Error-reduced digital elevation models and high-resolution land cover roughness in mapping tsunami exposure for low elevation coastal zones

Amra, Rajuli; Araki, Susumu; Geiß, Christian et al.

Remote Sensing Applications: Society and Environment, 2025, 37, 101438

Number of Access:269（2025-11-27 15:12 Counts）

Identifier to cite or link to this item: https://hdl.handle.net/11094/100391

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Title
Error-reduced digital elevation models and high-resolution land cover roughness in mapping tsunami exposure for low elevation coastal zones
Creator
CreatorName
Amra, Rajuli
NRID
1000080324804 1000080324804
researchmap permalink
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Scopus Author ID
7402411003 7402411003
CreatorName
Araki, Susumu
CreatorName
Geiß, Christian
CreatorName
Davies, Gareth
Subject
Error-reduced DEMs
Land cover roughness
Satellite-derived exposure data
Description
Amra R., Araki S., Geiß C., et al. Error-reduced digital elevation models and high-resolution land cover roughness in mapping tsunami exposure for low elevation coastal zones. Remote Sensing Applications: Society and Environment 37, 101438 (2025); https://doi.org/10.1016/j.rsase.2024.101438.
Abstract
This study presents a systematic exposure assessment by reconstructing the impact of the 2004 Indian Ocean Tsunami using a wide range of inundation scenarios and multiresolution exposure layers. To develop inundation and exposure models, we employed the error-reduced global digital elevation models (DEMs) and geospatially consistent multiresolution datasets: land cover roughness (LCR) models, built-up areas, and gridded population layers. We implemented three sequential validation assessments to evaluate the performance of inundation models, incorporating satellite observations, post-tsunami measurements, and the confidence level associated with inherent DEM error characteristics. The results demonstrated that the error-reduced variants of Copernicus DEM (i.e., FABDEM and DiluviumDEM) satisfied all reliability criteria. Incorporating these elevation models with LCR models improved the accuracy of inundation depth estimates; however, it reduced the agreement between simulated and observed inundation extents. We observed that applying high-resolution LCR models had a minimal impact on overland inundation extents but still influenced the exposure assessment, especially in high-density urban areas.
Publisher
Elsevier B.V.
Source Title
Remote Sensing Applications: Society and Environment
Volume (Issue)
37
Page
101438
Date of Issued
2025-01-01
Language
English
Handle URL
https://hdl.handle.net/11094/100391
eISSN
23529385
Relation.isIdenticalTo
DOI (Publisher Version)
https://doi.org/10.1016/j.rsase.2024.101438
Access Rights
open access
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This article is licensed under a Creative Commons Attribution 4.0 International License.
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Version of Record
Category
学術雑誌論文 Journal Article