Use of Sentinel-2 images for the detection of sandbars along the Lower Vistula

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 river with the use of Sentinel-2 Level 2A optical images. Material and methods: The analyses were performed in QGIS (version 2.18.4) and SNAP (version 7.0) s...

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Main Authors: Klaudia Oktawia Kryniecka, Artur Magnuszewski
Format: Article
Language:English
Published: University of Agriculture in Krakow 2020-09-01
Series:Acta Scientiarum Polonorum. Formatio Circumiectus
Subjects:
Online Access:http://acta.urk.edu.pl/USE-OF-SENTINEL-2-IMAGES-FOR-THE-DETECTION-OF-SANDBARS-ALONG-THE-LOWER-VISTULA,124707,0,2.html
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author Klaudia Oktawia Kryniecka
Artur Magnuszewski
author_facet Klaudia Oktawia Kryniecka
Artur Magnuszewski
author_sort Klaudia Oktawia Kryniecka
collection DOAJ
description 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 river with the use of Sentinel-2 Level 2A optical images. Material and methods: The analyses were performed in QGIS (version 2.18.4) and SNAP (version 7.0) software. Both the image reprogramming and pixel value analysis were conducted in the SNAP. 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.In the case of 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 had different results. The difference may be reduced by improving different threshold value algorithm.
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spelling doaj-art-20d0aeb8c258443eb3ab838d20127c9d2025-01-02T10:22:10ZengUniversity of Agriculture in KrakowActa Scientiarum Polonorum. Formatio Circumiectus1644-07652020-09-011922333https://doi.org/10.15576/ASP.FC/2020.19.2.23Use of Sentinel-2 images for the detection of sandbars along the Lower VistulaKlaudia Oktawia Kryniecka 0Artur Magnuszewski 1Uniwersytet WarszawskiUniwersytet WarszawskiAim 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 river with the use of Sentinel-2 Level 2A optical images. Material and methods: The analyses were performed in QGIS (version 2.18.4) and SNAP (version 7.0) software. Both the image reprogramming and pixel value analysis were conducted in the SNAP. 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.In the case of 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 had different results. The difference may be reduced by improving different threshold value algorithm.http://acta.urk.edu.pl/USE-OF-SENTINEL-2-IMAGES-FOR-THE-DETECTION-OF-SANDBARS-ALONG-THE-LOWER-VISTULA,124707,0,2.htmlsentinel-2water indicesndwisandbarsswm
spellingShingle Klaudia Oktawia Kryniecka
Artur Magnuszewski
Use of Sentinel-2 images for the detection of sandbars along the Lower Vistula
Acta Scientiarum Polonorum. Formatio Circumiectus
sentinel-2
water indices
ndwi
sandbars
swm
title Use of Sentinel-2 images for the detection of sandbars along the Lower Vistula
title_full Use of Sentinel-2 images for the detection of sandbars along the Lower Vistula
title_fullStr Use of Sentinel-2 images for the detection of sandbars along the Lower Vistula
title_full_unstemmed Use of Sentinel-2 images for the detection of sandbars along the Lower Vistula
title_short Use of Sentinel-2 images for the detection of sandbars along the Lower Vistula
title_sort use of sentinel 2 images for the detection of sandbars along the lower vistula
topic sentinel-2
water indices
ndwi
sandbars
swm
url http://acta.urk.edu.pl/USE-OF-SENTINEL-2-IMAGES-FOR-THE-DETECTION-OF-SANDBARS-ALONG-THE-LOWER-VISTULA,124707,0,2.html
work_keys_str_mv AT klaudiaoktawiakryniecka useofsentinel2imagesforthedetectionofsandbarsalongthelowervistula
AT arturmagnuszewski useofsentinel2imagesforthedetectionofsandbarsalongthelowervistula