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USE OF SENTINEL-2 IMAGES FOR THE DETECTION OF SANDBARS ALONG THE LOWER VISTULA.

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Titel: USE OF SENTINEL-2 IMAGES FOR THE DETECTION OF SANDBARS ALONG THE LOWER VISTULA.
Alternate Title: WYKORZYSTANIE ZDJĘĆ SENTINEL-2 DO DETEKCJI WYSP RZECZNYCH NA DOLNEJ WIŚLE. (Polish)
Autoren: Kryniecka, Klaudia, Magnuszewski, Artur
Quelle: Acta Scientiarum Polonorum. Formatio Circumiectus; 2020, Vol. 19 Issue 2, p23-33, 11p
Schlagwörter: SAND bars, RIVER channels, WATER, OPTICAL images, SURFACE analysis, MULTISPECTRAL imaging
Abstract (English): Aim of the study The aim of this paper was to develop and test detection methods of sandbars for a selected section of the Lower Vistula (Wisła) river with the use of Sentinel-2 Level 2A optical images. Material and methods The analyses were performed in the QGIS (version 2.18.4) and SNAP (version 7.0) software. Both the image reprogramming and pixel value analysis were conducted in the SNAP software. QGIS was used to perform activities involving the remainder of the work, such as steps with satellite data, i.e. processing, surface analysis, and their visualisation. For multispectral images, water indices were used such as: NDWI (Normalized Difference Water Index); MNDWI (Modified Normalized Difference Water Index); AWEIsh (Automated Water Extraction Index shadow); AWEInsh (Automated Water Extraction Index no shadow); LSWI (Land Surface Water Index); MLSWI (Modified Land Surface Water Index); MSI (Moisture Stress Index); SWM (Sentinel Water Mask) to separate sandbars from a water. These index methods base on a threshold value. Not all tested indices provided satisfactory results. Therefore, the layers were generated for 5 water indices. Results and conclusions The analyses have shown that, for the selected section of the Lower Vistula, it is possible to detect sandbars in the river channel on the basis of Sentinel-2 satellite's data. A proper selection of remote sensing index, creation of binary classification and selection of processing algorithm are important when detecting river islands. Every water index used produced different results. The difference may be reduced by improving the threshold value algorithm. [ABSTRACT FROM AUTHOR]
Abstract (Polish): Cel pracy Opracowanie i przetestowanie metody detekcji form korytowych na wybranym odcinku dolnej Wisły. Do przeprowadzenia badań wykorzystano archiwalne, powszechnie dostępne obrazy satelitarne Sentinel-2. Problemem badawczym jest optymalizacja narzędzi, danych retrospektywnych oraz wybór stosownych istniejących wskaźników teledetekcyjnych służących do wykrywania wód śródlądowych i przybrzeżnych na obrazach satelitarnych Sentinel-2. Materiał i metody Analizy przeprowadzono w oprogramowaniu QGIS (wersja 2.18.4) oraz SNAP (wersja 7.0). W oprogramowaniu SNAP wykonano przepróbkowanie obrazów oraz analizę wartości pikseli. Natomiast w oprogramowaniu QGIS wykonano działania należące do reszty etapów pracy z danymi satelitarnymi, tj. przetworzeń, analizy powierzchni oraz ich wizualizacji. Wyniki i wnioski Wykonane w niniejszej pracy badania w biegu analizowanego odcinka dolnej Wisły wykazały, ze możliwe jest wykrycie form korytowych w rzece na podstawie danych satelitarnych Sentinel-2. Duże znaczenie przy detekcji wysp rzecznych ma odpowiedni dobór wskaźnika teledetekcyjnego, utworzenie binarnej klasyfikacji oraz dobór algorytmu przetworzeń. [ABSTRACT FROM AUTHOR]
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Datenbank: Complementary Index
Beschreibung
Abstract:Aim of the study The aim of this paper was to develop and test detection methods of sandbars for a selected section of the Lower Vistula (Wisła) river with the use of Sentinel-2 Level 2A optical images. Material and methods The analyses were performed in the QGIS (version 2.18.4) and SNAP (version 7.0) software. Both the image reprogramming and pixel value analysis were conducted in the SNAP software. QGIS was used to perform activities involving the remainder of the work, such as steps with satellite data, i.e. processing, surface analysis, and their visualisation. For multispectral images, water indices were used such as: NDWI (Normalized Difference Water Index); MNDWI (Modified Normalized Difference Water Index); AWEIsh (Automated Water Extraction Index shadow); AWEInsh (Automated Water Extraction Index no shadow); LSWI (Land Surface Water Index); MLSWI (Modified Land Surface Water Index); MSI (Moisture Stress Index); SWM (Sentinel Water Mask) to separate sandbars from a water. These index methods base on a threshold value. Not all tested indices provided satisfactory results. Therefore, the layers were generated for 5 water indices. Results and conclusions The analyses have shown that, for the selected section of the Lower Vistula, it is possible to detect sandbars in the river channel on the basis of Sentinel-2 satellite's data. A proper selection of remote sensing index, creation of binary classification and selection of processing algorithm are important when detecting river islands. Every water index used produced different results. The difference may be reduced by improving the threshold value algorithm. [ABSTRACT FROM AUTHOR]
ISSN:16440765
DOI:10.15576/asp.fc/2020.19.2.23