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An automated approach to estimate large-scale flood volumes based on SAR satellite imagery and different DEMs - a risk management support

Baumhoer, Celia (2017) An automated approach to estimate large-scale flood volumes based on SAR satellite imagery and different DEMs - a risk management support. Master's, Rheinische Friedrich-Wilhelms-Universität Bonn.

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Abstract

Flood volume estimates provide valuable information for flood risk management applications. Up to now, quick volume estimates for large-scale areas are rare as hydraulic models require complex parameterization and GRACE (Gravity Recovery and Climate Experiment) gravity measurements deliver estimates on basin-scale. A new approach is taken to develop a novel flood volume estimation method for large-scale areas based on globally available and open access earth observation data. For this approach, an automatically derived water mask from SAR imagery is combined with a digital elevation model to estimate water levels for areas of horizontal water surface. A slope-dependent tiling algorithm and a threshold for flood and non-flood pixel separation allow accurate calculation of water levels. Model performance is assessed by in situ gauge and altimeter measurements for two study sites along the rivers Mekong and Brahmaputra. The results show consistency with validation data and support the transferability potential of the proposed algorithm. With regard to risk management this simple, quick and globally applicable model demonstrates major advantages compared to common approaches and allows new implementations of large-scale flood volume information in time-critical situations.

Item URL in elib:https://elib.dlr.de/114133/
Document Type:Thesis (Master's)
Title:An automated approach to estimate large-scale flood volumes based on SAR satellite imagery and different DEMs - a risk management support
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Baumhoer, CeliaCelia.Baumhoer (at) dlr.deUNSPECIFIED
Date:2017
Refereed publication:No
Open Access:No
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Number of Pages:97
Status:Published
Keywords:Hochwasser, SAR, large-scale, flood
Institution:Rheinische Friedrich-Wilhelms-Universität Bonn
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Erdbeobachtung
DLR - Research theme (Project):R - Remote sensing and geoscience
Location: Oberpfaffenhofen
Institutes and Institutions:German Remote Sensing Data Center > Geo Risks and Civil Security
Deposited By: Baumhoer, Celia
Deposited On:19 Oct 2017 12:13
Last Modified:19 Oct 2017 12:13

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