and sediments (Hesterberg et al. 1992, Stigliani
1991).
Finally, land use change causes a multitude of environmental impacts at the
lower spatial levels in urban, suburban, rural and open space areas which have
been extensively documented. Especially important are the land use changes
(land conversion) that occur in the periphery of large urban concentrations that
are subject to urbanization and industrialization pressures and frequently result
in losses of prime agricultural lands and tree cover. Their environmental impacts
include changes in the hydrological balance of the area, increase in the risk of
floods and landslides, air pollution, water pollution, etc. Other local impacts of
land use change include soil erosion, sedimentation, soil and groundwater
contamination and salinization , extinction of indigenous species, marine and
aquatic pollution of local water bodies, coastal erosion and pollution. The
importance of these impacts is not restricted to the local area of interest as they
are frequently cumulative arising out of the decisions of many individual land
and property owner to act in their narrow self-interest. In addition, land use
changes in one area may have environmental repercussions in other distant
areas. For example, urbanization or tourism development in an area increases
the demand for water which, however, is provided by another area. Excess water
abstraction reduces the water available for agriculture and plant growth in the
latter area and may induce saltwater intrusion in coastal areas.
In addition to the environmental, the socio-economic impacts of land use change
are equally significant and give rise to serious concerns at all spatial levels.
Global level socio-economic impacts concern issues of food security, water
scarcity, population displacement and, more generally, the issue of human
security and vulnerability to natural and technological hazards. International and
non-governmental organizations such as the FAO, the World Bank, the IHDP
Programme, etc. undertake systematic assessments to support policy and
39
decision making at all spatial levels on the above issues (Alexandratos 1988,
Liverman 1989, Lonergan 1998).
The food security and the water scarcity issues may arise out of reductions in the
area of agricultural land and decreases in available water supplies that result
from soil erosion, land degradation, desertification , industrialization,
urbanization, suburbanization, and above all, poor management of
environmental resources. In all these instances, unsuitable uses of land play an
important role. These issues concern the fundamental question of whether there
is enough food to feed the growing population of the earth and enough water to
cover present and future demands of an increasingly industrializing and
urbanizing world. In parallel, they concern the question of whether the
distribution of the food and water resources is even throughout the globe.
Population displacement is another issue that is being investigated to identify the
potential role played by environmental degradation to population movements
away from localities experiencing environmental stress. Finally, human security
and vulnerability is a collective term used to denote all those factors that may
pose threats to human health, welfare and well-being in a given geographic area.
A proposed measure is the "Index of Vulnerability" comprising 12 indicators ±
food import dependency ratio, water scarcity, energy imports as a percentage of
consumption, access to safe water, expenditures on defense vs. health and
education, indicator of human freedoms, urban population growth, child
mortality, maternal mortality, income per capita, degree of democratization and
fertility rates (Lonergan 1998, 27).
Regional level socio-economic impacts of land use change are more variegated
reflecting the variety of regional settings where these changes occur. These, too,
however, arise out of the same processes discussed above and evolve around
such issues as availability of land for regional food production, changes
(reduction) in land productivity and, consequently, lower profitability and
40
changes in industrial structure, employment/ unemployment, poverty, population
change and migration, and quality of life issues such as health and amenity.
Finally, local level socio-economic impacts of land use change comprise similar
concerns but they are restricted to the particular localities where these changes
occur. The issue of farmland conversion to urban and other uses has received
special publicity and concern has been expressed as, in addition to the
environmental impacts mentioned before, it causes also serious socio-economic
impacts. In the case of tourism development on previously agricultural land, a
less visible but extremely important socio-economic impact is the increased
dependency of the tourist region on not locally produced farm products and the
increased pressures for agricultural output grown in and bought from other
areas. Local level socio-economic, like the environmental impacts, may act
cumulatively and cause larger than local impacts in the longer term.
A point that needs to be stressed is that usually all impacts of land use change
are assumed to be negative. This is not always true for two reasons. First,
whether an impact is positive or negative depends on the spatial and temporal
scale concerned. Second, human mitigating forces mentioned above, such as
environmental and social regulation and policies, land restoration projects and
similar actions may impede the negative influences of human driving forces and,
thus, mitigate if not eliminate, the unwanted consequences of land use change.
The larger question, however, that relates to the impacts of land use change is
that of the sustainability of development at all spatial levels. Conceptualizing
sustainability as the achievement of a balance between social, economic and
environmental goals, the role of land use and its change is of central importance.
The negative environmental and socio-economic impacts of land use change
detract from the achievement of these go as they erode both the environmental
and the socio-economic resource base of an area and, thus, reduce its ability to
41
support equitably the needs of its population both in the short and in the longer
term. In this perspective, land use planning and management become
imperative. The broad goal of managing land use and its change is to develop
the land resources in ways that capitalize on their local potential and suitability,
avoid negative impacts and respond to present and future societal demand within
the limits of the carrying capacity of the local environment.
2.6 LAND USE AND LAND COVER CLASSIFICATION SYSTEMS
The analysis of land use change depends critically on the chosen system of land
use and land cover classification. The magnitude and quality of land use change
is expressed in terms of specific land use or land use/cover types. The
assessment of the environmental and socio-economic impacts of land use change
is possible only when the particular environmental and socio-economic features
of the chosen land use/cover types are specified. If this requirement is not met,
then, the analysis will be of limited value in guiding policy and decision making
especially at lower scales. Hence, the need to discuss available land use and land
cover classification systems and consider their suitability for the analysis of land
use change at various spatial and temporal levels.
In developing any land classification system, a central dilemma concerns the
choice between representing "what is" and "what should be". The "what is"
encompasses the land available on earth and its characteristics as described by a
given technology at a given point in time while the "what should be" relates to
values placed on the land and its characteristics and the resulting choices made
by people about uses for land (Wolman 1987, 655).
Before considering alternative land classification systems it is worth noting that
all of them are distinguished in terms of the spatial scale of analysis for which
they are developed and the purpose of their development. The spatial scale
determines the level of environmental and socio-economic detail contained in
42
the classification system while the purpose of the study determines the particular
attributes of the land use types that will be considered. In addition, available
technology for data collection is a significant determinant of their structure and
content. The following presentation will attempt to focus on land use as opposed
to land cover classification systems although the two are often interrelated (as
land use and land cover are interrelated) and the existing systems do not always
distinguish clearly between land use and land cover.
The development of land classification systems has a long history in various
countries of the world. Soil classification systems were the first to be produced
by both national (e.g. the U.S. Soil Conservation Service, Canada`s Soils
Directorate) and international (the FAO) organizations to serve the needs of
producing soil maps and provide a basis for determining land capability and
suitability for growing various types of crops. The need for developing land use
and land cover classification systems ensued first focusing, as it was natural, on
agriculture and forestry uses of land occupying large tracts of land and playing
important environmental and economic roles. After the 1960s and 1970s, efforts
to develop land use and cover classification systems for other types of land use
proliferated, a response to growing urban and industrial pressures on land and
the need to provide a basis for rational land use planning and management. In
the following, examples of land use and cover classification systems at various
spatial scales and for various purposes are offered.
At the world scale, the first land use classification systems produced concerned
the major land uses of the world. The FAO produces land use statistics, starting
in the 1950s, using a 4-category classification of land use: arable land (or,
cropland), grass land (or permanent pasture), forest land (or, forest and
woodland), other land (which includes urban areas, unmanaged rangelands, land
in polar regions, desert land, tundra, stony and rocky land in mountains and all
other classified land) (Wolman 1987, 647; Beale 1997). Wolman (1987),
43
however, cites another FAO publication describing world land use in terms of
five categories: arable or cropped, meadow and permanent pasture, forest and
woodland, unused but potentially productive, and built-over, wasteland and
other. The relevant data are collected annually by means of questionnaires from
national governments. Since the mid-1990s, the FAO is in the process of
developing a more elaborate international framework for classification of land
uses using a 3-level hierarchical system to develop classes of land use.
At the sub global level, mostly the national level, several land use
classification systems are in use. In the U.S.A., the U. S. Geological Survey has
developed the Land Use and Cover Classification System for use with remotely
sensed data (Anderson et al. 1976). This system, like the FAO system, uses a 2-
level hierarchy to define classes of land use and it is suitable up to the substate
regional level. In Canada, the Lands Directorate of Environment Canada
initiated the Canada Land Inventory in 1963 (Pierce and Thie 1981). An
elaborate land use classification system has been set up which is being
continuously improved to meet the variegated needs of users and uses. In
Europe, several land use classification systems appeared especially after the
1980s. Two of them are mentioned here (the reader can find more information
about other systems and related projects in Beale 1997). The CORINE system
(Coordinated Information on the European Environment) was set up in 1985 in
the European Community with the objective, among others, to improve data
availability and compatibility across the European Community and within the
member states. Its final product is a digital land cover data base made up of 44
classes with mapping units based on a tiered hierarchical classification scheme
(NUTS) used in the European Community for statistical purposes. Another
project, CLUSTERS (Classification for Land Use Statistics: Eurostat Remote
Sensing Programme), is being developed in coordination with the EUROSTAT
(the European Union Agency for statistical information). This system is also
44
based on a hierarchical scheme of developing land use types that attempts to
provide a standard system for studying land use applicable throughout the
European territory whilst taking into account official classifications of land use
at European level.
Land use classification systems vary with the purpose and context of their use
also. Classification systems for special types of land use usually employ more
detailed and elaborate criteria that reflect the particularities of the land use type
of concern as well as the intended use(s) of the classification system. In
particular, emphasis is given on those characteristics of the land resources that
determine the suitability of land for a given use or may constrain its
development. Land use classification systems for agriculture are the most widely
developed both by international (the FAO) and national organizations. The FAO
has produced several documents describing procedures for land evaluation in
agriculture in which criteria to classify agricultural land are described and
detailed definitions of land use types and their subdivisions and other features
are offered (FAO 1976, 1978, 1996; Alexandratos 1988). For example, in
developing the Agro-Ecological Zoning (AEZ) methodology a procedure for
small scale land suitability assessment, land was described on the basis of the
15,000,000 Soil Map of the World and an inventory of climatic data. Land use
requirements are de facto climate-related and soil-related crop requirements.
