Abstract
The prime purpose of the research study was to elucidate the potential of remotely sensed data for estimation of water quality parameters (WQPs) in inland and coastal waters. The useful application of remotely sensed data for operational monitoring of water bodies demand for improved algorithms and methodology. The in situ hyperspectral Spectroradiometer data, water quality data and Airborne Imaging Spectroradiometer for Applications (AISA) data of Apalachicola Bay Florida, USA were collected. The data was analyzed to develop the models for assessment of total suspended sediment (TSS), chlorophyll-a (chl-a), and secchi depth. The analysis of collected spectral data reveals that a peak reflectance in red domain was well correlated with chlorophyll-a concentration. The optical depth is found to be strongly correlated with Chl-a and TSS. In order to examine the feasibility of multispectral data for water quality monitoring; AISA data was integrated into band widths of ALOS/AVNIR-2 sensor. The combination of three bands, band 2, 3 and band 4 was developed to correlate the remotely sensed data with TSS. The developed regression models showed good correlation with water quality parameters and may successfully applied for estimation of WQP in surface waters. The research work demonstrates an example for the successful application of remotely sensed data for monitoring the distribution of water quality parameters in water bodies.