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Earth Observation Techniques for Spatial Disaggregation of Exposure Data

Geiß, Christian and Aravena Pelizari, Patrick and Priesmeier, Peter and Soto, Angelica and Schoepfer, Elisabeth and Langbein, Michael and Riedlinger, Torsten and Santa Maria, Hernan and Gomez Zapata, Camilo and Pittore, Massimiliano and Taubenböck, Hannes (2021) Earth Observation Techniques for Spatial Disaggregation of Exposure Data. EGU General Assembly 2021, 19–30 Apr 2021, Wien, Österreich.

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Official URL: https://meetingorganizer.copernicus.org/EGU21/EGU21-8574.html

Abstract

Exposure describes elements which are imperiled by natural hazards and susceptible to damage. The affiliated vulnerability characterizes the likelihood to experience damage regarding a given level of hazard intensity. Frequently, the compilation of exposure information is the costliest component (in terms of time and labor) in risk assessment. Existing data sets and models often describe exposure in an aggregated manner, e.g., by relying on statistical/census data for given administrative entities. Nowadays, earth observation techniques allow to collect spatially continuous information for large geographic areas while enabling a high geometric and temporal resolution. In parallel, modern data interpretation tools based on Artificial Intelligence concepts enable the extraction of thematic information from such data with a high accuracy and detail. Consequently, we exploit measurements from the earth observation missions TanDEM-X and Sentinel-2, which collect data on a global scale, to characterize the built environment in terms of fundamental morphologic properties, namely built-up density and height. Subsequently, we use this information to constrain existing exposure data in a spatial disaggregation approach. Thereby, we compare different methods for disaggregation and evaluate how different resolution properties of the earth observation data affect the risk assessment result. Results are presented for the city of Santiago de Chile, Chile, which is prone to natural hazards such as earthquakes. We present loss estimations and corresponding sensivity with respect to the resolution properties of the exposure data used in the model. Thereby, it can be noted how loss estimations vary substantially and that aggregated exposure information underestimates losses in our scenarios. As such, this study underlines the benefits of deploying modern earth observation technologies for refined exposure estimation and related loss estimation.

Item URL in elib:https://elib.dlr.de/144695/
Document Type:Conference or Workshop Item (Speech)
Title:Earth Observation Techniques for Spatial Disaggregation of Exposure Data
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Geiß, ChristianChristian.Geiss (at) dlr.deUNSPECIFIED
Aravena Pelizari, PatrickPatrick.AravenaPelizari (at) dlr.deUNSPECIFIED
Priesmeier, Peterpeterpriesmeier (at) gmx.deUNSPECIFIED
Soto, Angelicaangelica_sotocal (at) hotmail.comUNSPECIFIED
Schoepfer, Elisabethelisabeth.schoepfer (at) dlr.dehttps://orcid.org/0000-0002-6496-4744
Langbein, Michaelmichael.langbein (at) dlr.deUNSPECIFIED
Riedlinger, Torstentorsten.riedlinger (at) dlr.deUNSPECIFIED
Santa Maria, Hernanhsm (at) ing.puc.clUNSPECIFIED
Gomez Zapata, Camilojcgomez (at) gfz-potsdam.deUNSPECIFIED
Pittore, Massimilianomassimiliano.pittore (at) eurac.eduUNSPECIFIED
Taubenböck, HannesHannes.Taubenboeck (at) dlr.deUNSPECIFIED
Date:2021
Refereed publication:No
Open Access:No
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Status:Published
Keywords:exposure, Sentinel-2, TanDEM-X, natural hazard, risk
Event Title:EGU General Assembly 2021
Event Location:Wien, Österreich
Event Type:international Conference
Event Dates:19–30 Apr 2021
Organizer:EGU
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: Geiß, Christian
Deposited On:02 Nov 2021 20:21
Last Modified:02 Nov 2021 20:21

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