<abstract xmlns="http://www.w3.org/1999/xhtml">Results of research of the identification of flooding as a result of groundwater table fluctuations on the example of the valley of the River Vistula, with the use of multi-spectral Sentinel-2 images from the years 2017–2018 are presented. An analysis of indexes of water use, calculated on the basis of green, red and shortwave infrared (SWIR) bands, for extraction of water objects and flooded areas was carried out. Based on the analyses conducted, a mapping method was developed, using three water indexes (MNDWI Modified Normalised Difference Water Index, NDTI Normalised Difference Index and NDPI Normalised Difference Pond Index). Results show that the 10 metre false colour composite RNDTIGNDPIBMNDWI obtained significantly improved submerged extractions more than did individual water indexes. Moreover, the 10-m-images of MNDWI and NDPI, obtained by the sharpening High Pass Filter (HPF), may represent more detailed spatial information on floods than the 20-m-MNDWI and NDPI, obtained from original images.</abstract>

Results of research of the identification of flooding as a result of groundwater table fluctuations on the example of the valley of the River Vistula, with the use of multi-spectral Sentinel-2 images from the years 2017–2018 are presented. An analysis of indexes of water use, calculated on the basis of green, red and shortwave infrared (SWIR) bands, for extraction of water objects and flooded areas was carried out. Based on the analyses conducted, a mapping method was developed, using three water indexes (MNDWI Modified Normalised Difference Water Index, NDTI Normalised Difference Index and NDPI Normalised Difference Pond Index). Results show that the 10 metre false colour composite RNDTIGNDPIBMNDWI obtained significantly improved submerged extractions more than did individual water indexes. Moreover, the 10-m-images of MNDWI and NDPI, obtained by the sharpening High Pass Filter (HPF), may represent more detailed spatial information on floods than the 20-m-MNDWI and NDPI, obtained from original images.

An analysis of flooding coverage using remote sensing within the context of risk assessment

Polish Geological Institute – National Research Institute, Department of Hydrogeology and Environmental Geology

Geologos

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Results of research of the identification of flooding as a result of groundwater table fluctuations on the example of the valley of the River Vistula, with the...

An analysis of flooding coverage using remote sensing within the context of risk assessment

Online veröffentlicht: 31. Dez. 2019

Seitenbereich: 241 - 248

Eingereicht: 04. März 2019

Akzeptiert: 22. Aug. 2019

DOI: https://doi.org/10.2478/logos-2019-0026

Schlüsselwörter
Sentinel-2, Remote Sensing, flood mapping, Water Indexes

© 2019 Tatiana Solovey, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

An analysis of flooding coverage using remote sensing within the context of risk assessment

Online veröffentlicht: 31. Dez. 2019

Seitenbereich: 241 - 248

Eingereicht: 04. März 2019

Akzeptiert: 22. Aug. 2019

DOI: https://doi.org/10.2478/logos-2019-0026

SchlüsselwörterSentinel-2, Remote Sensing, flood mapping, Water Indexes

© 2019 Tatiana Solovey, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Schlüsselwörter
Sentinel-2, Remote Sensing, flood mapping, Water Indexes