GEOMATICS ANALYSIS ON LAND USE LAND COVER CLASSIFICATION SYSTEM IN PRECAMBRIAN TERRAIN OF CHITRADURGA DISTRICT KARNATAKA, INDIA

International Journal of Civil Engineering and Technology (IJCIET), ISSN 0976 – 6308 (Print),

ISSN 0976 – 6316(Online), Volume 6, Issue 2, February (2015), pp. 46-60 © IAEME

46

GEOMATICS ANALYSIS ON LAND USE LAND COVER

CLASSIFICATION SYSTEM IN PRECAMBRIAN TERRAIN

OF CHITRADURGA DISTRICT KARNATAKA, INDIA

Manjunatha M.C1, Basavarajappa H.T

2, Jeevan L

3

1,2,3

Department of Studies in Earth Science, Centre for Advanced Studies in Precambrian Geology,

University of Mysore, Manasagangothri, Mysuru-570 006, Karnataka, India

ABSTRACT

Earth's land use/land cover (LC/LU) classification provides information particularly on

natural resources, mapping and monitoring. There is a significant change on LC/LU across the globe

due to the climatic changes, rapid increase in population and over demand of the growing economic

minerals. The present aim is to map, implement and monitor the land use/land cover classification

using high-tech tools of geomatics in database generation, analyses and information extraction. Land

use/land cover maps are prepared using satellite images in conjunction with collateral data like

Survey of India (SoI) toposheets of 1:50,000 scale. Remote Sensing (RS) satellite data with its

synoptic view and multispectral data provides essential information in proper planning of LU/LC

conditions of larger areas. An attempt have been made to delineate the level-1, level-2 and level-3

LU/LC classification system through NRSC guidelines (1995) using both digital and visual image

interpretation techniques by Geographical Information Systems (GIS) software’s with limited

Ground Truth Check (GTC). More accurate classification is observed in case of digital technique as

compared to that of visual technique in terms of area statistics. The final results highlight the

potentiality of geomatics in classification of LU/LC patterns around Chitradurga district, Karnataka,

in natural resource mapping and its management.

Keywords: LU/LC Classification; Visual & Digital interpretation; Geomatics; Chitradurga.

1. INTRODUCTION

Land is a non-renewable resource and mapping of LU/LC is essential for planning and

development of land and water resources in a region of engineering projects under progress. Land-

use determined by environmental factors such as soil characteristics, climate, topography, vegetation,

basic human forces that motivate production and its responses to environmental changes. (Dinakar

INTERNATIONAL JOURNAL OF CIVIL ENGINEERING AND

TECHNOLOGY (IJCIET)

ISSN 0976 – 6308 (Print)

ISSN 0976 – 6316(Online)

Volume 6, Issue 2, February (2015), pp. 46-60

© IAEME: www.iaeme.com/Ijciet.asp

Journal Impact Factor (2015): 9.1215 (Calculated by GISI)

www.jifactor.com

IJCIET

©IAEME



47

S., 2005; Dinakar and Basavarajappa., 2005). Different classes of vegetation tend to slow down and

intercept the surface flow of run-off water leading to maximize infiltration. Proper management and

development of these lands should be initiated to increase the land productivity, restoration of soil

degradation, reclamation of wastelands, increase in environmental qualities and to meet the needs of

rapidly growing population of the country. Remote Sensing and GIS data provides better impact on

land resource management, monitoring, mapping and change detection at varying spatial ranges

(Anji Reddy., 2000; Singh et al., 2010). In modern times, satellite based remote sensing technology

has been developed, which are of immense value for preparing LU/LC map and their monitoring at

regular periodic intervals of time (Kumar et al., 2004). Land use systems need thorough systematic

monitoring and management to maintain food security, to minimize deforestation, conservation of

biological diversity and protection of natural resources. The land use/land cover classification

scheme of 1:50,000 scale is divided into Level-1: 6 classes; Level-2: 20 classes and Level-3: 3

classes (NRSA, 2007; Basavarajappa et al., 2013, 2014c).

2. STUDY AREA

The study area lies in between 13°34' to 15°02' N latitude and 76°00' to 77°01' E longitude

with a total areal extent of 8,448 Km2 (Fig.1) (Basavarajappa et al., 2014a). It include six taluks

namely Challakere, Chitradurga, Hiriyur, Holalkere, Hosadurga and Molakalmuru with general

ground elevation of 732 m above MSL. The study area experiences a hot, seasonally dry, tropical

savannah climate with average annual rainfall recorded are 631 mm (2013). Temperature ranges

from 170C to 41

0C and fall up to 12

0C during winter season. The main food crops grown are as Rice,

Ragi, Jowar and Maize; Pulses & seed crops area as Red gram, Horse gram, Green gram, Bengal

gram and Tur. The commercial crops such as Sugarcane, Cotton and Tobacco are also grown. Palms,

Palmyra, Conifer, Bamboo and other tress are noticed in parts of Holalkere and Neerthadi reserved

forest ranges of Chitradurga district.



