3.4.1 Image Processing
DIP was carried out in the computer system, which has the following hardware & software
configuration.
- 80 GB hard disk, Window XP version Pentium(R) IV processor.
- ERDAS Image processing 8.6 and
- ArcGIS 9.1 version.
Geometric correction of Image and Preparation of Area of Interest
(AOI)
A first order polynomial transformation and resampling with nearest neighborhood
algorithm was used to spatially geo-reference the IRS ID P6 LISS III image
to projection System, Ground control points identifiable at road intersections
in reference to topographic map (1:250,000) from SOI toposheet were used. The
boundary of the study area was extracted using Area of Interest (AOI) Module
of the ERDAS 8.6. This AOI of the study area was then used in extracting Nagpur
district sub-image. The procedure followed is presented schematically in Fig.
3.
Digital supervised and unsupervised classification
Supervised classification is defined as the process of samples of pixels of
known identity to classify pixels of unknown identity. Samples of known identity
are those pixels located within training areas. Pixels located within these
areas called as the training samples are used to guide the classification
algorithm to assign specific spectral values to appropriate informational
class. The basic steps involved in a typical supervised classification procedure
are:
- FCC Interpretation.
- The training stage.
- Feature section.
- Selection of appropriate classification algorithm.
- Post classification smothering.
- Accuracy assessment.
The training sites generated in the present study include current fallow,
road, river, forest, rock out crop and water body. Schematic diagram of supervised
classification is also presented in Fig. 3.