IMPROVING THE ASSESSMENT OF THE ECOLOGICAL STATE OF SURFACE WATERS BY SATELLITE DATA
Abstract
The article presents the results of research into the ecological state of surface waters using newly developed scientific approaches based on the use of high spatial resolution satellite data. The systematization of all available indicators and the development of new methodological approaches significantly improves the existing methodology for determining the ecological state of water bodies, which is the goal of research. In the studies of water bodies within the city of Kyiv, Obolon Bay and Lake Verbne, the optimal set of such indicators as spectral indices was determined, which made it possible to comprehensively assess the state of water bodies: NDWI - for distinguishing vegetation and water bodies, GCI - to assess the extent of blue-green algae, NDTI - to determine turbidity, IO - to determine the presence of soluble iron in water, NDSI - to assess the extent of flooding. According to the NDSI, NDWI indices and a combination of the red and infrared channels of the Sentinel-2 L2A satellite, the flooding of the floodplain of the Irpin River was traced, caused by the destruction of a hydraulic structure near the village of Kozarovichi. Wave abrasion of the shores was studied on the example of the Kremenchuk Reservoir near the villages of Pronozivka and Mozoliivka using Landsat4 (1984) and Landsat8 (2016) satellite images. The study of the reshaping of the coastline near the village of Tsybli in the Kyiv region used the method of determining spatio-temporal changes of the coastline as a result of its erosion. The assessment of spatio-temporal changes of the coastline should be carried out taking into account the water levels on the dates of the measurements. The conducted studies established that all the identified evaluation indicators can be grouped as biological, hydro morphological, and physicochemical, and it can be concluded that methodical approaches to assessing the ecological state of surface waters using satellite data are based on established cause-and-effect relationships of processes affecting water objects.
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