Land use alternatives were restricted to those involving the world`s major
(annual) food and fibre crops, selected on the basis of the area occupied, the
total production and the financial value they represent. Eleven major crops were
selected: wheat, paddy rice, maize, pearl millet, sorghum, cotton, phaseolus
bean, white potato, sweet potato and cassava (FAO 1996). Land use was
classified into Land Utilization Types (LUT) defined as "a use of land defined in
terms of a product, or products, the inputs and operations required to produce
these products, and the socio-economic setting in which production is carried
45
out" (FAO 1996, 72). Note that in a previous publication, FAO defined a major
kind of land use as "a major subdivision of rural land, such as rainfed
agriculture, irrigated agriculture, grassland, forestry or recreation" (FAO 1976).
The AEZ typology presented above has been used in several studies of land use
change and land use planning at various spatial levels.
Typologies for agricultural land use classification are developed also by
competent national bodies such as the USDA, the USGS, the BLM in the USA,
the Lands Directorate in Canada, various agencies in the European Union and its
member states and other countries internationally. A very thorough analysis of
past and contemporary efforts towards developing an agricultural typology is
found in Kostrowicki (1991).
Land use-cover classification systems for forest and woodland are equally well
developed despite the wide differences found among countries as regards
applicable definitions and typologies (Moser 1996). FAO, the U.N. ECE, the
World Resources Institute, the USGS, the USFS, the BLM, the Joint Research
Centre (JRC) of the European Union at Ispra (Italy) and many other agencies
worldwide provide systems of forest land classification that are instrumental in
recording quantitative and qualitative changes in the status of forests in
individual countries, large world regions and internationally. Classification
systems for parks and parkland also exist given their important role in nature
preservation and various types of recreation (Wolman 1987).
Finally, classification systems for the built environment (urban land use and
transportation systems) are increasingly being developed the historical origin for
their necessity being identiIied with McHarg`s (1969) plea Ior designing the
built environment within the limits set by nature. Given the variety of types of
built-up land and the contexts within which it occurs, selected ways to classify
urban land use are presented here based on Chapin and Kaiser (1979). These
46
authors define classification as "a systematic means of grouping similar
categories of land use in the pursuit of some predetermined goals" (Chapin and
Kaiser 1979, 239). Many of the available systems have been influenced by the
SIC (Standard Industrial Classification) system that is used for the classification
of industrial activities (Chapin and Kaiser 1979, 240). This is a hierarchical
system of classification, the lower level codes giving more detail on the
characteristics of the industrial establishment(s) and products involved ± and the
associated space requirements for the present purposes.
Two things must be noted as regards the development of land use classification
systems in general. Firstly, the context of development and use of these systems
determines critically their structure and content. In several countries, particular
land use types exist which are absent or negligible in other countries (e.g.
informal settlements, desert). Secondly, the development of land classification
systems is increasingly being influenced by the availability and use of satellite
data and remote sensing techniques. These changes in technology facilitate the
direct use of available data in conjunction with available techniques of analysis
and models. Cowen and Jensen (1998) discuss the capability of remote sensing
technology to measure key attributes of urban and suburban environments
accurately at the requisite levels of spatial, temporal, and spectral resolution.
They present a Table which depicts the relationships between selected
urban/suburban attributes and the remote sensing resolutions required to provide
such information (Cowen and Jensen 1998, 166).
To close this section, a brief discussion of the problems encountered in the
development and use of land use/cover classification systems for the analysis of
land use change is deemed necessary. Firstly, these systems have undergone
several changes over time reflected in changes in definitions of the land
use/cover types. These changes are due to changes in the qualitative
characteristics of the uses of land itself (and the corresponding land cover), the
47
needs of various types of users, the methods of analysis, and the technology
used to collect and record the related data. Wolman (1987) notes that "the recent
use of remote sensing techniques can introduce changes in classification as
mapping units are defined by distinctive signatures of the many sensors used"
(Wolman 1987, 647). Turner et al. (1995) observe that, originally, data
collection was based on field surveys. After the 1960s, new survey techniques
based on computer processing of aerial photographs and satellite images are
being used. "These techniques directed classifications towards the land cover
attributes captured in such imagery. Many existing land use classifications are
based on the vegetational and artificial cover of the land surface: the World
Land Use Classification, the Canada Land Inventory and Land Use
Classification, the Second Land Use Survey of Britain Classification, the
Canadian Land Use Classification, and the World Map of Present-Day
Landscapes (Moscow State University-UNEP 1993, Rjabehakovnd.) to name a
few" (Turner et al. 1995, 49).
The result of these changes is that "Not all classifications of land are
semantically consistent and the typologies become even more complex as the
scale is enlarged, covering smaller and smaller areas, and as the focus of interest
shifts" (Wolman 1987, 647). A review of land use classification systems by
Mucher et al. (1993) indicates that none of them is acceptable in a global change
context (cited in Turner et al. 1995, 49). The drawbacks they note include: (a)
lack of a sound definition of the units of analysis, ranging from field to farm to
region (confused with mapping units); (b) overlapping of land use classes
(because of the lack of clearly defined criteria; most hierarchical classifications
are only comprehensive at the first level, and are far from comprehensive at
lower levels); (c) near-total absence of quantitative class boundaries (critical or
threshold values of the criteria), adding a significant subjective element to land-
use assignments; (d) combination of land use with other dimensions, such as
48
climate characteristics, that may influence land use but are not inherent features
of it; (e) multiplicity of land use classification objectives, often closely tied to
regional or disciplinary foci (Turner et al. 1995, 49-50). Turner et al. (1995, 50)
observe that existing classifications do not use common classificatory principles
and often conflate use and cover. Similar problems exist for classification
systems of particular land use types.
2.7 CASE STUDIES
(i) Land use and land cover change detection through remote sensing
approach:A case study of Kodaikanal taluk, Tamil nadu,
(Prakasam.C,2010).
Land use and land cover is an important component in understanding the
interactions of the human activities with the environment and thus it is necessary
to be able to simulate changes. Empirical observation revealed a change in land
use land cover classification in Kodaikanal taluk, a part of Western Ghats
located in Tamilnadu state.
In this paper an attempt is made to study the changes in land use and land cover
in Kodaikanal Taluk, a part of Western Ghats located in Tamilnadu state ,over
40 years period (1969-2008).The study has been done through remote sensing
approach using SOI Taluk map of Kodaikanal (1969), and Land Sat imageries of
May 2003 and April 2008.
The land use land cover classification was performed based on the Survey
of India Kodaikanal Taluk map and Satellite imageries. GIS software is used to
prepare the thematic maps. Ground truth observations were also performed to
check the accuracy of the classification. The present study has brought to light
that Iorest area that occupied about 70 per cent oI the Taluk`s area in 1969 has
decreased to 33 per cent in 2008.Agricultural land, Built up area, Harvested land
49
and Waste land also have experienced change. Builtup lands (Settlement) have
increased from 3 per cent to 21 per cent of the total area. Kodaikanal area is
identified as one of the biodiversity area in India. Proper land use planning is
essential for a sustainable development of Kodaikanal Taluk.
(ii) Change detection in landuse and landcover using remote sensing and
GIS techniques,( Vemu Sreenivasulu et. al,2010)
Landuse and landcover exerts considerable influence on the various hydrologic
phenomenons such as interception, infiltration, evaporation and surface flow.
Various aspects of hydrological problems (i.e. Rainfall-Runoff modeling,
Sedimentation studies, etc.) can be studied if information on landuse / landcover
is available for a catchment. In the present study, a landuse / landcover maps of
Devak catchment for the years 1958,79,90 and 98 is prepared by Image
processing and visual interpretation technique from the analysis of the IRS-1A
L2B2 (FCC) data for the year 1990, IRS-1C LISS-III (digital data) for the year
1998 and SOI topographic maps for the year 1958 &1979.
Level-I classification is adapted and the various categories of landuse are
Mixed forest mainly pine, agricultural with sparse habitation, open scrub &
scattered trees and water bodies (river). Results revealed a large change in the
area of different landuse categories during the period from 1958 to 1998.The
open scrub and scattered tress covering an area of about 46.17% in 1958 reduced
to 9.90% in 1998,while the area under mixed forest increased from 36.68% in
1958 to 65.84% in 1998. The agriculture with sparse habitation also increased
from 7.09 % in 1958 to 13.92 % in 1998. The main river drainage covering an
area of about 10 % of the total catchment.
50
(iii) Land Use And Land Cover Change Detection And Urban Sprawl
Analysis Of Vijayawada City Using Multitemporal Landsat Data, (K.
sundarakumar et.al.,2012)
Land use and land cover change has become a central component in current
strategies for managing natural resources and monitoring environmental
changes. Urban expansion has brought serious losses of agriculture
land,vegetation land and water bodies. Urban sprawl is responsible for a variety
of urban environmental issues like decreased air quality, increased runoff and
subsequent flooding, increased local temperature, deterioration of water quality,
etc. In this work we have taken Vijayawada city as case to study the urban
expansion and land cover change that took place in a span of 36 years from 1973
to 2009. Remote sensing methodology is adopted to study the geographical land
use changes occurred during the study period. Landsat images of TM and ETM+
of Vijayawada city area are collected from the USGS Earth Explorer web site.
After image pre-processing, un-supervised and supervised image classification
has been performed to classify the images in to different land use categories.
Five land use classes have been identified as Urban (Built-up), Water body,
Agricultural land, Barren land and Vegetation. Classification accuracy is also
estimated using the field knowledge obtained from field surveys. The obtained
accuracy is between 73 to80 percent for all the classes. Change detection
analysis shows that Built-up area has been increased by 372.28%, agricultural
area has been decreased by 65.16% and barren area reduced by
60.98%.Information on urban growth, land use and land cover change study is
very useful to local government and urban planners for the betterment of future
plans of sustainable development of the city.
51
(iv) Land Use and Land Cover Assessment along Pondicherry and its
Surroundings Using Indian Remote Sensing Satellite and GIS, ( E.P.
Nobi,2009).
