Abstract
Waterlogging and subsequent salinization and/alkalinization is the major land degradation problem in irrigated commands in the arid and semi-arid regions. The Linear Imaging Self-scanning Sensor (LISS-III) digital data acquired by the Indian Remote Sensing Satellite (IRS-1C) over part of the Indo-gangetic plains are digitally analysed for delineating salt-affected and waterlogged areas on a IBM RS-6000 system. A comparison with the IRS-1B LISS-II data, with comparable spectral bands and acquired very close to LISS-III data, reveals a relatively poor overall classification accuracy achieved from this data as compared to LISS-II data. This may be attributed to higher intra-class spectral variations resulting from high spatial resolution LISS-III data. The classifiers capable of exploiting the spectral variations in spatial domain, like segmentation, textural analysis, etc., need to be used for exploiting the full potential of IRS-1C LISS-III data for mapping salt-affected soils and other degraded lands.
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