Comprehensive study of the damage assessment using coherence and land cover map by satellite SAR data

T. Nonaka; T. Asaka

doi:10.1117/12.3031495

18 November 2024 Comprehensive study of the damage assessment using coherence and land cover map by satellite SAR data

T. Nonaka, T. Asaka

Proceedings Volume 13195, Microwave Remote Sensing: Data Processing and Applications III; 131950M (2024) https://doi.org/10.1117/12.3031495
Event: Remote Sensing, 2024, Edinburgh, United Kingdom

Conference Poster

Abstract

This study discusses the versatility of a method developed by the authors that uses pre- and post-disaster SAR data to accurately assess the building damaged areas during a large-scale earthquake. After reviewing the outline of the method, we report the results of applying it to the Noto Peninsula earthquake that occurred in January 2024 and evaluating the extent of damage at the municipal level. Three combinations of paired data acquired by L-band ALOS-2 PALSAR-2 and C-band Sentinel-1 C-SAR were used to calculate the coherence. Seven municipalities near the epicenter in Ishikawa Prefecture were targeted, and building damage rate, which indicate the ratio of completely destroyed buildings to the total number of buildings, were calculated from data published by the prefecture. The urban areas were then extracted from the coherence using the land cover, and average coherence in each municipality was compared with the damage rate. The result showed that although the coherence was greater or less depending on the combination, there was a significant negative correlation between the average coherence and the damage rate in all combinations. Our finding indicated that the proposed coherence-based method was effective in assessing damage at the municipal level.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

T. Nonaka and T. Asaka "Comprehensive study of the damage assessment using coherence and land cover map by satellite SAR data", Proc. SPIE 13195, Microwave Remote Sensing: Data Processing and Applications III, 131950M (18 November 2024); https://doi.org/10.1117/12.3031495

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