Land use/land cover mapping serve as a basic inventory of land resources
through out the world. Whether regional or local in scope, remote sensing offers
a means of acquiring and presenting land cover data in timely manner. Land
use/land cover pattern of Pondicherry and its surroundings were studied using
IRS IC LISS III data. The land use/land cover patterns were visually interpreted
and digitized using ERDAS IMAGINE software. The study observed that
agriculture area (52.89%) is dominant in Pondicherry and its surroundings
followed by settlement with vegetation (18.35%). The study recommends the
use of satellite imageries for future environmental monitoring studies.
(v) Land Use and Land Cover Change Detection of Mouteh Wildlife
Refuge
Using Remotely Sensed Data and Geographic Information System, (V.
Rahdary et. al.,2008)
Environmental managers are interested to know land use/cover types and their
change detection in time series for sustainable land management. Remotely
sensed data due to periodic covering, data integrity and provide data in different
range of electromagnetic radiation and possibility to use by different hardware
and software, having high ability to prepare land cover/use maps. Major aim of
this study is to prepare land use/cover and their change detections by using RS
and GIS techniques. In this paper MSS images for 1972, TM scene for 1986,
TM scene for 1998 and LISS III scene for 2005. First images georeferenced.
Land use/cover maps were prepared by several image processing. Vegetation
cover's map was prepared in percentage by using SAVI index and field surveys.
52
Land cover produced by using hybrid image classification approach. Land cover
and land were classified into natural, semi natural and manual.Then changes
were detected by post classification comparison approach in four past decades.
Results suggested that manual land use increased from 176(ha) in 1972 to
1035(ha) in 2005.
(vi) Classification of lulc change detection using remotely sensed data for
coimbatore city, tamilnadu, india, ( Y.Babykalpana et al.,2010).
Maps are used to describe far-off places . It is an aid for navigation and military
strategies. Mapping of the lands are important and the mapping work is based on
(i). Natural resource management & development (ii).Information technology,
(iii). Environmental development, (IV). Facility management and (v). e-
governance. The Landuse / Landcover system espoused by almost all
Organizations and scientists, engineers and remote sensing community who are
involved in mapping of earth surface features, is a system which is derived from
the united States Geological Survey (USGS) LULC classification system. The
application of RS and GIS involves influential of homogeneous zones, drift
analysis of land use integration of new area changes or change detection
etc.,National Remote Sensing Agency(NRSA) Govt. of India has devised a
generalized LULC classification system respect to the Indian conditions based
on the various categories of Earth surface features , resolution of available
satellite data, capabilities of sensors and present and future applications. The
profusion information of the earth surface offered by the high resolution satellite
images for remote sensing applications. Using change detection methodologies
to extract the target changes in the areas from high resolution images and rapidly
updates geodatabase information processing. Traditionally, classification
approaches have focused on per-pixel technologies.Pixels within areas assumed
to be automatically homogeneous are analyzed independently. These new
53
sources of high spatial resolution image will increase the amount of information
attainable on land cover. Significance is that the data can be acquired by our
eyes and the energy can be analyzed.But satellites are capable of collecting data
beyond the visible band also. However, the traditional method of change
detection are not suitable for high resolution remote sensing, images. To
overcome the limitations of traditional pixel-level change detection of high
resolution remote sensing images, based on georeferencing and analysis method,
this paper presents a unsullied way of multi-scale amalgamation for the high
resolution remote sensing images change detection. Experiment shows that this
method has a stronger advantage than the traditional pixel-level method of high
resolution remote sensing image change detection.
(vii)Land Use Change Detection Along The Pravara RiverBasin In
Maharashtra, Using Remote Sensing And Gis Techniques, (Veena U.
Joshi,2009 )
In the past few decades there has been an increasing pressure of population all
over the world, especially in India, resulting in the utilization of every available
patch of available land from woodlands to badlands. The study area represents a
basin which is economically growing fast by converting the fallow lands,
badlands and woodlands to agricultural land for the past few decades. IRS
(Indian Remote sensing Satellites) 1 C ± LISS III and IRS 1 C PAN and IRS P6
± LISS III and IRS 1 D PAN Images were merged to generate imageries with
resolution matching to the landscape processes operating in the area. The images
of the year 1997, 2000, 2004 and 2007 were analyzed to detect the changes in
the landuse and landcover in the past ten years. The analysis reveals that there
has been 20% increase in the agricultural area over the past ten years. Built up
area also has increased from 1.35% to 6.36% of the area and dense vegetation
also has marginally increased. The remarkable increase in the agricultural area
54
occurs owing to the reclaim of the natural ravines and fallow lands. Presently the
area looks promising, but it is necessary to understand the sedimentological and
geomorphological characteristics of the area before massive invasion on any
such landscapes because the benefit may be short lived.
(viii)Land Use And Land Cover Changes Detection Using Multitemporal
Satellite Data, Cuddalore Coastal Zone, Sea coast Of India, (
Muthusamy.S,2010 )
Cuddalore coastal zone is located along the southeast coast of India, Tamil
Nadu. This coastal zone is suffering from many natural catastrophes such as
storms, cyclones, floods, tsunami and erosion. The study area is seriously
affected by 2004 Tsunami and during 2008 Nisha cyclone. The present study
aims to study the land use/cover changes through exploratory analyses, land
cover classification, and change detection analyses conducted on multitemporal
Landsat satellite data (1977, 1991 and 2006). Based on the quantitative analysis
on LULC, it was observed that a rapid growth in built up land between 1977 and
2006 while the periods between 1977 and 2006 witnessed a reduction in this
class. It is expected that the expansion of built up area will follow the same trend
from the year 2006 onwards. The settlement with vegetation covers nearly
8.876% of the total area. The dominant land use categories in 1977 were
settlement with plantation, which occupied 2.397%. In 1991 settlement with
plantation covered nearly 4.743 % in Cuddalore coastal zone. This increase is
due to population explosion and the construction of buildings and factories.
Landsat satellite data using remote sensing and GIS also proved that the model
can be employed under different climate changes as well as management
scenarios for developing adaptation strategies for this study area.
55
(ix) Human Induced Land Use/ Land Cover Changes In Northern Part Of
Gurgaon District, Haryana, India, ( B. S. Chaudhary,2008).
There is tremendous pressure on the natural resources due to increasing
population. To meet the demands of large population means the need for more
food production, more requirement of energy, more water requirement, better
civic amenities for a reasonable quality of urban life, more infrastructure
development to sustain increasing pressure and increased per-capita expenditure
for maintaining quality of life. Land resources being finite imply more judicious
use of land resources to meet the ever-increasing demands. The unsustainable
and unplanned exploitation of land resources is the major reason for degradation
of our environment. The main issue is to bring a balance between economic
development and conservation of resources, which is possible by proper
inventory, and management of these resources on periodic basis. Recent
technologies of Remote Sensing (RS) and Geographic Information System
(GIS) have made it feasible and cost effective. Present study deals with RS and
GIS based monitoring of land use/ land cover changes in northern part of
Gurgaon District, Haryana. Total area under study is about 697 sq. km. IRS 1B
LISS II satellite data paper prints of August 1996 and February 1997 and IRS-
IC/ID LISS-III digital data of August/ September 2001, February 2002 and June
2002 were used. This data was analyzed in GIS environment. It is found that
there is maximum increase in the area under settlements, which has increased
almost four times over this period. The double crop area showed a decline
however there as an increase in the area under closed forest. The wasteland has
also decreased drastically due to its conversion to Settlements and other
categories. The causes of these changes have also been analyzed.
56
(x) Land Use And Land Cover Change Detection Through Remote Sensing
Approach, ( Chetan Laxman Hulsure,2011)
Land use and land cover is an important component in understanding the
interactions of the human activities with the environment and thus it is necessary
to be able to simulate changes. Empirical observation revealed a change in land
use land cover classification in Solapur City. In this paper an attempt is made to
study the changes in land use and land cover in Solapur city over 10 years
period . The study has been done through remote sensing approach using
Cadastral map of Solapur city, and Land Sat and LISS III imageries of Nov.
2000, Oct. 2005 and Nov. 2009. The land use land cover classification was
performed based on the Cadastral map of Solapur city map and Satellite
imageries. GIS software is used to prepare the thematic maps. Ground truth
observations were also performed to check the accuracy of the classification. In
2000 agricultural area was 61.11% upto 2009 this area is decreased and remain
45.32% of the study area. Simultaneously Built Up area is increased from
14.18% to 31.57% in to 2000 to 2009. In 2000 wasteland area was 23.19% upto
2009 this area is decreased and remain 21.98% of the study area. Water body
remains constantly. Proper land use planning is essential for a sustainable
development of Solapur City.
(xiii)Trend in Land Use/Land Cover Change Detection by RS and GIS
Application (N. Nagarajan et al.,2011)
The study aims to effects of Land Use / Land Cover Changes (LU/LCC) is the
quantitative method, to expound the impact of land use/land cover changes in
Manimuktha sub-watershed of Vellar basin, Tamilnadu, India. The relationship
between Land Use Changes and its trend is analysed using IRS IC LISS III and
PAN merged data. Further, the preparation of LU/LC map using Survey of India
57
(SOI) Toposheet for the year 1972 has come in handy to know the past land use
pattern. Similarly, the Land Use/Land Cover (LU/LC) map of various years,
namely, 1996, 2003 and 2007, which was digitized, using Arc GIS 9.1 software.
About 52.89 per cent of land is devoted to agricultural practices under
agriculture and cropland has a major impact over the hydrological processes of
the basin. Hence, the information obtained from change detection of LU/LC aids
in providing optimal solutions for the selection, planning, implementation and
monitoring of development schemes to meet the increasing demands of human
needs has lead to land management.
58
CHAPTER-III
MATERIALS &METHODOLOGY
3.1 GENERAL
Land use reIers to man`s activities and various uses which are carried on land
and land cover refers to natural vegetation, water bodies, rock/soil, artificial
cover and others resulting due to land transformation. Although land use is
generally inferred based on the cover, yet both the terms land use and land cover
are closely related and interchangeable. The growing biotic pressure coupled
with increasing human demand exerts pressure on the available land resources
all over the country. Therefore, in order to optimally use the land, it is not only
necessary to have the information on the existing land use / land cover, but also
to monitor the dynamic land use resulting from the increasing demands arising
from the growing population. Land use data are needed in the analysis of
environmental processes and problems that must be understood if living
conditions and standards are to be improved or maintained at current levels. The
conventional ground methods of land use mapping are time consuming, labour
intensive and are relatively infrequent. The maps, thus, prepared become out of
date with the passage of time, particularly in a dynamic or rapidly changing
environment. With the advent of remote sensing technology, particularly
satellite remote sensing, techniques have been developed which have proved to
be of immense value in preparing land use/land cover maps and monitoring
changes at periodic intervals. In case of inaccessible region, this technique is
perhaps the only method of obtaining the required data on a cost and time-
effective basis.
