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Monitoring shrimp farming development from the space: A RS and GIS approach in Kandleru creek area, Andhra Pradesh, India
The geometric correction and registration of three images were done using 15 ground control points (GCPs) in each image. Linear polynomial equation was used to implement the corrections. Georeferencing of satellite imagery was carried out using digitized topographic map. Nearest neighbor interpolation method was used for resampling the satellite image. Image fusion techniques (PCA and RGB/HIS) were applied to obtain high spatial and spectral resolution from low spatial-multispectral images and high spatial panchromatic images. It was useful to identify the shrimp farms from vegetation and other land uses for its capability to enhance the specific shapes and extract spectral reflectance of shrimp farms (Figure 2). Band ratio (Red Band/Near Infrared Band) technique was carried out to differentiate water from other land use classes, which has helped to find and locate active shrimp farms.  Figure 2: Data Fused Image of Kandleru creek area derived from IRS 1C LISS-III (23.5m) and IRS 1C PAN (5.8m), (RGB/IHS). The rectangle shape water bodies with dykes along the creek are shrimp Several classifiers were applied to extract maximum environmental information for creating database in GIS. Creek map was digitized from 1.50,000 scale topographic map. Other information layers such as villages, roads, canals, islands, and swamps were also used as GIS layers (Figure 3). Finally, the analysis was carried out in Arcview GIS. Increasing shrimp farms, decreasing natural resources and changing others land use patterns were identified, located and evaluated at two different dates of data acquisition.  Figure 3: Land use or land cover map of Kandleru creek area in 2001 |