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IAPRS & SIS, Vol.34, Part 7, “Resource and Environmental Monitoring”, Hyderabad, India, 2002 
Information on land use/land cover is the basic prerequisite for 
land resource evaluation, environmental assessment, utilization 
and management. A considerable degree of land 
transformations is being witnessed as a result of growing 
population pressure on the finite land resources consummating 
in deterioration of the environment. As a precursor, it is 
necessary to understand the ‘cause and effect’ of the 
transformations through scientific studies. Satellite remote 
sensing technology in conjunction with GIS techniques has 
proven experience in meeting such information needs as desired 
above. To cite a few examples — land use/land cover assessment 
of Patna and environs for selecting suitable site for location of 
Rail Bridge across river Ganga for rites, and land use / land 
cover dynamics study of zinc mine area of Rajpura-Dariba, 
Rajastan using remote sensing techniques by nrsa in 2000. 
Satellite remote sensing and GIS based techniques are also 
applied in riparian buffer zone mapping studies (NRSA, 2000) 
in Hyderabad area, India. 
OBJECTIVES 
* To map land use / land cover showing Level-I/ Level-II 
surface details 
* To integrate map sheet contours and land parcel details 
with land use / land cover 
* To generate a composite map showing land use / land 
cover, contours, and land parcels 
% Identification and mapping of clusters of homesteads 
within the resolvable limits of IRS-1D satellite data 
STUDY AREA 
It is covered in one map sheet (B/6 & B/7 of 46J/8 & J/12) on 
1:15,840 scale with an area of around 120 sq. km (7.5' x 5.0") 
within the Sardar Sarovar Catchment. The study area is 
covered around seventeen villages. 
DATA BASE 
(ii) Satellite Data 
The basic data selected is IRS —1D satellite's multispectral 
LISS-III data set and Panchromatic PAN data set of March 
2000 period. 
(iii) Collateral Data 
Survey of India (SOI) topographical maps on 1:15,840 & 
1:50,000 scales numbering B-6 & B-7 of 48 J/ 8 and 48 J/12 
have been used. 
(iv) Ground Truth 
Ground truth verification of doubtful areas and 
ground measurements form an important component of 
satellite-based remote sensing studies. In the present study 
sample field checks ware carried out during 19" to 23" 
November 2000. 
METHODOLOGY 
Image Restitution 
Using ERDAS Imagine (v. 8.5) image processing software, the 
PAN data set is geo-referenced. For this, feature controls were 
obtained from SOI topographical sheets 48 J/8 and 48 J/12 as 
the reference and Nearest Neighborhood resampling technique 
609 
is used. This is followed by, image-to-image registration of 
LISS-III data to the geo-referenced PAN data set(ref figure 1a). 
There exist different data fusion techniques for merging multi- 
resolution and multi-spectral data sets like: Determinant 
analysis, Principal Component analysis, Brovy transformation, 
I transformation, etc. Filtering technique is also a viable 
alternative to the above. However, for the purpose of the 
present study, I transformation is used to merge the data sets. 
Classification finalization & pre-field interpretation 
Visual interpretation refers to monoscopic interpretation of 
satellite imagery, either single band (black and white) or 
(standard/non-standard), False Color Composite (FCC) hard 
copy based on image characteristics like tone/color, texture, 
pattern, size, shape, location/site, shadow, aspect and 
association. Based on these image elements, an “interpretation 
key’ is developed which explains the process of identification 
and classification of different land use/land cover categories 
(Table:1). 
  
  
  
  
  
  
  
LEVEL — I LEVEL - II 
AGRICULTURE Crop Land 
Fallow Land 
FOREST Dense Forest 
Degraded Forest 
WASTELAND Land with Scrub 
Land Without 
  
Barren Land 
Rocky Outcrops 
WATER BODIES River sand 
Water Body 
  
  
  
  
  
  
  
Table:1 Land Use / Land Cover Classification 
Ground Data Collection and Verification 
Doubtful points were identified based on anomalies in spectral 
responses (away from normal) or mixture of spectral responses 
between more than one thematic categories. To this, the 
transportation network information is added and sample points 
for field verification are identified based on distance and 
accessibility criteria. These sample points were verified in the 
field and were marked on the control map sheet, which was 
carried to the field. 
Image Classification 
Based on the field-derived observations, the pre-field 
interpreted maps were rectified. Later, these were labeled and 
finalized. 
(v) Digital Elevation Models 
Surfaces as earth are continuous phenomena rather than 
discrete objects. To model these surfaces in digital 
environment, DEMs are used. The term Digital Elevation 
Model or DEM is frequently referred to any digital 
representation of a topographic surface. However, most often 
it is used to refer specifically to a raster or regular grid of spot 
heights. It is the simplest form of digital representation of 
topography and the most common one. The quality of a DEM 
is dependent on its resolution or the distance between adjacent