48

3. METHODS & MATERIALS

3.1 Methodology

LU/LC maps are prepared using satellite image in conjunction with collateral data like SoI

topomaps on 1:50,000 scale by considering permanent features such as major roads, drainages,

power-lines, railways, settlements, co-ordinates, forests and village boundaries. Visual interpretation

of IRS-1D PAN+LISS-III FCC of Band 3,2,1 on 1:50,000 scale (Fig.3) is carried out and updated on

Google Earth Image (Fig.4) in delineating the various LU/LC categories. The satellite data of two

seasons are acquired (Rabi in Dec-2005 and Kharif in Oct-2006) to estimate the spatial distribution

and temporal variability of different LU/LC pattern. These classifications are carried out based on

the standard schemes developed by National Remote Sensing Agency (NRSA, 1995).

3.2 Materials used

a. Topomaps: 57A/12; 57B/3, 4, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16; 57C/1, 2, 5, 6, 9, 10, 13

(Fig.2). Source: Survey of India (SoI) of 1:50,000 scale.

b. Satellite Data: IRS-1D LISS-III of 23.5m Resolution and PAN of 5.8m (March & Nov-2005 &

06). Google Earth Image of >5m resolution (Date of acquisition: March-2007)

Source: National Remote Sensing Agency (NRSA), Hyderabad; Google Earth software.

c. GIS software’s: Arc Info v3.2, Erdas Imagine v2011 and Arc GIS v10.

d. GPS: Garmin 12 is used to check conditions of the land use/land cover patterns during field visits.



49

4. CLASSIFICATION ANALYSIS USING GEOMATICS

Satellite Remote Sensing has been extensively utilized for Satellite data acquisition at

periodic intervals to monitor the land resources and to evaluate the land use/ land cover classification

and its impact on environment (Dinakar and Basavarajappa., 2005; Basavarajappa et al., 2014c).

Geomatics are used as an advent high-tech tool for LC/LU classification system to analyze and to

maintain the natural resources (NRSA, 1995). Information on land use/land cover is of utmost

importance in hydro-geological investigation as the groundwater regime of a region is influenced by

the type of land use/land cover patterns. Hence the satellite based data is very much useful in

preparing the precise land use/land cover maps in a very short time period using geomatics as

compared to that of conventional/traditional methods. Different LU/LC are delineated and classified

based on the key elements of image characteristics like tone, texture, shape, shadow, pattern,

association, background etc. Level-1 classification consists of 6 major categories such as agricultural

land, built-up land, forest, wastelands, water bodies and others (Fig.5; Table.1) are further divided

into sub-categories of level-2 (Fig.6; Table.2); keeping the area under investigation. Level-3

classification has been carried out in detail on agricultural and forest lands to study the cropping

pattern (Fig.7; Table.3). Digital interpretation and post classification comparison techniques are

adopted to observe the changes among various land uses over a period (Rubee and Thie, 1978;

Likens and Maw, 1982; Priyakant et al., 2001).

Table.1 Land use/land cover classification system (NRSA, 1995) LEVEL – 1 LEVEL – 2 LEVEL – 3

1 Built – up land 1.1 Towns/Cities

1.2 Villages

2 Agricultural Land

2.1 Crop land

2.1.1 Kharif

2.1.2 Tank irrigated kharif

2.1.3 Rabi

2.1.4 Kharif + Rabi (Double cropped)

2.2 Fallow

2.3 Plantation

3 Forest

3.1 Evergreen/ Semi evergreen 3.1.1 Dense

3.2.2 Open

3.2 Deciduous (Moist & Dry) 3.2.1 Dense

3.2.2 Open

3.3 Scrub Forest

3.4 Forest Blank

3.5 Forest Plantations

3.6 Mangroves

4 Wastelands

4.1 Salt Affected Land

4.2 Waterlogged Land

4.3 Marshy / Swampy Land

4.4 Gullied / Ravinous Land

4.5 Land with scrub

4.6 Land without scrub

4.7 Sandy area (Coastal & Desert)

4.8 Mining/ Industrial Wasteland

4.9 Barren rocky/Stony waste/Sheet rock area

5 Water Bodies

5.1 River / Stream

5.2 Canals

5.3 Lake / Reservoirs / Tanks

6 Others

6.1 Shifting Cultivation

6.2 Grassland/ Grazing land 6.2.1 Dense

6.2.2 Degraded

6.3 Salt Pans

6.4 Snow covered / Glacial Area



50

9. LAND USE/LAND COVER CLASSIFICATION

9.1 Agricultural land

These are the land primarily used for farming, production of food, fiber, other commercial

and horticultural crops including land under crops (irrigated and unirrigated), fallow, plantations, etc.

This category covers an area of 6273.66 Km2 (74.4%) (Fig.5)

9.1.1 Crop Land: The crops may be either Kharif/Rabi seasons or double cropped including

irrigated and unirrigated, fallow, plantation etc (NRSA, 1989). The area under crops have digitized

based on the standing crops as on the date of satellite image acquisition using both Kharif & Rabi

seasons. This covers an area of 5,706.02 Km2 (67.67%) (Fig.6).

