Abstract
Recognizing the environmental impact of aquaculture, a study was conducted to investigate the feasibility of generating aquaculture data using ResourceSat LISS-IV and PAN data in a section of coastal Andhra Pradesh, southern India. The study involved database preparation, including georeferencing and radiometric normalization, on-screen visual interpretation of spaceborne multispectral and multitemporal data, and the creation of area statistics.
The ResourceSat LISS-IV data enabled the identification of areas where aquaculture is practiced, while the LISS-IV and PAN-merged data facilitated the detection of individual aquaculture ponds due to improved spatial resolution. Between 1986 and 2001, the area under aquaculture expanded significantly.
The study aimed to assess the potential of various image fusion techniques, namely:
- Hue-Intensity-Saturation (HIS),
- Principal Component Analysis (PCA),
- Brovey transformation,
- Cubic spline wavelet transformation,
- Multiplicative transformation, and
- High-pass filter (HPF) transformation,
for delineating salt-affected soils in the Kaikalur area of Andhra Pradesh using data from the Indian Remote Sensing Satellite (IRS-ID) Linear Imaging Self-Scanning Sensor (LISS-IV) and Panchromatic sensor data.
The results indicate that, compared to commonly used approaches like IHS transformation, wavelet transformation provides more accurate delineation of salt-affected soils. Furthermore, IHS and HPF transformations have been found to outperform PCA transformation in terms of accuracy and performance.
Keywords: Aquaculture; LISS-IV; PAN-data; Image Fusion
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