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Chander, S.
- Water Quality Assessment of River Ganga and Chilika Lagoon using AVIRIS-NG Hyperspectral Data
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Authors
S. Chander
1,
Ashwin Gujrati
1,
K. Abdul Hakeem
2,
Vaibhav Garg
3,
Annie Maria Issac
2,
Pankaj R. Dhote
3,
Vinay Kumar
3,
Arvind Sahay
1
Affiliations
1 Space Applications Centre, Indian Space Research Organisation (ISRO), Ahmedabad 380 015, IN
2 National Remote Sensing Centre, ISRO, Hyderabad 500 037, IN
3 Indian Institute of Remote Sensing, ISRO, Dehradun 248 001, IN
1 Space Applications Centre, Indian Space Research Organisation (ISRO), Ahmedabad 380 015, IN
2 National Remote Sensing Centre, ISRO, Hyderabad 500 037, IN
3 Indian Institute of Remote Sensing, ISRO, Dehradun 248 001, IN
Source
Current Science, Vol 116, No 7 (2019), Pagination: 1172-1181Abstract
Remote sensing is a vital tool to assess water quality parameters in water bodies like rivers, lakes, estuaries and lagoons. All these fall under the category of optically complex waters (case 2), where water-leaving radiance is affected by optically active water constituents and bottom substrate. The present study estimates water quality parameters, viz. turbidity, suspended sediment concentration and chlorophyll in River Ganga in Buxar (Bihar), and Howrah (West Bengal) and Chilika lagoon (Odisha) using hyperspectral reflectance data of AVIRIS-NG. Concurrent ground-truth data of water samples were collected and simultaneous spectro-radiometer measurements were made in synchronous with the AVIRIS-NG flight over the study area. Semi-analytical simulation modelling followed by inversion and contextual image analysis-based methods were used for estimating the water quality parameters. Water turbidity maps were generated for both the study sites. Over Ganga river, water was relatively clear in Buxar (6.87–20 NTU, TSS 42–154 mg/l), while it was extremely turbid in Howrah (50–175 NTU, TSS 75–450 mg/l). In Chilika lagoon, water was more turbid in the northern sector, which may be due to the river input and resuspension from shallow bathymetry. The results suggest that the small-scale changes in turbidity due to point sources like river tributaries or sewerage discharges can be identified using hyperspectral data. The imaging spectroscopy data over water are a key source to find out potential locations of water contamination.Keywords
Hyperspectral Data, Remote Sensing Reflectance, Semi-Analytical Algorithms, Spectroradiometer.Full Text
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