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Re-learning observed flood extents can improve remote sensing products

Brill, Fabio and Schlaffer, Stefan and Martinis, Sandro and Schröter, Kai and Kraibich, Heidi (2021) Re-learning observed flood extents can improve remote sensing products. In: Second International Conference on Natural Hazards and Risks in a Changing World 2021. Second International Conference on Natural Hazards and Risks in a Changing World 2021, Potsdam.

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Abstract

Flood extent data is critical for both response action and subsequent impact modelling. Satellite-based emergency mapping products typically exhibit low sensitivity in vegetated and urban areas, though. As the information content of spaceborne sensor data is limited in these areas, e.g. due to shadow and overlay effects, advances in processing can primarily reduce overdetection, but hardly avoid underdetection. We present a novel procedure of re-learning the observed flood extent from different features (i.e. not derived from sensor data) using a one-class classifier (OCC). This allows us to treat the entire flood mask as training region, and extrapolate into unobservable areas. The approach was tested for hurricane Harvey in Houston, where three satellite-based flood masks of varying quality were available to us, as well as a 50 cm resolution aerial image for validation. An assessment of the initial masks showed that the standard emergency mapping product effectively detected only open water, while the high quality products detected about 40% flooded urban areas. All of these products could be improved by our presented modelling approach, with the best models raising the k score by 0.2 (high quality product) to 0.7 (standard product).

Item URL in elib:https://elib.dlr.de/144729/
Document Type:Conference or Workshop Item (Poster)
Title:Re-learning observed flood extents can improve remote sensing products
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Brill, FabioGeoforschungszentrum PotsdamUNSPECIFIED
Schlaffer, Stefanstefan.schlaffer (at) geo.tuwien.ac.atUNSPECIFIED
Martinis, Sandrosandro.martinis (at) dlr.dehttps://orcid.org/0000-0002-6400-361X
Schröter, KaiGeoforschungszentrum PotsdamUNSPECIFIED
Kraibich, HeidiGeoforschungszentrum PotsdamUNSPECIFIED
Date:2021
Journal or Publication Title:Second International Conference on Natural Hazards and Risks in a Changing World 2021
Refereed publication:No
Open Access:No
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Status:Published
Keywords:Flood, SAR, one-class classifier
Event Title:Second International Conference on Natural Hazards and Risks in a Changing World 2021
Event Location:Potsdam
Event Type:international Conference
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Earth Observation
DLR - Research theme (Project):R - Remote Sensing and Geo Research
Location: Oberpfaffenhofen
Institutes and Institutions:German Remote Sensing Data Center > Geo Risks and Civil Security
Deposited By: Martinis, Sandro
Deposited On:02 Nov 2021 20:32
Last Modified:02 Nov 2021 20:32

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