9.1.1.a Double Cropped: The main cropping season, kharif, starts from May and ends by

September. The cropping intensity is very high due to physical factors such as flat terrain, fertile soil

and irrigated from canal system. Most of the double crop areas are concentrated adjacent to the rivers

flowing in the study area. On FCC, the double crop show a dark red tone with square pattern

representing soil covers with higher amount of moisture near the streams. The cultivated lands at

elevated zones represent bright red tone representing less amount of moisture and deeper levels of

groundwater prospect zones. This category has been identified and mapped using the two season

satellite images. This category covers an area of 774.46 Km2 (13.57%) (Fig.7).

9.1.1.b Kharif: These are the standing crops from June to September associated with rainfed crops

under dry land farming and limited irrigation. The cultivated land of Kharif season on FCC shows

bright red tone. The areas in single crop system with moderately deep to deep soil on nearly level to

very gently sloping with good to moderate groundwater potential/accessible surface water resources

or both can be put into intensive cropping system. Kharif crops such as groundnut, sunflower, jowar,

bajra and horsegram grown under rainfed condition and paddy & ground nut are grown under

irrigated conditions. The land occupies an area of 4,269.58 Km2 (74.82%) (Fig.7).

9.1.1.c Rabi Season: These are another type of standing crops from October to February. Rabi

season data found to be very much useful in discriminating other plantations from croplands by

multi-temporal data of the period. These are noticed in north eastern parts of Chitradurga taluk,

northwestern parts of Hiriyur taluk and in small parts of Holalkere, Hosadurga and Molkalmuru

taluks covering an area of 661.97 Km2 (11.6%) (Fig.7).

Table.2. Image Characteristics of various land use/land cover categories of the study area (as seen in

FCC)

LU/LC category Tone/ color Size Shape Texture Pattern

Agricultural

plantation Dark red to red Small to large

Regular to

Irregular

Coarse to

medium

Dispersed

contiguous

Barren rocky/

Sheet rock

Greenish blue

to yellow to

brownish

Varying in

size

Irregular,

discontinuous

Coarse to

medium

Linear to contiguous

and dispersed

Built-up land Dark bluish

green Small to big Irregular Coarse

Clustered to

Scattered

Crop land Bright red to

red

Varying in

size

Regular to

Irregular

Medium to

Smooth

Contiguous to non-

Contiguous

Deciduous forest Red Varying in

size

Irregular,

discontinuous

Smooth to

medium

(depends on

crown density)

Contiguous to non-

Contiguous



51

Fallow land Yellow to

greenish blue Small to big

Regular to

Irregular

Medium to

Smooth

Contiguous to non-

Contiguous

Forest land Dark red Varying in

size

Irregular,

discontinuous

Smooth to

medium

(depends on

crown density)

Contiguous to non-

Contiguous

Forest plantation Light red to red Varying in

size

Regular to

Irregular

Smooth to

medium

Contiguous to non-

Contiguous

Gullied/Ravenous

land

Light yellow to

bluish green

Varying in

size Regular, broken

Very coarse to

coarse

Dendritic to sub-

dendritic

Land with scrub

Light yellow to

brown to

greenish blue

Varying in

size

Irregular,

discontinuous

Coarse to

mottled

Contiguous

dispersed

Land without

scrub

Light yellow to

brown

Varying in

size

Irregular,

discontinuous

Coarse to

mottled

Contiguous

dispersed

Mining/Industrial

area

Light bluish to

black dark gray

Small to

medium in

size

Irregular in shape Mottled texture Contiguous

dispersed

Reservior/

River/stream

Light blue to

dark blue

Long narrow

and wide Irregular, Sinuous

Smooth to

medium

Contiguous,

dendritic/sub-

dendritic

Salt affected land White to light

blue

Small to

medium

Irregular,

discontinuous

Smooth to

mottled

Dispersed, non-

contiguous

Scrub forest

Light red to

brown (depends

on canopy

cover)

Varying in

size

Irregular,

discontinuous

Coarse to

mottled

Contiguous to non-

Contiguous

Water bodies

Light blue to

dark blue

(Subject to

depth, weeds)

Small,

medium,

large

Regular to

Irregular

Smooth to

mottled

Non-contiguous

dispersed

9.1.2 Fallow land: The agricultural land which is taken up for cultivation but is temporarily allowed

to rest, uncropped for one more season with less than one year. These are particularly devoid of

crops at the time; when the imagery is taken from both seasons. On FCC, fallow land shows yellow

to greenish blue tone, irregular shape with varying size associated with amidst crop land as harvested

agriculture field. The total area under this category is 65 Km2 (0.77%) (Fig.6).

9.1.3 Agricultural Plantations: The areas with tree plantation or fruits orchards planned by

adopting certain agricultural management techniques undoubtedly considered to be lucrative as

compared to agriculture crops; further no tedious maintenance is required for the plantation.

