Auto-extraction technique-based digital classification of saltpans and aquaculture plots using satellite data

Mapping and classification of coastal features from visible (VIS) and near-infrared (NIR) bands of remote sensing satellite data is less accurate (similar to 67 to 70 only) than land features due to confusing spatial and spectral characteristics among several contiguous shallow water features. Our study of spectral responses of most alike coastal features such as aquaculture plots, saltpans, sandy beaches, built-up areas and fly ash dumpsites show mix-ups in the VIS and NIR band responses. Albeit, the VIS (green) and short-wavelength infrared (SWIR) bands show subtle distinctions which help to more accurately and automatically perform digital classification of these features with a reasonable accuracy of >95%.