Flood Inundation Depth Estimation from SAR-Based Flood Extent and DEM

Luis Moya; Erick Mas; Shunichi Koshimura

doi:10.1109/IGARSS52108.2023.10283297

Flood Inundation Depth Estimation from SAR-Based Flood Extent and DEM

Luis Moya, Erick Mas, Shunichi Koshimura

IRIDeS - Risk Evaluation and Disaster Mitigation Research Division

Pontificia Universidad Católica del Perú

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Remote sensing has been used extensively to identify the extent of floods. However, few studies have addressed the estimation of inundation depth, which would provide a deeper understanding of the affected areas. This paper reports a step-by-step application of a novel method to estimate inundation depths during a flood in Mabi town, Okayama Prefecture, Japan 2018. The method is based on the solution of a nonlinear programming problem, in which the flood extent, computed from SAR imagery, is represented as a sparse linear combination of water bodies calculated from a digital elevation model. The results show a good agreement with observations on the field survey and can be implemented in a fully automatic framework.

Original language	English
Title of host publication	IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	337-340
Number of pages	4
ISBN (Electronic)	9798350320107
DOIs	https://doi.org/10.1109/IGARSS52108.2023.10283297
Publication status	Published - 2023
Event	2023 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2023 - Pasadena, United States Duration: 2023 Jul 16 → 2023 Jul 21

Publication series

Name	International Geoscience and Remote Sensing Symposium (IGARSS)
Volume	2023-July

Conference

Conference	2023 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2023
Country/Territory	United States
City	Pasadena
Period	23/7/16 → 23/7/21

Keywords

ALOS-2
flood inundation depth
remote sensing
SAR
Sparsity

Access to Document

10.1109/IGARSS52108.2023.10283297

Cite this

Moya, L., Mas, E., & Koshimura, S. (2023). Flood Inundation Depth Estimation from SAR-Based Flood Extent and DEM. In IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, Proceedings (pp. 337-340). (International Geoscience and Remote Sensing Symposium (IGARSS); Vol. 2023-July). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IGARSS52108.2023.10283297

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title = "Flood Inundation Depth Estimation from SAR-Based Flood Extent and DEM",

abstract = "Remote sensing has been used extensively to identify the extent of floods. However, few studies have addressed the estimation of inundation depth, which would provide a deeper understanding of the affected areas. This paper reports a step-by-step application of a novel method to estimate inundation depths during a flood in Mabi town, Okayama Prefecture, Japan 2018. The method is based on the solution of a nonlinear programming problem, in which the flood extent, computed from SAR imagery, is represented as a sparse linear combination of water bodies calculated from a digital elevation model. The results show a good agreement with observations on the field survey and can be implemented in a fully automatic framework.",

keywords = "ALOS-2, flood inundation depth, remote sensing, SAR, Sparsity",

author = "Luis Moya and Erick Mas and Shunichi Koshimura",

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Moya, L, Mas, E & Koshimura, S 2023, Flood Inundation Depth Estimation from SAR-Based Flood Extent and DEM. in IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, Proceedings. International Geoscience and Remote Sensing Symposium (IGARSS), vol. 2023-July, Institute of Electrical and Electronics Engineers Inc., pp. 337-340, 2023 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2023, Pasadena, United States, 23/7/16. https://doi.org/10.1109/IGARSS52108.2023.10283297

Flood Inundation Depth Estimation from SAR-Based Flood Extent and DEM. / Moya, Luis; Mas, Erick ; Koshimura, Shunichi.
IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, Proceedings. Institute of Electrical and Electronics Engineers Inc., 2023. p. 337-340 (International Geoscience and Remote Sensing Symposium (IGARSS); Vol. 2023-July).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Moya, Luis

AU - Mas, Erick

AU - Koshimura, Shunichi

PY - 2023

Y1 - 2023

N2 - Remote sensing has been used extensively to identify the extent of floods. However, few studies have addressed the estimation of inundation depth, which would provide a deeper understanding of the affected areas. This paper reports a step-by-step application of a novel method to estimate inundation depths during a flood in Mabi town, Okayama Prefecture, Japan 2018. The method is based on the solution of a nonlinear programming problem, in which the flood extent, computed from SAR imagery, is represented as a sparse linear combination of water bodies calculated from a digital elevation model. The results show a good agreement with observations on the field survey and can be implemented in a fully automatic framework.

AB - Remote sensing has been used extensively to identify the extent of floods. However, few studies have addressed the estimation of inundation depth, which would provide a deeper understanding of the affected areas. This paper reports a step-by-step application of a novel method to estimate inundation depths during a flood in Mabi town, Okayama Prefecture, Japan 2018. The method is based on the solution of a nonlinear programming problem, in which the flood extent, computed from SAR imagery, is represented as a sparse linear combination of water bodies calculated from a digital elevation model. The results show a good agreement with observations on the field survey and can be implemented in a fully automatic framework.

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KW - Sparsity

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Moya L, Mas E , Koshimura S. Flood Inundation Depth Estimation from SAR-Based Flood Extent and DEM. In IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, Proceedings. Institute of Electrical and Electronics Engineers Inc. 2023. p. 337-340. (International Geoscience and Remote Sensing Symposium (IGARSS)). doi: 10.1109/IGARSS52108.2023.10283297

Flood Inundation Depth Estimation from SAR-Based Flood Extent and DEM

Abstract

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Keywords

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