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; Davies, Gareth

doi:https://doi.org/10.1016/j.rsase.2024.101438

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

アクセス数:222件（2025-07-27 07:05 集計）

固定URL: https://hdl.handle.net/11094/100391

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タイトル	Error-reduced digital elevation models and high-resolution land cover roughness in mapping tsunami exposure for low elevation coastal zones
著者	著者名 Amra, Rajuli
	NRID 1000080324804 1000080324804 researchmap permalink read0054762 read0054762 Scopus Author ID 7402411003 7402411003 著者名 Araki, Susumu
	著者名 Geiß, Christian
	著者名 Davies, Gareth
キーワード等	Error-reduced DEMs
	Land cover roughness
	Satellite-derived exposure data
内容	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.
抄録	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.
出版者	Elsevier B.V.
収録物名	Remote Sensing Applications: Society and Environment
巻(号)	37
ページ	101438
刊行年月	2025-01-01
言語	英語
ハンドルURL	https://hdl.handle.net/11094/100391
eISSN	23529385
関連情報 (isIdenticalTo)	DOI (出版社版) https://doi.org/10.1016/j.rsase.2024.101438
アクセス権	open access
権利情報	This article is licensed under a Creative Commons Attribution 4.0 International License.
出版タイプ	Version of Record
カテゴリ	学術雑誌論文 Journal Article

資源タイプ	学術雑誌論文
ローカル資源タイプ	学術雑誌論文
DCTERMS.bibliographicCitation	Remote Sensing Applications: Society and Environment. 2025, 37, p. 101438
DC.title	Error-reduced digital elevation models and high-resolution land cover roughness in mapping tsunami exposure for low elevation coastal zones
DC.creator	Amra, Rajuli
	Araki, Susumu
	Geiß, Christian
	Davies, Gareth
DC.publisher	Elsevier B.V.
DC.language' scheme='DCTERMS.RFC1766	英語
DCTERMS.issued' scheme='DCTERMS.W3CDTF	2025-01-01
DC.identifier	https://doi.org/10.1016/j.rsase.2024.101438
DC.subject	Error-reduced DEMs
	Land cover roughness
	Satellite-derived exposure data
DC.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.
DCTERMS.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.
DC.rights	This article is licensed under a Creative Commons Attribution 4.0 International License.
DC.format	100391
citation_title	Error-reduced digital elevation models and high-resolution land cover roughness in mapping tsunami exposure for low elevation coastal zones
citation_author	Amra, Rajuli
	Araki, Susumu
	Geiß, Christian
	Davies, Gareth
citation_publisher	Elsevier B.V.
citation_language	英語
citation_date	2025-01-01
citation_journal_title	Remote Sensing Applications: Society and Environment
citation_volume	37
citation_firstpage	101438
citation_doi	https://doi.org/10.1016/j.rsase.2024.101438
citation_public_url	https://hdl.handle.net/11094/100391

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

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