59
3.1.1 Basic Concepts of Land Use
Clawson has given nine major ideas or concepts about land. These are:
1. Location or the relation of a specific parcel of land to the poles, the
equator, and the major oceans and landmasses. There is also relationship
between various tracts of land, as well as a political location.
2. Activity on the land, for what purpose this piece of land or tract is used.
3. Natural qualities of land, including its surface and subsurface
characteristics and its vegetative cover.
4. Improvements to and on the land. This is closely related to the activity.
5. Intensity of land use or amount of activity per unit area.
6. Land tenure, i.e who owns the land, who uses it.
7. Land prices, land market activity and credit as applied to land.
8. Interrelations between activities on the land and other economic and
social activities.
9. Interrelations in the use between different tracts of land.
3.1.2 Objectives of Classification
The main objectives of land use/ land cover classification system are
1. To develop a land use land cover map of study area.
2. To see the applicability of merged data of IRS-ID LISS-III satellite data
for delineating various land use/ land cover categories through digital
image analysis and processing (i.e. unsupervised classification) as well as
visual interpretation techniques.
3. To study land use land cover dynamics of study area.
60
3.2 LAND USE / LAND COVER CLASSIFICATION
In the context of developing a classification system, it is essential to consider
certain criteria and limitations of satellite data and study area particularly to
Indian conditions, as the classification system using satellite data should provide
a framework to satisfy the needs of the majority of users. In arriving at the
classification and nomenclature the following criteria are considered.
i) Land use/ land cover classification should be comprehensive,
scientifically sound, practical and applicable over large areas
ii) It should meet the needs of variety of users
iii) The classification should be flexible, which can be used at different scales
and at different levels of detail
iv) Land use/ land cover categories should be described with the minimal set
of classifiers
v) The classification should be amicable for use of multi-seasonal satellite
data
vi) To decide on an appropriate classification or data level within a
classification an arbitrary decision must be made. One must decide on
imagery scale or on the scale of representation of data. Satellite data on
scales of 1:250000, 1:50000, 1:25000, 1:10000 and 1:5000 will serve to
represent Level-I, Level-II, Level-III and Level-IV categories respectively
vii) The minimum interpretation accuracy and reliability in the identification
of land use/ land cover categories from satellite data should be at least 85-
95 percent based on the scale of mapping
viii) Due to certain limitations of satellite data, some of the similar categories
may be generalized, for example forest and wooded land, can be put under
main head 'Forest¨.
The comprehensive National Land use/ Land cover classification system as
given by NRSA is given in Table 3.1.
61
3.2.1 Objectives of Land Use / Land Cover Map
The main objectives of land use map are,
1) The land use map will be utilized as a basic database, which provides the
information for allocating new land use practices.
2) It will incorporate demographic, economic and environmental impact,
which have occurred in an area.
3) Not only will the information indicate where intensive development has
already taken place and where there is open land suitable for future
expansion, but it will also make it possible to determine special areas,
such as prime agricultural lands.
4) Land use/ land cover map will serve as a basis for monitoring land use
change.
5) The land use map will serve as a base in the integrated overall planning of
agricultural and industrial development of the region.
6) Landuse landcover classification system as devised by NRSC was used.
Table 3.1 NRSC Land Use / Land Cover Classification System
S. No Level ± I Level ± II
1 Built-up 1.1 Built-up
2 Agricultural Land 2.1 Crop Land
i)Kharif
ii)Rabi
iii)Kharif+Rabi
2.2 Fallow
2.3 Plantation
3 Forest 3.1Evergreen/Semi-evergreen
3.2 Deciduous (dry/moist)
3.3 Scrub/Shrub Land
62
3.4 Forest blank
3.5 Forest plantations
3.6 Mangrove
4 Wastelands 4.1 Salt affected land
4.2 Waterlogged land
4.3 Marshy/Swampyland
4.4 Gullied/Ravinous land
4.5 Land with or without scrub
4.6 Sandy area (coastal and desertic)
4.7BarrenRocky/Stony waste/Sheet rock
area
5 Water bodies 5.1 River/ Stream
5.2Lake/Reservoirs/ Tanks/Canals
6 Others 6.1Shifting cultivation
6.2Grassland/Grazing land
6.3Snow covered/Glacial area
Source: N.C. Gautam, 2004)
63
3.2.2 Methodology For Land Use/Land Cover Mapping
For analysis and interpretation two types of data are needed viz., Basic data and
Ground data.
1. Basic data includes:
(a) Data of IRS ± 1D LISS-III satellite imagery obtained from
NRSC, Balanagar.
(b) Toposheets Number 56K/10, 56K/11, 56K/14, 56K/15 is
obtained from Survey of India, Hyderabad.
(c) Ground truthing
(d) Area map on any scale to transfer details
(e) Reports and other literature of the study area
2. Ground data: Ground data is very much essential to verify and to increase
the accuracy of the interpreted classes and also to minimize the fieldwork.
3. Towards preparing land use/land cover map, IRS-1D, PAN + LISS III
Merged satellite imagery is used adopting visual interpretation techniques.
The Details of sensor specification of LISS III,IRS-1D is given in Table
3.2.Later, field checking was carried out to test accuracy of image
interpretation at selected sites and to clarify interpretation assumptions. In
addition, collateral data from other sources were also utilized in finalizing
the maps. Land use/land cover units derived from satellite data provides
information related to agriculture, forestry, wasteland, water resources,
built-up area, etc. The mapping is done using the Survey of India
toposheets as base to provide information on the various land use / land
cover categories up to level III classification. Flowchart showing the
Methodology adopted for land use/land cover mapping is given in Fig.
3.1.
64
For analysis and interpretation of satellite data, the study can be divided into
three parts:
A. Preliminary work
B. Field work
C. Post field work
A. Preliminary work:
i. Checking of limitation of satellite data
ii. Laying down the criteria for land use classification to be
adopted
iii. Fixing the size of mapping units, which depends upon
the scale
iv. Interpretation of different land use/land cover classes
v. Demarcation of doubtful areas
vi. Preparation of field land use/land cover map
B. Field work:
i. Type of ground data to be collected
ii. Selection of sample area for final classification
iii. Checking of doubtful areas
iv. Change in land use/ land cover due to wrong
identification, fresh development, nomenclature.
v. General verification
C. Post field work:
i. Reinterpretation or analysis or correction of doubtful
areas
ii. Transfer of details on base map
iii. Marginal information
iv. Preparation of final land use/land cover map
65
Table 3.2 Details of LISS III of IRS-1D
SI.No Parameter Specification
1. Spatial resolution (m) B2.B
3
B4 21.2 to 23.5
B5 63.6 to 70.5
2. Swath (Km) B2.B B4 127 to 141
B5 133 to 148
3 Spectral band (microns) B2 0.52 -.059
B3 0.62-0.68
B4 0.77-0.86
B5 1.55-1.70
4. Camera Square Wave B2 >40
Response (SWR) B3 >40
B4 >35
B5 >30
5. Quantisation (bits) 7
6. Signal to Noise Ratio >128
7. Saturation Radiance (Gain
(mw/cm -str-micron) B2 29 ±1. 5
B3 28 ± 1.5
B4 28 ± 1.5
B5 32.5+ 2.5
8. Integration time (ms) B2, and 3.6
B5 10.8
9. Data rate (Mbps) B2. and 35.7904
= B5 1.3906
66
67
3.3 PREPARATION OF SPATIAL DATA
Procedure for preparing the spatial data for the study area is Satellite data
processing using image processing software Generation of thematic maps such
aslanduse/landcover, Hydrogeomorphology,Geology,Structures,Groundwaterpot
ential, Groundwater infiltration and Groundwater table maps. Generation of
topographical maps showing physical characteristics of the study area. The
topographical maps extracted from SOI toposheet are drainage, base map, slope
and watershed map.
3.3.1 Acquisition and Processing of Topomaps and Satellite Data
Acquisition and processing of raw data for preparation of thematic maps
involves the following steps.
1. Acquisition of IRS-1D LISS-III and PAN satellite data of the year 2006 &
2011 from NRSC, Balanagar, Hyderabad and toposheets from Survey of
India, Hyderabad.
2. Geo-referencing of toposheets based on latitude and longitudinal values.
3. Edge matching of the toposheets and preparation of digital mosaic depicting
the entire study area.
4. Geo-coding and geo-referencing of LISS III and PAN digital data by
extracting the Ground Control Points (GCPs) from SOI toposheets.
5. Digital image enhancement and application of correction models for making
the digital data free from errors and distortions both radiometry and geometry
of the satellite data.
6. Fusion of PAN and LISS III for merged product preparation of a mosaic,
which shows the continuous imagery of the study area. This is FCC mode
and is used for visual interpretation.
7. Generation of thematic maps using ARC GIS software.
69
the display device. Based on these LUT` s an enhanced image is produced
4.1.1.3 Geo-coding and Geo-referencing
The following standard techniques have been adopted for Geo-referencing of
LISS III and PAN data covering the study area. ERDAS (Image Processing
Software) has been used for the work.
1:50,000 scale toposheets are scanned and raster file for study area is created.
These are geo-referenced based on the longitudinal & latitudinal co-ordinates.
After geo-referencing all the maps are edge-matched and a digital mosaic is
prepared which depicts the continuity of the study area.
Sufficient number of well-distributed ground control points is selected both on
the maps and corresponding imagery. Care is taken to satisfy the condition on
density of GCPs for image registration. Geo-referencing is carried out using
ERDAS image processing software. The geo-referenced image is further
mosaiced and then feature matching is carried out. At the end of this process the
digital data, which is free from all distortions, is available for digital image
enhancement, classification for Land use/land cover map preparation with the
help of Visual image analysis techniques.