Differentiation of plantation from cropland is possible by multi-temporal data of the period matching

harvesting time of the inter-row crop or the flowering of the plantation crop. Overall, rabi season

data found to be very much useful in discriminating these plantations from croplands. This category

covers an area of 502.62 Km2 (5.96 %) (Fig.6).

9.1.4 Prosopis Juliflora: Prosopis juliflora is capable of growing in problematic salt affected soils

and one of the most tolerant species for saline, alkaline soils (Maliwal, 1999). Growing Prosopis

juliflora for ten years can significantly decreases pH, EC, Ca, Mg, K, CO3, HCO3, SO4 and Cl. These

are noticed on red sandy loam soils of Hiriyur taluk derived from gneiss and schist-chlorites with



52

few bands of ferruginous quartzite (Basavaraja et al., 2007). These are noticed occupying almost all

the road sides, neglected areas, lakes and margins of forest lands covering an area of 42.12 Km2

(0.49 %) (Fig.6).

Table.3 Level-1 land use /land cover classification

Sl No Level-1 Area (Km2) Percentage (%)

1. Agricultural land 6273.6615 74.40

2. Built up land 94.2260 1.11

3. Forest land 741.1825 8.79

4. Wastelands 841.6576 9.98

5. Water bodies 384.9181 4.56

6. others 96.2902 1.14

8431.9359 99.98



53

9.2 Built-up land

The land surfaces of man-made constructions due to non-agricultural use including buildings,

transportation network, communication, industrial, commercial complexes, utilities and services in

association with water, vegetation and vacant lands. Collectively, cities, towns and habitations are

included under this category (Basavarajappa et al., 2013). The total aerial extent of built-up land is

94.22 Km2 (1.11%) (Fig.5).

9.2.1 Urban (Towns and Cities): Land used for human settlement of population more than 5000 of

which more than 80% of the work forces are involved in non-agricultural activities is termed as

urban land use. Most of the land covered by building structures is parks, institutions, playgrounds

and other open space within built up areas. Urban land occupies an area of 15.23 Km2 (0.18 %)

(Fig.6).

9.2.2 Rural (Villages): Land used for human settlement of size comparatively less than the urban

settlement of which more than 80% of people are involved in agricultural activities. Villages can be

clearly noticed from toposheet & satellite images with number of houses, inter spread with trees and

agriculture fields especially in south western parts of study area occupied by thick forest with hilly

region. The area occupied by this class is about 78.73 Km2 (0.93%) (Fig.6).

9.3 Forest

The area (within the notified forest boundary) bearing an association predominantly of trees,

other vegetation types capable of producing timer and other forest products. Satellite data has

become useful tool in mapping the different forest types and density classes with reliable accuracy

through visual as well as digital techniques (Madhavanunni, 1992; Roy et al., 1990; Sudhakar et al.,

1992). Forests exert influence on climate, water regime and provide shelter for wildlife and livestock

(FAO, 1963). The area under this category is 741.18 Km2 (8.79 %) (Fig.5).



54

Table.4. Level-2 land use/land cover classification

Sl. No Level-2 Area (Km2) Percentage (%)

1. Agricultural plantation 502.6252 5.96

2. Barren rocky/stony waste/sheet rock area 114.0821 1.35

3. Crop land 5706.0266 67.67

4. Deciduous forest 136.8978 1.62

5. Degraded forest 232.8372 2.76

6. Fallow land 65.0095 0.77

7. Forest plantations 37.4425 0.44

8. Gullied/Ravenous land 22.2030 0.26

9. Land with scrub 581.3225 6.89

10. Land without scrub 25.5328 0.30

11. Mining/industrial wasteland 2.3603 0.02

12. Prosopis juliflora 42.1221 0.49

13. Reservoir 90.7647 1.07

14. River island 1.6319 0.01

15. Rivers/streams/lakes/ponds 292.5214 3.46

16. Rural (Village) 78.7377 0.93

17. Salt affected land 96.4147 1.14

18. Scrub forest 334.0048 3.96

19. Tree groves 54.1580 0.64

20. Urban (Town/cities) 15.2302 0.18

Total 8432.0969 99.92

9.3.1 Deciduous forest: The common type occurring over large areas in the plains in various stages

of degradation of tropical dry deciduous forests. However these forests are in a fluid state and may

progress into dry deciduous forests if proper protection is provided. Most parts of Kudirekanive,

Jogimatti, Lakkihalli, Suvarnamukhi State Forest are of this type (Ganesh Babu., 2013). Teak,

Terminalia and Padauk are some of the economically important trees noticed in deciduous forest.

Type, crown density and composition of forest vegetation along with degradational stage help in the



55

analysis of deciduous forest vegetation under acceptable limits of accuracy. These deciduous forests

are well intermixed with evergreen forest in central and southern parts. Multi-temporal data,

particularly during October and March/April seasons help in their discrimination from other forest

types. The area occupied by this category is 136.89 Km2 (1.62%) (Fig.6).

