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|Title:||Coastal water quality near to desalination project in Cyprus using earth observation||Authors:||Alexakis, Dimitrios
Hadjimitsis, Diofantos G.
|Keywords:||Spectroscopy;Water;Remote sensing;Earth--observations||Category:||Civil Engineering||Field:||Engineering & Technology||Issue Date:||2011||Publisher:||Spie||Source:||Proceedings of SPIE - The international society for optical engineering, 2011, Volume 8181, article number 81810T||Abstract:||Remote sensing can become a very useful tool in order to monitor coastal water quality. Economically benefits of using remote sensing techniques are obviously comparatively to the field-based monitoring because water quality can be checked daily or weekly depended on satellite overpass frequency rather than monthly as done by traditional methods which involve expensive sampling campaigns. Moreover remote sensing allows the spatial and temporal assessment of various physical, biological and ecological parameters of water bodies giving the opportunity to examine a large area by applying the suitable algorithm. This paper describes the overall methodology in order to retrieve a coastal water monitoring tool for a high risk area in Cyprus. This project is funded by the Research Promotion Foundation of Cyprus and is been developed by the Department of Civil Engineering & Geomatics, Remote Sensing Laboratory, Cyprus University of Technology in corporation with the Department of Fisheries and Marine Research in Cyprus. Firstly a time series of pigments will be done in order to determine the concentrations of the expedient parameters such as Chlorophyll, turbidity, suspended solids (SS), temperature etc at the same time of satellite overpass. At the same time in situ spectroradiometric measurements will be taken in order to retrieve the best fitted algorithm. Statistical analysis of the data will be done for the correlation of each parameter to the in situ spectroradiometric measures. Several algorithms retrieved from the in situ data are then applied to the satellite images e.g. Landsat TM/ETM+, MODIS in order to verify the suitable algorithm for each parameter. In conclusion, the overall approach is to develop regression models in which each water quality parameter will be retrieved using image, field spectroscopy, and water quality data||URI:||http://ktisis.cut.ac.cy/handle/10488/6134||ISSN:||0277-786X||DOI:||10.1117/12.898361||Rights:||© 2011 Copyright Society of Photo-Optical Instrumentation Engineers (SPIE)||Type:||Article|
|Appears in Collections:||Άρθρα/Articles|
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