With the aid of location, and condition of the various resources the sensor data
were collected. This information is then compiled generally in the forms of
hardcopy maps and tables or as computer files that can be merged with other
¨layers¨ oI inIormation in a geographic inIormation system (GIS). The role that
reference data play in the data analysis procedure and describe how the spatial
location of reference date observed in the field is often determined using global
positioning systems (GPS) methods.
70
Figure 3.2: IRS-ID LISS-III satellite imagery of 2006
71
Figure 3.3 IRS-1D LISS-III satellite imagery of 2011
72
3.3.4 Image Interpretation
Satellite imagery contains a detailed record of features as the ground at the time
of satellite overpass. An image interpreter systematically examines the images
for generating the information required by him. Other supporting materials such
as published maps and reports of various departments and field observation will
increase the accuracy of interpretation.
3.3.5 Elements of Image Characteristics
There are certain fundamental photo elements or image characteristics seen on
image which aid in the VIP of the imagery. They are tone/colour, size, shape,
texture, pattern, location, association, resolution and season. By understanding
the image characteristics of each of the thematic class, an image interpretation
key has been evolved. This will enable the image to identify different features
on satellite imagery. However, VIP, also, depends upon the season, scale,
spectral bands, spatial resolution, overall image contrast and quality of the data.
3.3.6 Visual Image Interpretation
The study of land use, land cover or land force from there has been a focus of
interest since the early days of aerial photography with the availability of new
remote sensing techniques using aircrafts and spacecraft as platforms with a
capacity for operating outside the visible part of the electromagnetic spectrums.
The limitation of photo interpretation has now been changed to broad spectrum
of image interpretation. Success in image interpretation varies with the training
and experience of the interpreter, the nature of the objects or phenomena being
interpreted and the quality of the image being utilized.
74
Tone/Colour:
Refers to relative shades of gray on Black and white images or colours on FCC
(False Colour Composite) images. Tone is directly related to reflectance of light
from terrain features. For example, water, which absorbs nearly all incident light
produces black tone.Whereas,a dry sand reflects a high percentage of light and
consequently produces very light tone on the image. Tone/colour is a
fundamental property of an image and conveys more information to an alert
interpreter than any other interpretation elements. Without tonal differences,
shape, patterns and texture of objects describe relative tonal values are light,
moderate, medium, dark etc.Absolute tonal values in terms of photo density
have no physical significance for interpretation purposes and practically never
used. The variation in gray tones can be transformed into corresponding colours
of various shades/lines on FCC colour imagery normally provide better thematic
information than single band black and white imagery by virtue of the more
spectral information it contains.
Texture:
Refers to the frequency of tonal changes in an image. Texture is produced by an
aggregate of unit features which may be too small to be clearly discerned
individually on the image. It is a product of their individual shape, size, pattern,
shadow and tone. By definition texture is dependent on the scale. As the scale
of the photograph is reduced the texture of a given object becomes progressively
liner and eventually disappears. Some of the terms often used to describe
relative texture values qualitatively are coarse, fine, medium, smooth, rough etc.
It is rather easier to distinguish various texture classes visually than digital
oriented techniques.
Pattern:
Relates to the spatial arrangement of the objects. The repetition of certain
general forms or relationships is characteristic of many objects, both natural and
75
manmade and gives objects a pattern which aids the image interpreter in
recognizing them.
Shape: Relates to the general form, configuration or outline of an individual
object. Shape is one of the most important single factor for recognizing objects
from images. For example, a railway line is usually readily distinguished from a
highway or a dirt road because its shape consists of long straight tangents and
gentle curves as opposed to the shape of a highway. The shape of an object
viewed from above may quite different from its profile view. However, the plan
view of object is more important and sometimes conclusive indication of their
structure, composition and function is possible.
Size:
The size of an object can be important tool for its identification. Objects can be
misinterpreted if their sizes are not evaluated properly. Although, the third
dimension, therefore height of the object is not readily measurable on satellite
images, but valuable information can be derived from the shadows of the
objects. Images with stercospic FRYHUDJH¶V. Such as SPOT and IRS-IC. It is
possible to measure the third dimension (height). For planned objects it is easier
to calculate the areal dimension on imagery, for example alluvial fan flood plain
etc.
Shadows: are of importance to photo-interpreters in two opposing respects (1)
The outline or shape of a shadow affords a profile view of objects, which aids
interpretation and (2) Objects within shadow reflect little light and are difficult
to discern on photographs, which hinders interpretation.
Site: Location of objects in relation to other features may be very helpful in
identification aspects, topography, geology, soils, vegetation etc are distinctive
factors that the interpreter should use when examining site.
76
Association: It is one of the most helpful clues in identification of land forms.
For example a flood plain is associated with several fluvial features such as
terraces, meanders, ox-bow lakes, abandoned channel etc. Similarly a sandy
plain in a desert is associated with various types of sand dunes.
ii)Terrain Elements
In addition to the image elements described above, the terrain elements listed
below are also highly useful for image interpretation. They are (i) Drainage
patterns (ii) Drainage texture (iii) topography/ landform (iv) Erosion status.
Drainage Patterns: The drainage patterns and texture seen on images are good
indicators of land form and bedrock type and also suggest soil characteristics
and site drainage conditions. Figure 4.2 illustrates various types of drainage
patterns that are commonly encountered and the possible interpretation one can
derive above the terrain, For example Dendritic drainage patterns the most
common drainage pattern found in nature. It develops under many terrain
conditions including homogenous unconsolidated materials, rocks with uniform
resistance to erosion such as horizontally bedded sedimentary unconsolidated
materials, rocks with uniform resistance to erosion such as horizontally bedded
sedimentary rocks and granitic gneissic terrains.
Drainage texture:
It is a combination of drainage or integration of different kinds of drainage
patterns. Texture can be termed as 'coarse textured and Iine drainage patterns¨.
Coarse textured patterns develop where the soils and rocks have good internal
drainage with little surface runoff. Fine textured patterns develop where the
soils and rocks have poor internal drainage and high surface run-off. Also fine
textured drainage patterns develop on soft, easily eroded rocks, such as, shale,
79
3.4.2 Drainage Map
The drainage map forms the base map for the preparation of other thematic
maps related to surface water pollution sensitivity from the toposheets of Survey
of India. All the rivers, tributaries and small stream channels shown on the
toposheets are extracted to prepare the drainage map. Care is taken that the
boundaries of rivers/ water bodies appearing on land use /land cover map or
base map are perfectly matched with those on the toposheet. All the drainage
lines are examined very closely and final drainage map is prepared.
Fractured pattern and other structural features control drainage pattern in hard
rocks. Slope gradient of area coupled with drainage density decides the
weathering profile. These two factors synthesized with rainfall of a given area
provides information on the ground water potential (weathering profile.
structural factors) and discharge of surface water along streams. Weathering
profile increases groundwater potential, slope/gradient together with runoff
controls the thickness of weathered zone. Major faults and lineaments
sometimes connects two are more watersheds (Drainage basin) and act as
conduits (Interconnecting channel ways). Flow of groundwater along these weak
zones is an established fact. A proper understanding of the major faults, their
influence of groundwater flow are to be understood from drainage system and its
controls. In the present study a drainage network map is prepared from the
toposheets which is further scanned, digitized using AutoCAD software and
then edited in ARC/INFO GIS platform to produce a digital output. The
drainage map of study area is shown in Fig 3.6
Irregular branching of channels in tree like fashion is observed which is a
characteristic of dendritic pattern of drainage which usually develops on
Homogenous massive rocks and flat lying strata. The dendritic pattern of
drainage showed third order basins.
80
3.4.3 Significance of drainage analysis
Drainage analysis includes the study of drainage pattern, drainage texture,
individual stream pattern and drainage anomalies.It provides clues to the
distribution and attitude of the underlying rock formations and geologic
structures, such as bedding planes, joints, fractures, faults, folds, etc.The basic
drainage patterns and their significance in geologic interpretation are
summarized. Drainage texture is also an important parameter for studying the
rock type distribution as throws light on the infiltration capacity of the
rocks.Higher the infiltration capacity of the rocks, coarser is the drainage texture
and vice versa.Drainage anomalies, i.e. the local deviation from the regional
drainage/stream pattern in the form of linear stream segments, actuate stream
courses, appearance/disappearance of braided and meandering streams, change
in drainage texture, each also indicate change in underlying rock types and
geologic structures.
3.4.4 Transportation map
Transport network plays an important role in the overall development of a
region/district. Accessibility by roads and rail is essential for social and
educational development besides economic development of a region. Two major
classes of transport network namely, the roads and railways were demarcated
from the toposheets and satellite imagery.
The roads are classified as national highways, state highways, major district
roads, other district roads and village roads. This information is mainly extracted
from the Survey of India topographical maps on 1:50,000 scale. The road
coverage network from the toposheets is updated with the latest satellite data to
extract additional information on the newly developed roads. The road network
map was used for the selection of shortest route for the transportation of waste
from the site of generation to final disposal site (Fig. 5.2). Transport network
81
interpreted using IRS-1D PAN data when compared with 1:50,000 scale SOI
map delineated about 80% of roads as depicted on map. Thus, the results of the
data conclude that, improved spatial resolution of the PAN offers scope to map
urban features on 1:50,000 scale.
The major roads passing through the study area include NH-202 towards
Warangal and various other roads connecting the settlements and landforms.
The road lengths of different types of roads like national highway, state
highway, district highway, metalled roads and unmetalled roads are also
calculated using the ARCGIS software.
3.4.5 Slope map
Land slope is one of the principal factors influencing watershed operations. The
slope of the land influences the intensity and extent of runoff. The velocity of
water flow varies as a square root of the vertical drop. Hence, if the land slope
increased four times, the velocity of water flowing on the slope is doubled. If the
velocity is doubled, the energy and consequently the erosive or cutting capacity
is increased four times. In this way the erosive capacity of runoff varies in direct
proportion with the slope of a land on which the runoff occurs. The degree of
slope sets limits on land use for annual crops, plantation and even on land
reclamation, depending on soil depth, nature of the soil, etc. A critical analysis
of the basin slope helps in modifying its effect on runoff by the use of transverse
channels or terraces or by bounding along contours.