9.3.2 Degraded Forest: Forest cover with less than 10% is called as degraded forest. The

degradation is brought about by maltreatment meted out by repeated felling, grazing and forest fires.

On the contrary, if further ravaged it, ultimately degrades into thorny type and ultimately dry grass

prevails and naked boulders are exposed. The general floristic composition is almost the same as in

Southern dry mixed deciduous forests but for the fact that the crop is sparse and much degraded.

These are observed in Elakuranahalli, Elladakere, Gollarahatti, Bagganadu of Hiriyur taluk,

Alagavadi, Hire Kandavadi of Chitradurga, Katamdevarakote of Challakere taluk and few parts of

Molakalmuru taluk. This category covers an area of 232.83 Km2 (2.76 %) (Fig.6).

9.3.3 Forest plantation: Area of trees with species of forestry and its importance raised on notified

forest lands. These are artificially planted areas with tree cover, either in the open spaces or by

clearing the existing forests for economically inferior species. New and young plantations can be

readily separated from contiguous forested areas. The area occupied by this class is about 37.44 Km2

(0.44 %) (Fig.6).

9.3.4 Scrub Forest: Scrub forest is associated with barren rocky/stony waste due to inadequate and

erratic rainfall conditions that brings drought and extreme heat in summer season which preclude

hardly in any profitable forest. On FCC, it appears as dark red to red tone mainly due to rich in

timber trees. They appear as light red to dark brown tone on standard FCC due to canopy covers. The

area covered by this category is 334 Km2 (3.96 %) (Fig.6).

9.4 Wastelands

These are degraded lands which can be brought under vegetative cover with reasonable

effort. These are currently under utilized and deteriorating due to lack of appropriate water & soil

management or on account of natural causes. Wastelands can result from inherent/imposed

disabilities such as locations, environment, chemical and physical properties of the

soil/financial/management constraints (NWDB, 1987; Pushpavathi and Basavarajappa., 2009;

Basavarajappa and Manjunatha., 2014b). The total aerial extent of wasteland covers about 841.65

Km2 (9.98 %) (Fig.5).

9.4.1 Barren rocky/Stony Waste: As the area is exposed to the direct action of sun and wind, most

of the area remains barren. These are the lands characterized by exposed massive rocks, sheet rocks,

stony pavements or land with excessive surface, accumulation of stones that render them unsuitable

for production of any green biomass. Such lands are easily discriminated from other categories of

wastelands due to their characteristic spectral response. On FCC, they appears as greenish blue to

yellow to brownish in tone with varying size associated with steep isolated hillocks, hill slopes and

eroded plains. They occur as a linear form within the plain land mainly due to varying lithology

(Basavarajappa and Manjunatha., 2014b). These types of lands are noticed in Vijapura,

Guddadarangavvana halli, Madakaripura of Chitradurga taluk and few parts of Molakalmuru taluk.

The area occupied by this category is 114.08 Km2 (1.35 %) (Fig.6).

9.4.2 Gullied/Ravenous land: Gullies are narrow and deep channels developed from rills which are

tiny channels of few centimeters deep, formed by the impact of rainfall and weaving action of runoff

occurs more commonly on sloping land. These areas are having entrenched drainage system, good

rainfall and surface runoff. On FCC, they appears as light yellow to bluish green depending upon the

surface moisture and depth of erosion with varying size (Basavarajappa and Manjunatha., 2014b;

Basavaraj Hutti and Basavarajapp., 2014). This type of land is observed in Arehallihatti of Holalkere

taluk and Kalkere of Hosadurga taluk. These gullies and ravines contribute to soil erosion and land

degradation covering an area of 22.2 Km2 (0.26 %) (Fig.6).



56

9.4.3 Land with scrub: Scrub lands are observed along the ridges, valley complex, linear ridges and

steep slope areas. Most of these areas are characterized by the presence of thorny scrub, herb species,

many hillocks of steep and domal shaped are associated with poor vegetal cover. As a consequence,

severe soil erosion frequently occurs during rainy seasons and later most of the hill tops become

barren/ rocky. These lands are observed in few parts of Molakalmuru and Chitradurga, and most part

of Hiriyur, Hosadurga and Challakere taluks. This category covers an aerial extent of 581.32 Km2

(6.89 %) (Fig.6).

9.4.4 Land without scrub: Land under this class is generally prone to degradation/deterioration and

may not have scrub cover. It is confined to (relatively) higher topography such as uplands or high

grounds etc excluding the hills and mountainous terrain. On FCC, they appear as light yellow to

brown to greenish blue, varying in size associated with gentle relief with moderate slope in plain and

foothills surrounded by agricultural lands. This covers an aerial extent of 25.53 Km2 (0.3 %) (Fig.6).

