Sentinel-1 and -2 Based near Real Time Inland Excess Water Mapping for Optimized Water Management

Changing climate is expected to cause more extreme weather patterns in many parts of the world. In the Carpathian Basin, it is expected that the frequency of intensive precipitation will increase causing inland excess water (IEW) in parts of the plains more frequently, while currently the phenomenon...

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Main Authors: Boudewijn van Leeuwen, Zalán Tobak, Ferenc Kovács
Format: Article
Language:English
Published: MDPI AG 2020-04-01
Series:Sustainability
Subjects:
Online Access:https://www.mdpi.com/2071-1050/12/7/2854
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spelling doaj-c57f9954fd404e2d96a1a251c9dab9052020-11-25T02:28:55ZengMDPI AGSustainability2071-10502020-04-01122854285410.3390/su12072854Sentinel-1 and -2 Based near Real Time Inland Excess Water Mapping for Optimized Water ManagementBoudewijn van Leeuwen0Zalán Tobak1Ferenc Kovács2Department of Physical Geography and Geoinformatics, University of Szeged, Egyetem u. 2-6, H-6722 Szeged, HungaryDepartment of Physical Geography and Geoinformatics, University of Szeged, Egyetem u. 2-6, H-6722 Szeged, HungaryDepartment of Physical Geography and Geoinformatics, University of Szeged, Egyetem u. 2-6, H-6722 Szeged, HungaryChanging climate is expected to cause more extreme weather patterns in many parts of the world. In the Carpathian Basin, it is expected that the frequency of intensive precipitation will increase causing inland excess water (IEW) in parts of the plains more frequently, while currently the phenomenon already causes great damage. This research presents and validates a new methodology to determine the extent of these floods using a combination of passive and active remote sensing data. The method can be used to monitor IEW over large areas in a fully automated way based on freely available Sentinel-1 and Sentinel-2 remote sensing imagery. The method is validated for two IEW periods in 2016 and 2018 using high-resolution optical satellite data and aerial photographs. Compared to earlier remote sensing data-based methods, our method can be applied under unfavorite weather conditions, does not need human interaction and gives accurate results for inundations larger than 1000 m<sup>2</sup>. The overall accuracy of the classification exceeds 99%; however, smaller IEW patches are underestimated due to the spatial resolution of the input data. Knowledge on the location and duration of the inundations helps to take operational measures against the water but is also required to determine the possibilities for storage of water for dry periods. The frequent monitoring of the floods supports sustainable water management in the area better than the methods currently employed.https://www.mdpi.com/2071-1050/12/7/2854inland excess waterfloodwater managementradar remote sensingoptical remote sensingautomation
collection DOAJ
language English
format Article
sources DOAJ
author Boudewijn van Leeuwen
Zalán Tobak
Ferenc Kovács
spellingShingle Boudewijn van Leeuwen
Zalán Tobak
Ferenc Kovács
Sentinel-1 and -2 Based near Real Time Inland Excess Water Mapping for Optimized Water Management
Sustainability
inland excess water
flood
water management
radar remote sensing
optical remote sensing
automation
author_facet Boudewijn van Leeuwen
Zalán Tobak
Ferenc Kovács
author_sort Boudewijn van Leeuwen
title Sentinel-1 and -2 Based near Real Time Inland Excess Water Mapping for Optimized Water Management
title_short Sentinel-1 and -2 Based near Real Time Inland Excess Water Mapping for Optimized Water Management
title_full Sentinel-1 and -2 Based near Real Time Inland Excess Water Mapping for Optimized Water Management
title_fullStr Sentinel-1 and -2 Based near Real Time Inland Excess Water Mapping for Optimized Water Management
title_full_unstemmed Sentinel-1 and -2 Based near Real Time Inland Excess Water Mapping for Optimized Water Management
title_sort sentinel-1 and -2 based near real time inland excess water mapping for optimized water management
publisher MDPI AG
series Sustainability
issn 2071-1050
publishDate 2020-04-01
description Changing climate is expected to cause more extreme weather patterns in many parts of the world. In the Carpathian Basin, it is expected that the frequency of intensive precipitation will increase causing inland excess water (IEW) in parts of the plains more frequently, while currently the phenomenon already causes great damage. This research presents and validates a new methodology to determine the extent of these floods using a combination of passive and active remote sensing data. The method can be used to monitor IEW over large areas in a fully automated way based on freely available Sentinel-1 and Sentinel-2 remote sensing imagery. The method is validated for two IEW periods in 2016 and 2018 using high-resolution optical satellite data and aerial photographs. Compared to earlier remote sensing data-based methods, our method can be applied under unfavorite weather conditions, does not need human interaction and gives accurate results for inundations larger than 1000 m<sup>2</sup>. The overall accuracy of the classification exceeds 99%; however, smaller IEW patches are underestimated due to the spatial resolution of the input data. Knowledge on the location and duration of the inundations helps to take operational measures against the water but is also required to determine the possibilities for storage of water for dry periods. The frequent monitoring of the floods supports sustainable water management in the area better than the methods currently employed.
topic inland excess water
flood
water management
radar remote sensing
optical remote sensing
automation
url https://www.mdpi.com/2071-1050/12/7/2854
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AT zalantobak sentinel1and2basednearrealtimeinlandexcesswatermappingforoptimizedwatermanagement
AT ferenckovacs sentinel1and2basednearrealtimeinlandexcesswatermappingforoptimizedwatermanagement
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