Survey of India Toposheet maps on 1:50,000 scale are used for deriving the
information. Contour lines on topographic maps are particularly useful for
preparation of slope map. Closed space contours on the map reflect steepness
when compared to widely spaced contours. The different classes of slopes have
82
been categorized as per the guidelines suggested by All India Soil and Land Use
Survey (ALS & LUS). Slope categories are indicated in Table 3.3.The density of
contours on 1:50,000 scale Survey of India toposheets with 20m contour interval
have been used for preparing the slope map
Slope classes 1, 2, 3, 4, 6 and 7 are observed in the study area. The distance
between the successive contours is wide and only a few contours developed in
most part of the total study area (88%) indicating its near level nature, whereas
the distance between the successive contours is little wide in about 10%
indicating gently sloping and the distance between the successive contours is
short in about 2% and 0.35% indicating Moderate sloping and moderately steep
sloping respectively. Numerous contours are present in very few parts of the
total study area0.06% and 0.08% indicating steep sloping and Very gently
sloping. The slope map of the study area is shown in Fig 4.4
Slope map showing following slope categories is prepared on 1:50,000 scale
using table below.
Table :3.3 slope categories
Slope
category
Lower and upper limit
of percentage
Lower and contour
spacing
1 0 to 1% More than 4 Cms
2 More than 1% upto 3% More than 1.33 Cms and
upto 4 Cms
3 More than 3% upto 5% More than 0.8 Cms and
upto 1.33 Cms
83
4 More than 1% upto 10% More than 0.4 Cms and
upto 0.8 Cms
5 More than 10% upto
15%
More than 0.26 Cms and
upto 0.4 Cms
6 More than 15% upto
35%
More than 0.11 Cms and
upto 0.26 Cms
7 More than 35% 0.11 Cms and less
3.4.6 Land Use / Land Cover Map
Land use reIers to man`s activities and various uses, which are carried on land.
Land cover refers to natural vegetation, water bodies, rock/soil, artificial cover
and others resulting due to land transformation. Although land use is generally
inferred based on the cover, yet both the terms land use and land cover are
closely related and interchangeable.
Information on the rate and kind of change in the use of land resources is
essential to the proper planning, management and regulation of the use of such
resources. Knowledge about the existing land use and trends of change is
essential if the nation is to tackle the problems associated with the haphazard
and uncontrolled growth. A systematic framework is needed for updating the
land use and land cover maps that will be timely, relatively inexpensive and
appropriate for different needs at national and state level. The rapidly
developing technology of remote sensing offers an efficient and timely approach
to the mapping and collection of basic land use and land cover data over large
area. The satellite imageries are potentially more amenable to digital processing
because the remote sensor output can be obtained in digital format. Land use
data are needed in the analysis of environmental processes and problems that
84
must be understood if living conditions and standards are to be improved or
maintained at current levels.
3.4.6.1 Basic Concepts of Land Use
Clawson has given nine major ideas or concepts about land. These are:
Location or the relation of a specific parcel of land to the poles, the equator, and
the major oceans and landmasses. There is also relationship between various
tracts of land, as well as a political location. Activity on the land, for what
purpose this piece of land or tract is used. Natural qualities of land, including its
surface and subsurface characteristics and its vegetative cover. Improvements to
and on the land. This is closely related to the activity. Intensity of land use or
amount of activity per unit area. Land tenure, i.e who owns the land, who uses it.
Land prices, land market activity and credit as applied to land. Interrelations
between activities on the land and other economic and social activities.
Interrelations in the use between different tracts of land.
3.4.6.2 Objectives of Land Use / Land Cover Map
The main objectives of land use map are as follows:
The land use map will be utilized as a basic database, which provides the
information for allocating new land use practices. It will incorporate
demographic, economic and environmental impact, which have occurred in an
area. Not only will the information indicate where intensive development has
already taken place and where there is open land suitable for future expansion,
but it will also make it possible to determine special areas, such as prime
agricultural lands. Land use/ land cover map will serve as a basis for monitoring
land use change. The land use map will serve as a base in the integrated overall
planning of agricultural and industrial development of the region.
85
3.4.6.3 Application of Remote sensing techniques for land use/land cover
Remote sensing techniques provide reliable, accurate baseline information for
land use mapping. Generalized delineation of land use classification for large
area and spatial distribution of land use categories is possible by satellite
imagery as it provides synoptic view. Satellite Remote sensing techniques are
helpful to study changes at regular intervals. Rapid small scale land use mapping
for state and national series on 1:1,000,000 and 1:250,000 is possible by satellite
Remote sensing techniques. Satellite remote sensing provides data in different
bands of the electromagnetic spectrum. Also we can have the coverage of the
same area on different dates. We can combine data in different bands to produce
a color composite. Land use mapping both by visual interpretation and computer
aided interpretation is possible by satellite remote sensing technique.
3.4.6.4 Methodology for land use/land cover mapping
IRS-ID, LISS-III FCC`s on 1;50,000 scale have been used Ior preparation oI
LU/LC map. The map so prepared depicts the details of waterbodies,
grasslands, forest. agricultural and built up land. Area statistics were generated
from the maps so prepared for all the LU/LC categories
Present land use/land cover map showing the spatial distribution of various
categories and their areal extent is vital for the present study. The spatial
distributions of various land uses are interpreted based on data of IRS-1D LISS
III data. The different land use. land cover classes existing in the area over space
and time are briefly discussed here in their dimension. The LU/LC map of the
study area is shown in Figure 4.5 ,Figure 4.6 and their distribution in Table 4.1
along with Pie chart showing LU/LC categories of study area in Fig 4.7
86
CHAPTER-IV
RESULTS & DISCUSSION
4.1 GENERAL
Land is used to meet a multiplicity and variety of human needs and to serve
numerous, diverse purposes. When the users of land decide to employ its
resources towards different purposes, land use change occurs producing both
desirable and undesirable impacts. The analysis of land use change is essentially
the analysis of the relationship between people and land. Why, when, how, and
where does land use change happen? To provide answers to these closely
interrelated questions, theories have been advanced and models have been built
in the last 200 years. This contribution attempted to provide a panorama of
theoretical and modeling approaches to the study of land use change as well as
to examine broadly how well they reflect the drivers, processes and implications
of this change.
This project work demonstrates the ability of GIS and Remote Sensing in
capturing spatial-temporal data. Attempt was made to capture as accurate as
possible on 1:50,000 scale, Classifying land use land cover change detection
upto II
nd
±Level and Developed the common legend for land use land cover
mapping. The results of the above case study indicates that there has been
change in land use/land cover. Spatial information on the pattern of LU/LC at
large scale is great importance for proper planning and management. Recent
advances in satellite sensor spectral, spatial and radiometric capabilities have
strengthened the operational scenario of remote sensed based land use / land
cover change information at village and mandal level which is important for
monitoring environmental changes.
87
Figure 4.1 : Base Map
88
Figure 4.2: Drainage Map
89
Figure 4.3: Transportation Map

90
Figure 4.4: Slope Map
91
Figure 4.5: LU/LC 2006
92
Figure 4.6 : LU/LC 2011 1
93
4.2 CHANGE DETECTION RESULT AND ANALYSIS:
The Change Detection of Land use/ Land cover of the study area (2006 ± 2011)
and its areal extent were given in Table 4.1. The total study area is 16689
Hectares. The most salient change in land use has been the quick augment in
forest area from 59% in 2006 to 46% in 2011 of the total area. The
built up land which was 2% in 2006 increased to 12% by 2011.The water bodies
which covered 18 % in 2006 is reduced to 15% in 2011.The agricultural land
which was 16% in 2006 were reduced to 13% in 2011.Grassland which were
covering 5% in 2006 were found to be increased to 14% in 2011.
The comparative study of LU/LC of 2006 and 2011 showed a drastic decline in
forest area by 13% along with a increase in built up land by 10%.The water
bodies and agricultural land showed a decline of 3% each. An increase by 9%
was observed in Grassland and gazing area growth.
Table 4.1: Over all Change detection (2006-2011)
LEGEND 2006 2011
PERCENTAGE
AREA
(Ha) PERCENTAGE
AREA
(Ha)
WATER BODIES 18% 3004.02 2503.35 15%
GRASSLAND 5% 834.45 2336.46 14%
FOREST AREA 59% 9846.81 7676.94 46%
AGRICULTURAL
LAND 16% 2670 2169.57 13%
BUILT UP LAND 2% 333.78 2002.68 12%
TOTAL 100% 16689 16689 100%
94
Figure 4.7: Pie chart ±Change detection (2006-2011)
Lu/Lc classification of 2006 and 2011 for waterbodies,Grasslands,Forest
area,Agricultural land and built up area was studied.The pie chat shows there is
a decrease in waterbodies, Forest area,Agricultural land and built up area and
increase in Grassland and Built up area.