9.4.5 Mining/Industrial area: These are the lands with large-scale mining operations, mine dumps

and discharge of large scale industrial effluents causing land degradation. The features exhibit dark

gray (coal mining areas) to light bluish to black (iron ore waste) tone on standard FCC based on the

color of the mine dump, small to medium in size, irregular in shape with mottled texture, located at

or near active mining areas and industrial complexes. Conspicuously around urban areas and other

areas where industrial activity is prominent. This type of lands are observed in Megalahalli,

Beemasamudra, Hanumanahalli, Sannakittadahalli, Ingaldhal, Halekal, Hosahatti and Bahadurghatta

area of the study area.This category covers an area of 2.36 Km2 (0.02 %) (Fig.6).

9.4.6 Salt-affected area: The areas are delineated based on white to light blue tone and its situation.

These are found in river plains and in association with irrigated lands. These areas are adversely

effecting the growth of most of the plants due to the action or presence of excess soluble or high

exchangeable sodium. These lands are noticed in few parts of Molakalmuru taluk, Hosahalli, Talaku,

Balenahalli, Kammathmarikunte, Challakere, Purlehalli, Parasurampura, ThimmannanaikanaKote,

Gollahalli, Hariyabbi, Ajjikamasagara, Turuvanur, Chikkgondanhalli and Panjaiahnahatti of the

study area. The area occupied by this category is 96.41 Km2

(1.14 %) (Fig.6).



57

Table.5. Level-3 land use/land cover classification

Sl No. Level-3 Area (Km2) Percentage (%)

1. Kharif + Rabi (Double crop) 774.4670 13.57

2. Kharif crop 4269.5836 74.82

3. Rabi crop 661.9759 11.60

Total 5706.0265 99.99

9.5 Water bodies

This class comprises areas of surface water, either impounded in the form of ponds, lakes and

reservoirs or flowing as streams, rivers, canals, etc. These are clearly observed on standard FCC in

different shades of blackish blue to light blue color depending on the depth of water bodies. The area

occupied by this category is 384.91 Km2 (4.56 %) (Fig.5).

9.5.1 River/streams/lakes/ponds: The Natural course of water flowing openly on the land surface

along a definite channel. Vedavathi River basin covers maximum areas in the district and is tributary

of Tungabhadra River. The length of the Vedavathi river measures 208 Km. The other rivers in the

taluk noticed are the Doddahalla (Peddavanka), Janagahalli, Chikhagari, Swarnamukhi, Garain and

Nayakanahalli halla. About 162 major tanks, 135 minor tanks, 5,643 tube-wells and 3 reservoirs

have been reported from the District (CGWB, 2012). These cover an area of 292.52 Km2 (3.46%)

(Fig.6).

9.5.2 Reservoir: A reservoir is the artificial lake created by construction of a dam across the river

specifically for the generation of hydro-electric power, irrigation, water supply for

domestic/industrial uses and flood control. The introduction of a huge reservoir would be disturbing

the delicate balance between soil, water and plants through rise in groundwater table (water-logging)

(Piyoosh Rautela, 2002). The well noticed reservoirs are Vanivilas Sagar reservoir, Gayatri reservoir,

Rangayanadurga reservoir and Narayanapura anicut. Vanivilas Sagar reservoir is one of the

reservoirs built across the Vedavathi River at Vanivilaspura in Hiriyur taluk. Gayathri reservoir is

built across the river Suvarnamukhi near Javagondanahalli village; while Narayanapura dam is built

near Ramanahalli of Hiriyur taluk providing water majorly for irrigation. Rangayanadurga Reservoir

is built in between Challakere and Rayadurg taluk. These categories cover an area of 90.76 Km2

(1.07 %) (Fig.6).

9.5.3 River Island: These are the landmass or fluvial landform observed within a river after decrease

in water level especially during summer seasons covering an area of 1.63 Km2 (0.01%) (Fig.6).



58

8. RESULTS & DISCUSSION

LU/LC exposes considerable influence on the various hydrological aspects such as

interception, infiltration, catchment area, evaporation and surface flow (Sreenivasalu and Vijay

Kumar., 2000; Kumar et al., 1999). LU/LC provides a better understanding on the cropping pattern

and spatial distribution of fallow lands, forests, wastelands and surface water bodies, which is vital

for developmental planning (Philip and Gupta, 1990).According to Karnataka State Forest

Department, the district is endowed with 25 State forest with an area of 741.18 Km2 (8.79%)

(Dinakar and Basavarajappa., 2005; Basavarajappa and Manjunatha., 2014b; Basavarajappa et al.,

2014c). The impact of land use and land cover over the surface and sub-surface hydrologic condition

is observed to be remarkably high on agricultural practices. Change in land use is mainly due to the

hydrological factors (Saraf and Choudhary., 1998).

