21 October 2014 Hyperspectral remote sensing for estimating coastal water quality: case study on coast of Black Sea, Romania
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Abstract
The North-Western part of the Black Sea is highly affected by eutrophication due to nutrient and sediment load inflow from the Danube River, which is the second largest delta in Europe. To get a general spatial picture of the water quality of the Romanian coast, it is not only time consuming, but also hard to measure with traditional in situ sampling. To solve these issues, methods have been developed to use close range spectral measurements for accurate and cheap assessments in real-time for the concentrations of Chlorophyll-a, Total Suspended Matter and water transparency. This paper presents the applicability of a state-of-the-art hand-held hyper-spectral sensor and a simple water transparency indicator for monitoring water quality. The fieldwork was conducted during the summer of 2013 on the Romanian coast of the Black Sea. The same techniques are used to calculate these parameters from satellite images (MODIS). The validation results and potential applications of the instruments will be discussed.
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S. G. Ghezehegn, Peters Steef, Annelies Hommersom, De Reus Nils, Oana Culcea, Bram Krommendijk, "Hyperspectral remote sensing for estimating coastal water quality: case study on coast of Black Sea, Romania", Proc. SPIE 9239, Remote Sensing for Agriculture, Ecosystems, and Hydrology XVI, 923913 (21 October 2014); doi: 10.1117/12.2067415; https://doi.org/10.1117/12.2067415
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