PIE CHART SHOWINGTHE DIFFERENCE BETWEEN 2006 &
2011
0
2000
4000
6000
8000
10000
12000
LEGEND
A
R
E
A

I
N
H
E
C
T
A
R
S
Series1 3004.02 834.45 9846.81 2670 333.78
Series2 2503.35 2336.46 7676.94 2169.57 2002.68
Water bodies-
Reservoirs/Tan
Natural
Grassland &
Forest area
Agricultural
land/Crop
Built up land
95
A=Waterbodies
B= Grasslands
C=Forest Area
D= Agricultural area
E=Built-up land
Table 4.2 : Land Use Land cover of Ghatkesar Mandal in Hectares - 2006
S.No Villages A B C D E
Total
Ha
Ha Ha Ha Ha Ha
1 ANKUSHAPUR 29 11 36 19 41 137
2 ANNOJIGUDA 74 7 986 9 5 1081
3 AUSHAPUR 37 6 739 15 3 799
4 BANKNALGUDA 43 7 766 16 4 836
5 CHENGICHERLA 239 21 189 49 19 516
6 CHERRLAPALLI 381 60 362 127 27 957
7 EDULABAD 527 123 521 224 33 1427
8 GHATKESAR 59 7 943 8 7 1023
9 GODAMKUNTA 294 36 280 57 30 697
10 GONAPURAM 451 65 432 134 27 1109
11 HAJJALGUDA 8 186 55 5 17 271
12 KONDAPURAM 11 13 107 320 10 461
13 KORREMULA 2 143 48 2 16 211
14 MADHARAM 27 3 536 11 3 579
15 MARPALLIGUDA 524 73 477 182 29 1285
16 MEDIPALLY 95 9 1142 70 9 1324
17 NARAPALLY 108 10 1172 91 9 1390
18 NEMAGMALA 29 4 703 13 2 751
19 POCHARAM 24 23 125 519 20 711
20 RAMPALLY 21 15 120 439 13 609
21 YEMNAPET 21 14 107 360 11 514
3004 834 9847 2670 334 16689
96
A=Waterbodies
B= Grasslands
C=Forest Area
D= Agricultural area
E=Built-up land
Table 4.3 : Land Use Land cover of Ghatkesar Mandal in Percentage - 2006
S.No Village A B C D E
% % % % %
1 ANKUSHAPUR 0.176 0.067 0.216 0.114 0.246
2 ANNOJIGUDA 0.442 0.042 5.91 0.054 0.032
3 AUSHAPUR 0.219 0.036 4.43 0.087 0.018
4 BANKNALGUDA 0.259 0.039 4.59 0.097 0.023
5 CHENGICHERLA 1.432 0.124 1.131 0.291 0.112
6 CHERRLAPALLI 2.283 0.362 2.17 0.762 0.159
7 EDULABAD 3.157 0.736 3.12 1.34 0.196
8 GHATKESAR 0.352 0.041 5.65 0.048 0.039
9 GODAMKUNTA 1.763 0.214 1.68 0.342 0.178
10 GONAPURAM 2.702 0.389 2.59 0.804 0.161
11 HAJJALGUDA 0.045 1.112 0.332 0.032 0.104
12 KONDAPURAM 0.064 0.079 0.64 1.92 0.061
13 KORREMULA 0.014 0.856 0.29 0.009 0.096
14 MADHARAM 0.163 0.016 3.21 0.067 0.015
15 MARPALLIGUDA 3.142 0.436 2.86 1.09 0.174
16 MEDIPALLY 0.568 0.056 6.84 0.421 0.051
17 NARAPALLY 0.649 0.058 7.021 0.544 0.055
18 NEMAGMALA 0.176 0.024 4.21 0.078 0.011
19 POCHARAM 0.143 0.136 0.75 3.11 0.122
20 RAMPALLY 0.127 0.091 0.72 2.63 0.079
21 YEMNAPET 0.124 0.086 0.64 2.16 0.068
18 5 59 16 2
97
A=Waterbodies
B= Grasslands
C=Forest Area
D= Agricultural area
E=Built-up land
Table 4 .4: Land Use Land cover of Ghatkesar Mandal in Hectares - 2011
S.No Village A B C D E
Total
Ha
Ha Ha Ha Ha Ha
1 ANKUSHAPUR 4.00 2.50 250.3 2.00 300 559
2 ANNOJIGUDA 62.91 50.40 722.9 18.69 7.34 862
3 AUSHAPUR 83.44 297.0 1.33 3.00 3.50 388
4 BANKNALGUDA 46.72 35.21 625.6 191.42 10.5 909
5 CHENGICHERLA 11.68 9.51 196.9 399.86 272 890
6 CHERRLAPALLI 252.00 102.1 228.6 75.43 70.2 728
7 EDULABAD 430.57 236.9 405.5 233.64 203 1510
8 GHATKESAR 15.02 253.6 263.6 136.51 118 787
9 GODAMKUNTA 246.99 11.34 213.6 8.84 40.3 521
10 GONAPURAM 335.44 140.1 272.0 113.15 71.5 932
11 HAJJALGUDA 200.26 387.1 3.67 6.34 5.17 602
12 KONDAPURAM 28.37 16.85 549.9 13.68 8.67 617
13 KORREMULA 183.57 370.3 2.00 4.83 3.67 564
14 MADHARAM 53.40 36.38 679.7 17.02 12.3 798
15 MARPALLIGUDA 357.14 235.3 328.7 204.27 111 1237
16 MEDIPALLY 86.78 68.59 919.8 54.07 31.8 1161
17 NARAPALLY 16.68 13.01 535.2 11.01 6.67 582
18 NEMAGMALA 70.09 50.73 807.5 37.71 16.8 982
19 POCHARAM 8.34 5.84 143.5 300.40 166 625
20 RAMPALLY 5.00 4.50 323.7 3.83 357 694
21 YEMNAPET 10.01 8.67 186.9 333.78 193 732
2508 2336 7661 2169 2012 16689
98
A=Waterbodies
B= Grasslands
C=Forest Area
D= Agricultural area
E=Built-up land
Table 4.5: Land Use Land cover of Ghatkesar Mandal in Percentage - 2011
S.No Village Names A B C D E
% % % % %
1 ANKUSHAPUR 0.02 0.01 1.5 0.01 1.79
2 ANNOJIGUDA 0.37 0.30 4.33 0.11 0.04
3 AUSHAPUR 0.5 1.78 0.00 0.01 0.02
4 BANKNALGUDA 0.28 0.21 3.74 1.14 0.06
5 CHENGICHERLA 0.07 0.05 1.18 2.39 1.63
6 CHERRLAPALLI 1.51 0.61 1.37 0.45 0.42
7 EDULABAD 2.58 1.42 2.43 1.4 1.22
8 GHATKESAR 0.09 1.52 1.58 0.81 0.70
9 GODAMKUNTA 1.48 0.06 1.28 0.05 0.24
10 GONAPURAM 2.01 0.84 1.63 0.67 0.42
11 HAJJALGUDA 1.2 2.32 0.02 0.03 0.03
12 KONDAPURAM 0.17 0.10 3.29 0.08 0.05
13 KORREMULA 1.1 2.21 0.01 0.02 0.02
14 MADHARAM 0.32 0.21 4.07 0.10 0.07
15 MARPALLIGUDA 2.14 1.41 1.97 1.22 0.66
16 MEDIPALLY 0.52 0.41 5.51 0.32 0.19
17 NARAPALLY 0.1 0.07 3.20 0.06 0.04
18 NEMAGMALA 0.42 0.30 4.83 0.22 0.10
19 POCHARAM 0.05 0.03 0.86 1.8 1
20 RAMPALLY 0.03 0.02 1.94 0.02 2.14
21 YEMNAPET 0.06 0.05 1.12 2 1.16
15 14 46 13 12
99
A=Waterbodies
B= Grasslands
C=Forest Area
D= Agricultural area
E=Built-up land
Table 4.6:Change Detection (2006-2011) comparison
S.No Village A B C D E
1 ANKUSHAPUR -0.152 -0.052 1.284 -0.102 1.553
2 ANNOJIGUDA -0.065 0.26 -1.57 0.058 0.012
3 AUSHAPUR 0.281 1.744 -4.42 -0.069 0.003
4 BANKNALGUDA 0.021 0.172 -0.84 1.05 0.04
5 CHENGICHERLA -1.362 -0.067 0.049 2.105 1.518
6 CHERRLAPALLI -0.773 0.25 -0.8 -0.31 0.262
7 EDULABAD -0.577 0.684 -0.69 0.06 1.024
8 GHATKESAR -0.262 1.479 -4.07 0.77 0.669
9 GODAMKUNTA -0.283 -0.146 -0.4 -0.289 0.064
10 GONAPURAM -0.692 0.451 -0.96 -0.126 0.268
11 HAJJALGUDA 1.155 1.208 -0.31 0.006 -0.07
12 KONDAPURAM 0.106 0.022 2.655 -1.838 -0.00
13 KORREMULA 1.086 1.363 -0.27 0.02 -0.07
14 MADHARAM 0.157 0.202 0.863 0.035 0.059
15 MARPALLIGUDA -1.002 0.974 -0.89 0.134 0.495
16 MEDIPALLY -0.048 0.355 -1.32 -0.097 0.14
17 NARAPALLY -0.549 0.02 -3.81 -0.478 -0.01
18 NEMAGMALA 0.244 0.28 0.629 0.148 0.09
19 POCHARAM -0.093 -0.101 0.11 -1.31 0.878
20 RAMPALLY -0.097 -0.064 1.22 -2.607 2.064
21 YEMNAPET -0.064 -0.034 0.48 -0.16 1.092
-3 9 -13 -3 10
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4.3 GHATKESAR MANDAL LU/LC OF2006 ANALYSIS
Water Bodies-Reservoir/Tanks-Dry & Wet:
Water bodies constituted 18% of total geographical area spreading over 3004.02
Hectares.
The 6 villages which showed richness in water bodies are Adilabad (3.15 7%),
Marpalliguda (3.142 %), Gonapuram (2.702%), Cherrlapalli (2.283%),
Godamkunta (1.763%) and Chengicherla (1.432%)
Natural Grassland & Grazing Land:
Grassland constituted 5% of total geographical area spreading over 834.45
Hectares.
The 2 villages which showed richness in grasslands are Hajjalguda (0.045%)
and Korremula (0.856%).
Forest Area:
Forest constituted 59% of total geographical area spreading over 9846.81
Hectares.
The 8 villages which showed richness in Forest are Narapally (7.021%),
Medipally (6.84%), Annojiguda (5.91%), Ghatkesar (5.65%), Banknalguda
(4.59%), Aushapur (4.43%), Nemagmala (4.21%) and Madharam (3.21%).
Agricultural Land /Crop Land /Double Crop Area:
Agricultural area constitutes 16% of total geographical area spreading over 2670
Hectares.
The 4 villages which showed richness in Agriculture are Pocharam (3.11%),
Rampally (2.63%), Yemnapet (2.16%) and Kondapuram (1.92).
101
Built Up Land:
The Built up land constitutes 2% of total geographical area spreading over
333.78 Hectares.
The village which showed richness in Built-up is Ankushapur (0.246%).
4.4 GHATKESAR MANDAL LU/LC OF 2011: ANALYSIS
Water Bodies-Reservoir/Tanks-Dry & Wet:
Water bodies constituted 15% of total geographical area spreading over 2503.35
Hectares.
The 5 villages which showed richness in water bodies are Adilabad (2.549%),
Marpalliguda (2.14%), Gonapuram (2.01%), Cherrlapalli (1.51%) and
Godamkunta (1.48%).