9. CONCLUSIONS

The land use/land cover classification analysis of 1:50,000 scale is divided into Level-1: 6

classes; Level-2: 20 classes and Level-3: 3 classes are carried out based on environmental and socio-

economic concerns. Level-3 classification has been carried out in detail on agricultural and forest

lands to study the cropping pattern. More accurate classification is observed in case of digital

technique as compared to that of visual technique in terms of area statistics. The satellite data of two

seasons is acquired (Rabi in Dec-2005 and Kharif in Oct-2006) to estimate the spatial distribution

and temporal variability of different LU/LC pattern based on the standard schemes developed by

NRSA using geomatics technique. Kharif crops are dependent mainly of rainfall and occupy the

maximum areal extent of 4269.58 Km2 (74.82%) that indirectly reflect that groundwater dependent

crops are less. Double crops are noticed adjacent to the perennial rivers which provide well

developed canal system for irrigation purpose. Vedavathi River along with others streams such as

Doddahalla (Peddavanka), Janaga halla, Chikhagari halla, Swarnamukhi, Garain halla and

Nayakanahalli halla drain most parts of the district. The area occupied by built-up land is 94.22 Km2

(1.11%) and further increase in population can negatively impacts on biodiversity and also disturbs

natural land cover, increase in soil erosion into streams and lakes. Changes in land surface conditions

can affect the volume, timings and quality of run-off water. Prosopis juliflora is capable of growing

in problematic salt affected soils and can significantly decreases pH, EC, Ca, Mg, K, CO3, HCO3,

SO4 and Cl which covers an area of 42.12 Km2

(0.49%) in the study area. Reclamation of wastelands

are the important task in agricultural point of view. Geomatics application provide wide range of

digital databank information in a synoptic, spatial and temporal manner for mapping and monitoring

of land use/land cover in most time and cost effective manner.

ACKNOWLEDGEMENT

The authors are indepthly acknowledged Prof. S. Govindaiah, Chairman, DoS in Earth

Science, CAS in Precambrian Geology, Manasagangothri, University of Mysore, Mysore; Zilla

Panchayath, Chitradurga and UGC-MRP no.42-73(SR)/2012-13, dt: 12.03.2012, New Delhi for

financial support.



59

REFERENCE

1. Basavaraja P.K, Sharma S.D, Badrinath M.S, Sridhara S and Hareesh G.R (2007). Prosopis

Juliflora – an efficient tree species for reclamation of salt affected soils, Karnataka Journal of

Agricultural Science, Vol.20, No.4, Pp: 727-731.

2. Basavaraj Hutti and Basavarajappa H.T., (2014). Assessment of River Basin for Engineering

Restoration in Ghataprabha Catchments using Geo-informatics Applications, International

Journal of Computer Engineering and Technology (IJCET), Vol.5, Issue.1, Pp: 94-102.

3. Basavarajappa H.T, Parviz Tazdari, Manjunatha M.C and Balasubramanian A., (2013).

Application of Remote Sensing and GIS on Waste Disposal Site Selection and Environmental

Impact Assessment around Mysore City, Karnataka, India., International Journal of Earth

Sciences and Engineering, Cafetinnova, Vol.6, No.2, Issue.2, Pp: 1801-1808.

4. Basavarajappa H.T, Manjunatha M.C and Jeevan L (2014a). Application of Geoinformatics

in Delineation of Groundwater Potential Zones of Chitradurga district, Karnataka, India.

International Journal of Civil Engineering and Technology (IJCIET), Vol.5, Issue.5, Pp: 94-

108.

5. Basavarajappa H.T and Manjunatha M.C (2014b). Geoinformatics Techniques in Mapping

and Reclamation of Wastelands in Chitradurga district, Karnataka, India. International

Journal of Computer Engineering and Technology (IJCET), Vol.5, Issue.7, Pp: 99-110.

6. Basavarajappa H.T, Dinakar S and Manjunatha M.C (2014c). Analysis of Land use/land

cover classification around Mysuru and Chamarajanagara district, Karnataka, India using

IRS-1D, PAN+LISS III Satellite Image. International Journal of Civil Engineering and

Technology (IJCIET), Vol.5, Issue.11, Pp: 79-96.

7. Central Ground Water Board, (2013). Govt. of India, Ministry of Water Resources,

Groundwater Information Booklet, Pp: 1-31.

8. Dinakar S., (2005). Geological, geomorphology and land use/land cover studies using

Remote Sensing and GIS around Kollegal Shear Zone, South India, Unpub thesis, University

of Mysore, Pp: 1-191.

9. FAO, (1963). World Forest Inventory. Food and Agriculture Organization of United Nations,

Rome.

10. Ganesh Babu N M (2013). A Note on the Floristic Diversity and Ethno-botany of Chitradurga

District, Expert Committee, Honourable National Green Tribunal (South Zone), Centre of

Excellence of Union Ministry of Environment and Forests. Pp: 1- 40.

11. Kumar A., Tomas S., and Prasad L.B (1999). Analysis of fracture inferred from DTM and

remotely sensed data for groundwater development potential zones through remote sensing

and a geographical information system, Int. J. Remote Sensing, Vol.26, No.2, Pp: 105-114.

12. Kumar, Vijay, Rai, S.P. and Rathore, D.S. (2004). Land use mapping of Kandi Belts of

Jammu.

