Use of IRS-1B data for change detection in water quality and vegetation of Chilka lagoon, east coast of India

Sedimentation, resulting from cyclic growth, spread and disintegration of macrophytes and influx of silt-laden fresh water through the riverine system, is the dominant process influencing the contemporary phase of lagoon modification in the Chilka. Remote sensing offers promise in the detection and delineation of the functional elements of lagoon modification. Therefore, IRS-1B LISS-I data along with synchronous ground data observations have been used in the present study for a qualitative and quantitative evaluation of the components involved in the modification and to obtain estimates of their distribution, abundance, diversity and physical state during an annual cycle. Results obtained indicate that the ecological parameters in the lagoon such as water quality and macrophytes undergo significant seasonal as well as interannual variability following interannual monsoon variability. Seasonal mode of variability appears to dominate over interannual mode. October and April appear as two extreme periods in the annual cycle of lagoon modification. Maximum likelihood classification for digital image analysis of time series data depicts the different lagoonal features, which largely agree with field observations. Area estimates for spectrally significant classes and their comparison with earlier studies indicate that the rate at which the vegetation is spreading has been increasing steadily and alarmingly. IRS data proved useful for predicting selected water quality parameters.