Natural Grassland & Grazing Land:
Grassland constituted 14% of total geographical area spreading over 2336.46
Hectares.
The 4 villages which showed richness in grasslands are Hajjalguda (2.32%),
Korremula (2.219%), Aushapur (1.78%), and Ghatkesar (1.52%).
Forest Area:
Forest constituted 46% of total geographical area spreading over 9846.81
Hectares.
The 7 villages which showed richness in Forest are Medipally (5.512%),
Nemagmala (4.868%), Annojiguda (4.332%), Madharam (4.063%),
Banknalguda (3.794%), Kondapuram (3.322%) and Narapally (3.207%).
102
Agricultural Land /Crop Land /Double Crop Area:
Agricultural area constitutes 13% of total geographical area spreading over
2169.57 Hectares.
The 3 villages which showed richness in Agriculture are Chengicherla (2.396%),
Yemnapet (2%) and Pocharam (1.8%).
Built Up Land:
The Built up land constitutes 12% of total geographical area spreading over
2002.68 Hectares.
The 2 villages which showed richness in Built-up are Rampally (2.1%) and
Ankushapur (1.8%).
4.5 CHANGE DETECTION ANALYSIS (2006-2011):
Change detection in 21 villages under Ghatkesar Mandal (2006-2011)
(1) EDULABAD
There is an increase in Built up land (1.024%), grassland (0.684%) and
agriculture land (0.06%) but decline in forest (-0.69%) and waterbodies (-
0.577%).
(2) ANNOJIGUDA
Increase in grassland (0.26%), agriculture (0.058%) and built up (0.012%) but
decrease in forest (-1.578%) and waterbodies (-0.065%).
(3) ANKUSHAPUR
Increased in Built up land (1.553%) and forest (1.284%), but Decease in
waterbodies (-0.152%), agriculture (-0.102%), and grassland (-0.052%).
(4) AUSHAPUR
Increase in grassland (1.744%), waterbodies (0.281%) and built up (0.003%) but
decrease in agriculture (-0.069%) and forest (-4.422).
103
(5) BANKNALGUDA
Increased in Agriculture (1.05%), grassland (0.172%), waterbodies (0.021%)
and built up (0.04%) but decease in forest (-0.841%).
(6) CHERRLAPALLI
Increased in Built up (0.262%), grassland (0.25%) and decrease in forest (-
0.8%), waterbodies (-0.773%) and agriculture (-0.31%).
(7) CHENGICHERLA
Increased in Agriculture (2.105%) and built up (1.518%) and forest (0.049%)
but decrease in waterbodies (-1.362%) and grassland (-0.067%).
(8) GHATKESAR
Increased in Grassland (1.479%), agriculture (0.77%) and built up (0.669%) but
decrease in forest (-4.07%) and waterbodies (-0.262%).
(9) GONAPURAM
Increased in Grassland (0.451%) and built up (0.268%) but decease in forest (-
0.96%), waterbodies (-0.692%) and agriculture (-0.126%).
(10) GODAMKUNTA
Increase in Built up (0.064%) but decrease in agriculture (-0.289%), waterbodies
(-0.283%), forest (-0.4%) and grassland (-0.146%).
(11) HAJJALGUDA
Increased in Waterbodies (1.155%) and grassland (1.208%) and agriculture
(0.006%) but decease in forest (-0.31%) and built-up (-0.073%).
(12) KONDAPURAM
Increase in forest (2.655%), waterbodies (0.106%) and Grassland (0.022%), but
decrease in agriculture (-1.838%) and built up(-0.009%).
(13) KORREMULA
Increase in waterbodies (1.086%), grassland (1.363%) and agriculture (0.02%),
but decrease in forest (-0.278%) and built up (-0.074%).
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(14) MADHARAM
Increase in forest (0.863%), grassland (0.202%) waterbodies (0.157%), built
up(0.059%) and agriculture (0.035%).
(15) MARPALLIGUDA
Increase in grassland (0.974%), built up(0.495%) and agriculture(0.134%) but
decrease in waterbodies (-1.002%) and forest (-0.89%).
(16) MEDIPALLY
Increase in grassland (0.355%) and built up (0.14%) but decrease in forest (-
1.328%), agriculture (-0.097%) and waterbodies (-0.048%).
(17) NARAPALLY
Increase in grassland (0.02%) but decease in Forest (-3.814%), Waterbodies (-
0.549%), Agriculture (-0.478%) and Built Up (-0.015%).
(18) NEMAGMALA
Increase in Forest (0.629%), Grassland (0.28%), Waterbodies (0.244%),
Agriculture (0.148%) and Built Up (0.09%).
(19) POCHARAM
Increase in Built Up (0.878%), Forest (0.11%) and decease in Agriculture (-
1.31%), Grassland (-0.101%) and Water (-0.093%).
(20) RAMPALLY
Increase in Built Up (2.064%), Forest (1.22%) but decrease in Agriculture (-
2.607%), Waterbodies (-0.097%) and Grassland (-0.064%)
(21) YEMNAPET
Increase in Built-up (1.092%), Forest (0.48%) but decrease in Agriculture
(-0.16%),Water(-0.064%) and Grassland(-0.034%).
105
Chapter V
CONCLUSION AND RECOMMENDATIONS
5.1 CONCLUSION:
Land use or land cover always involves specific areas on surface of earth and is
therefore a geographical concept. A clear understanding of land use land cover
within any geographical boundaries can be obtained only by detail survey and
mapping of such land. Land use or cover is also a dynamic concept as its
properties or nature within any area may change over time and monitoring these
changes may require periodic surveys. Thus, surveying, mapping and
monitoring of land cover is essential for understanding, planning and managing
the land use and its environment to obtain maximum benefit for the human
society in a sustainable manner.
Land use is carried out in many different ways. The broadest categories include
agriculture, forestry, mining, highways, industrial complexes, townships,
villages, recreation grounds, etc. Application of surveying, mapping and
monitoring techniques generates such information that can be used for sound
management of forest resources.
The major common Land Use categories such as water bodies, grasslands,
forest area, and agricultural land, built up land are identified and mapped from
the SOI topographic sheets. The land use of the year 2006 and 2011was mapped,
classified and calculated accurately from the toposheets, it was compared with
those prepared from the satellite imageries (IRS 1C LISS III), and IRS Pan
merged data. The IRS 1C LISS III data used as the source for the land use/land
cover mapping. The registration and digitization of the watershed was done
using Arc GIS 9.1 Software to create land use coverage. Five land use categories
i.e. water bodies, grasslands, forest area, and agricultural land, built up land. The
106
comparative study of LU/LC of 2006 and 2011 showed a drastic decline in
forest area by 13% along with a increase in built up land by 10%.The water
bodies and agricultural land showed a decline of 3% each. An increase by 9%
was observed in Grassland and gazing area growth. Built-up land is an area of
human habitation, which has a cover of buildings and network of transport, and
other civic amenities. The Built-up land increased to 10% due to Singapore
townships, Special economic zones, Jawaharlal Nehru ring road and increase in
demand for land. Agricultural land primarily used for farming and for
production of food, oil seed and other commercial and horticultural crops comes
under this category. This area is further divided into different categories such as
rabi crop, Kharif crop, double crop and fallow. There was a decline by 3% in
agricultural land in Ghatkesar Mandal. The forest area declined by
13%.Wastelands are those lands, which are currently unutilized or underutilized
and can be brought under vegetation cover/ cultivation with reasonable efforts.
Wastelands are very negligible as they are converted to Built-up land. Water
bodies include village ponds, lakes, reservoirs and manmade tanks. The water
bodies showed a decline of 3%.The grassland showed an increase by 9% which
could be due to demand for forage cops and fodder for animals. The livestock
includes VKHHS¶V, goats, donkeys, pigs, dogs, rabbits and poultry.
Aushapur village showed increase in grassland by 1.744%, but there
decrease in forest area by -4.422.Chengicherla village showed increase in
agriculture by 2.105% but waterbodies declined by -1.362%Ghatkesar showed
increased in grassland by 1.479% but there was decrease in forest area by -
4.07%.Kondapuram village was found to be rich in forest area by 2.655% but
there was decrease in agricultural land by -1.838%.Rampally showed increased
in built up land by 2.064%, but agricultural land declined by -2.607%. Although
Inner ring road is in progress, not much of change was detected since the IRR
project is in inception stages. Most of the development is expected to take place
107
in East direction due to HMDA IRR development and Bypass road development
which is planned in Aushapur.
5.2 Recommendations:
1) To prevent soil erosion and flooding Riparian forest along Erimulli Vagu
River is necessary which will act as buffers.
2) Promoting Agro-forestry in villages might protect and enhance crop or
livestock production systems and can increase income.
3) Alley cropping systems provide a way to lower risk by diversifying
production. In alley cropping an agricultural crop is grown simultaneously with
a long-term tree crop to provide annual income while the tree crop matures.
When nut-bearing trees are used they can provide an intermediate product for
sale. In addition to improving annual cash flow, these systems also protect
annual crops, reduce soil erosion, and provide wildlife habitat.
4) Promoting Green- belts along road margins.
5) Residential colony plantations.
6) Block plantations in waste lands, institutional lands and silvi pasture.
7)Watershed management though check dams, Farm ponds, sunken ponds,
Gully plugging, contour trenching ,bench terracing, afforestration, horticulture
development, fodder cultivation and pasture development.
8) Growing short duration legume crops like green gram, cowpea can help
mitigate drought.
9) Growing alternative crops like perennial gasses for live stock farming.
10) Implementing stringent laws to discourage formation of built up land.
11) The grasslands are the most neglected, abused and least protected
ecosystems in India.
They remain unprotected unless they are notified as Protected Areas under the
Wild Life (Protection) Act, 1972 or notified as Protected or Reserve Forest
108
under the Indian Forest Act, 1927. To plan and implement, with the involvement
and consent of state governments and local communities, landscape level
strategies for grassland management.
12) The practice of stall-feeding should be encouraged among livestock owners
in order to prevent over grazing consequent depletion of available forest fodder
resources.
13) To develop a policy of regulated grazing that is managed on scientific
principles so that desirable vegetation development could be ensured.
109
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