13. Likens W and Maw K, (1982). Hierarchial modeling for image classification, Proc. Remote

Sensing with Special Emphasis on Output to Geographic Information System in the 1980’s,

PECORA VII, South Dakota, USA, Pp: 290-300.

14. Madhavanunni N.V (1992). Forest and ecology application of IRS-1A data, Natural resources

management – A new perspective, Publication and Public Relations Unit, ISRO-Hq,

Bangalore, Pp: 108-119.

15. Maliwal G.L (1999). Reclamation of saline and sodic soils through Prosopis Juliflora, Indian

Journal of Forestry, Vol.22, Pp: 132-135.

16. NRSA (1989). Manual of Nationwide land use/land cover mapping using satellite imagery,

part-1, Balanagar, Hyderabad.



60

17. NRSA (1995). Integrated mission for sustainable development, Technical Guidelines,

National Remote Sensing Agency, Department of Space, Govt. of India, Hyderabad.

18. National Remote Sensing Agency (2007). Manual of National Wastelands Monitoring Using

Multi-temporal Satellite Data, Department of Space, Hyderabad.

19. NWDB (1987). Description and Classification of Wastelands, National Wastelands

Development Board, Ministry of Environmental and Forest, Govt. of India, New Delhi.

20. Philip G and Gupta R.A., (1990). Channel migration studies in the middle Ganga basin, India

using Remote sensing data, Int. J.Remote Sensing, Vol.10, No.6, Pp: 1141-1149.

21. Piyoosh Rautela, Rahul Rakshit, Jha V.K., Rajesh Kumar Gupta and Ashish Munshi (2002).

GIS and Remote Sensing based study of the reservoir-induced land-use/land-cover changes in

the catchment of Tehri dam in Garhwal Himalaya, Uttaranchal (India), Current Science,

Vol.83, No.3, Pp: 309-311.

22. Priyakant G.S., Kanade A.S., Deshpande V.K., and Kondawar (2001). Application of Remote

Sensing data and Geographical Information Systems for land use/land cover changes analysis

in mining areas – A case study, Muralikrishna I.V., (Ed). ICORG Spatial Information

Technology: Remote Sensing and Geographical Systems, BS Publications, Hyderabad, India,

Vol.2, Pp: 520-525.

23. Pushpavathi K.N and Basavarajappa H.T (2009). Remote Sensing and GIS applications for

Wasteland identification - a case study in Kollegal taluk, Chamarajanagar district, Karnataka,

India, Environmental Geochemistry, Vol.12, No.1 & 2, Pp: 13-18.

24. Roy P.S., Diwakar P.G., Vohra T.P.S and Bhan S.K (1990). Forest resources management

using Indian Remote Sensing Satellite data, Asian-Pacific Remote Sensing J., Vol.3, No.1,

Pp: 11-16.

25. Rubee C.D and Thie J, (1978). Land use monitoring with Landsat digital data in southwestern

Monitoba, Proc. 5th Canadian Symp. on Remote Sensing of Environment, Victoria, British

Columbia, Pp: 136-149.

26. Saraf A.K and Choudhary P.Q (1998). Integrated Remote Sensing and GIS for Groundwater

exploration and identification of artificial recharge sites, Int. J.Remote Sensing, Vol.19,

No.10, Pp: 1825-1841.

27. Singh, S.K., Thakur, J.K. and Singh, U.K. (2010). Environmental monitoring of land

cover/land use changes in Siwalik Hills, Rupnagar district of Punjab, India using remote

sensing and ancillary data. Paper presented at the International Conference on Global Climate

Change.

28. Sreenivasalu V. and Vijay Kumar (2000). Land use/land cover mapping and change detection

using satellite data – A case study of Devak catchment, Jammu and Kashmir, Proc. of

ICORG, Vol.1, Feb, Hyderabad, Pp:520-525.

29. Sudhakar S., Krishnan N., Das P and Raha A.K (1992). Forest cover mapping of Midnapore

forest division using IRS-1A LISS-II data, Natural resources management – A new

perspective, Publication and Public Relations Unit, ISRO-Hq, Bangalore, Pp: 314-319.

30. Basavarajappa H.T, Jeevan L and Manjunatha M.C, “Delineation of Groundwater Potential

Zones In Precambrian Hard Rock Terrain of Tumakuru District, Karnataka, India Using

Geomatics Application” International Journal of Civil Engineering & Technology (IJCIET),

Volume 5, Issue 12, 2014, pp. 305 - 315, ISSN Print: 0976 – 6308, ISSN Online: 0976 –

6316.

31. Basavarajappa H.T. Pushpavathi K.N. and Manjunatha M.C, “Morphometric Analysis on

Precambrian Rocks In Part of Cauvery Basin, Chamarajanagar District, Karnataka, India,

Using Geomatics Technique” International Journal of Civil Engineering & Technology

(IJCIET), Volume 6, Issue 1, 2015, pp. 97 - 112, ISSN Print: 0976 – 6308, ISSN Online:

0976 – 6316.