IAPRS & SIS, Vol.34, Part 7, “Resource and Environmental Monitoring”, Hyderabad, India, 2002
grid points both in planimetric and altimetric term’s ie,
horizontal and vertical directions.
For the present study, DEM is generated using Conversion of
printed contour lines; for which, the SOI topographic maps
(special series) on 1:15840 scale are used as the base.
This is then used as input and using ARC INFO GIS software's
TIN module, it was converted into a matrix of Triangulated
Irregular Network (TIN), which in turn, was converted into a
DEM of 6 meters resolution, i.e., the spatial resolution of the
merged satellite data.
After generating the DEM using lattice and poly commands
sequences and extract predefined submergence contours of 140,
137, 134 and 131 meters over MSL from the DEM.
(vi) Projection of Village Cadastres
As part of the work to met one of the objectives, it was needed
to overlay the land parcel information from the Cadastral Maps
on to the classified LU/LC maps. To achieve this, the
following steps were followed.
Tracing of Cadastre maps
Cadastre map copies supplied for the pilot study area by the
SSNNL were overlain with transparent Artean Tracing Film
and were manually traced in the form of continuous lines.
These maps were then photo optically reduced to 1:15840 scale
from their given scale of 1:7200 and outputs X were
collected in the form of transparent positives.
Identification of GCPs
As these maps do not possess any geographical referencing
schemes, their transparent positive outputs were overlaid on
corresponding 1:15,840 scale. ^ Special Series Topomaps
supplied by M/s SSNNL ànd suitable Ground Control Points
(GCPs) were identified. In some cases, where to find required
number of GCPs for one village by itself was difficult, a mosaic
of these positives was made and then GCPs were then pointed
on that.
Scanning and Projection
These positives were then scanned on Black and White Context
Scanner at suitable resolution and the resultant raster output
was thinned, vectorised and edited for different errors. The
error-free vector coverage was then tagged with corresponding
Survey Number information to the extent possible and was then
projected and transformed based on the GCP information.
(vii) Overlay and Statistics Extraction
To achieve the third and fourth objectives of the study, it is a
prerequisite to overlay the corresponding layers of information
one over the other. This is achieved in ARC INFO GIS /
ERDAS Imagine Image Processing Softwares. To help the
outlook of the map composition and to make the land use maps
easily interpretable in terms of the location, the base details
were also added into a vector layers.
610
Overlay Process
The next step involves in Vector over raster overlay and vector
over vector overlay operations, for which, ARC INFO GIS
software is used, taking help of the common projection surface,
the projected Cadastral map mosaic along with the base map
was overlaid onto the raster form land use land cover map.
Similarly the submergence contour coverage was also overlaid
onto the land use/land cover map and village wise submergence
statistics were extracted in tabular form.
Results and Discussion
As per the statistics, about 25% of the submergence area falls
under agriculture category. It was observed that in the entire
village, an agricultural land comes under submergence. Most of
the agricultural land under submergence was found under
fallow land category. About 22% of total submerged area is
% to Sub- | % to Sub-
Category Total T.G.A 140m 140 m
Crop 280.70 2.96 34.87 1.60
Fallow 3889.97 41.06} 530.06 24.36
Dense forest 88.91 0.94 0.67 0.03
Degraded
forest 2121.92 22.40] 430.69 19.79
LWS 1091.09 11,52 113.79 5.46
LwoS 914.05 9.69 — 127.33 5.85}
Barren land 183.23 1.93 90.59 4.16
Rocky
outcrops 25.70 0.27 25.70 1.18
Riversand 311.65 3.29, 283.35 13.02
Water 567.70 5.99.....533.55 24.52
Vill Total 9474.94 100.001 2176.04 100.00
Table 2: Area and Submergence statistics
observed under forestland use (Table 2). Most of the forest area
is under degraded forest category. In comparison to other land
use classes under submergence, maximum land (about 29%) is
observed to be wasteland, which include riverbed parts also.
The existing water spread is about 24% of submergence area;
which includes tanks and river courses (Ref 1b and 2).
Homesteads
Ground truth verification was carried for about 30% of the
homesteads, which were located on all elevations (.e. from131
m to 140 m). As per the table, about 254 homesteads are likely
to be affected. Alternative sites may be provided to all affected
villages.
CONCLUSIONS
Satellite imagery at scale of 1: 15,840 found to be very useful
in determining the land use / land cover classes in submergence
area. Land use with parcel information, parcel-wise land use
details affected by submergence are useful in planning
rehabilitation. This study is very useful to know overall
scenario of submergence land use classes. Accordingly,
planning measures can be taken.
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