FLOMPY: An Open-Source Toolbox for Floodwater Mapping Using Sentinel-1 Intensity Time Series

A new automatic, free and open-source python toolbox for the mapping of floodwater is presented. The output of the toolbox is a binary mask of floodwater at a user-specified time point within geographical boundaries. It exploits the high spatial (10m) and temporal (6 days per orbit over Europe) reso...

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Autores principales:	Kleanthis Karamvasis, Vassilia Karathanassi
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	flooding time series Sentinel-1 thresholding open-source software Hydraulic engineering TC1-978 Water supply for domestic and industrial purposes TD201-500
Acceso en línea:	https://doaj.org/article/7bfde5b7ffea44d59adb580ead3a395e
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id	oai:doaj.org-article:7bfde5b7ffea44d59adb580ead3a395e
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spelling	oai:doaj.org-article:7bfde5b7ffea44d59adb580ead3a395e2021-11-11T19:52:15ZFLOMPY: An Open-Source Toolbox for Floodwater Mapping Using Sentinel-1 Intensity Time Series10.3390/w132129432073-4441https://doaj.org/article/7bfde5b7ffea44d59adb580ead3a395e2021-10-01T00:00:00Zhttps://www.mdpi.com/2073-4441/13/21/2943https://doaj.org/toc/2073-4441A new automatic, free and open-source python toolbox for the mapping of floodwater is presented. The output of the toolbox is a binary mask of floodwater at a user-specified time point within geographical boundaries. It exploits the high spatial (10m) and temporal (6 days per orbit over Europe) resolution of Sentinel-1 GRD intensity time series and is based on four processing steps. In the first step, a selection of Sentinel-1 images related to pre-flood (baseline) state and flood state is performed. In the second step, the preprocessing of the selected images is performed in order to create a co-registered stack with all the pre-flood and flood images. In the third step, a statistical temporal analysis is performed and a <i>t</i>-score map that represents the changes due to a flood event is calculated. Finally, in the fourth step, a classification procedure based on the <i>t</i>-score map is performed to extract the final flood map. A thorough analysis based on several flood events is presented to demonstrate the main benefits, limitations and the potential of the proposed methodology. The validation was performed using Copernicus Emergency Management Service (EMS) products. In all case studies, overall accuracies were higher than 0.95 with Kappa scores higher than 0.76. We believe that the end-user community can benefit by exploiting the flood maps of the proposed methodological pipeline by using the provided open-source toolbox.Kleanthis KaramvasisVassilia KarathanassiMDPI AGarticlefloodingtime seriesSentinel-1thresholdingopen-source softwareHydraulic engineeringTC1-978Water supply for domestic and industrial purposesTD201-500ENWater, Vol 13, Iss 2943, p 2943 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	flooding time series Sentinel-1 thresholding open-source software Hydraulic engineering TC1-978 Water supply for domestic and industrial purposes TD201-500
spellingShingle	flooding time series Sentinel-1 thresholding open-source software Hydraulic engineering TC1-978 Water supply for domestic and industrial purposes TD201-500 Kleanthis Karamvasis Vassilia Karathanassi FLOMPY: An Open-Source Toolbox for Floodwater Mapping Using Sentinel-1 Intensity Time Series
description	A new automatic, free and open-source python toolbox for the mapping of floodwater is presented. The output of the toolbox is a binary mask of floodwater at a user-specified time point within geographical boundaries. It exploits the high spatial (10m) and temporal (6 days per orbit over Europe) resolution of Sentinel-1 GRD intensity time series and is based on four processing steps. In the first step, a selection of Sentinel-1 images related to pre-flood (baseline) state and flood state is performed. In the second step, the preprocessing of the selected images is performed in order to create a co-registered stack with all the pre-flood and flood images. In the third step, a statistical temporal analysis is performed and a <i>t</i>-score map that represents the changes due to a flood event is calculated. Finally, in the fourth step, a classification procedure based on the <i>t</i>-score map is performed to extract the final flood map. A thorough analysis based on several flood events is presented to demonstrate the main benefits, limitations and the potential of the proposed methodology. The validation was performed using Copernicus Emergency Management Service (EMS) products. In all case studies, overall accuracies were higher than 0.95 with Kappa scores higher than 0.76. We believe that the end-user community can benefit by exploiting the flood maps of the proposed methodological pipeline by using the provided open-source toolbox.
format	article
author	Kleanthis Karamvasis Vassilia Karathanassi
author_facet	Kleanthis Karamvasis Vassilia Karathanassi
author_sort	Kleanthis Karamvasis
title	FLOMPY: An Open-Source Toolbox for Floodwater Mapping Using Sentinel-1 Intensity Time Series
title_short	FLOMPY: An Open-Source Toolbox for Floodwater Mapping Using Sentinel-1 Intensity Time Series
title_full	FLOMPY: An Open-Source Toolbox for Floodwater Mapping Using Sentinel-1 Intensity Time Series
title_fullStr	FLOMPY: An Open-Source Toolbox for Floodwater Mapping Using Sentinel-1 Intensity Time Series
title_full_unstemmed	FLOMPY: An Open-Source Toolbox for Floodwater Mapping Using Sentinel-1 Intensity Time Series
title_sort	flompy: an open-source toolbox for floodwater mapping using sentinel-1 intensity time series
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/7bfde5b7ffea44d59adb580ead3a395e
work_keys_str_mv	AT kleanthiskaramvasis flompyanopensourcetoolboxforfloodwatermappingusingsentinel1intensitytimeseries AT vassiliakarathanassi flompyanopensourcetoolboxforfloodwatermappingusingsentinel1intensitytimeseries
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FLOMPY: An Open-Source Toolbox for Floodwater Mapping Using Sentinel-1 Intensity Time Series

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