Identifying Damaged Areas Caused by the Noto Peninsula 2024 Earthquake Using Change Detection from Optical Satellite Images

Abstract. Strategic response during disasters requires the swiftness of the flow of data and information. Simple change detections can be used from Optical Satellite Images to achieve fast results that can be used for analysis and planning. In response to the earthquake that devastated the Noto Peninsula of Japan on New Year’s Day, news reports and early optical satellite images were utilized to identify areas that were damaged by the earthquake. The changes in the reflectance values and indicators, such as NDBI and NDVI were analyzed to identify the areas with damages such as collapsed buildings and landslides. From the after-event satellite images of PlanetScope and Sentinel-2, three areas were identified as severely affected based on news reports namely, Wajima City, Niemachi, and Noto Town. To verify the results of the analysis, aerial images provided by the Geographical Survey Institute of Japan, and Google Earth Street View Images were used. Through change detection methods, the locations of damaged areas were pinpointed using Optical Satellite Images after the earthquake incident.

Authors

Institutions

Publication Details

Journal
ISPRS annals of the photogrammetry, remote sensing and spatial information sciences
Published
2024-11-04
DOI
https://doi.org/10.5194/isprs-annals-x-3-2024-277-2024
Primary Topic
Remote-Sensing Image Classification
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Identifying Damaged Areas Caused by the Noto Peninsula 2024 Earthquake Using Change Detection from Optical Satellite Images

Fritz Rhaem M. Olivar, Rosalie Reyes, Masahiko Nagai
ISPRS annals of the photogrammetry, remote sensing and spatial information sciences
Remote-Sensing Image Classification
article

Identifying Damaged Areas Caused by the Noto Peninsula 2024 Earthquake Using Change Detection from Optical Satellite Images

Fritz Rhaem M. Olivar, Rosalie Reyes, Masahiko Nagai
article en

Abstract

Abstract. Strategic response during disasters requires the swiftness of the flow of data and information. Simple change detections can be used from Optical Satellite Images to achieve fast results that can be used for analysis and planning. In response to the earthquake that devastated the Noto Peninsula of Japan on New Year’s Day, news reports and early optical satellite images were utilized to identify areas that were damaged by the earthquake. The changes in the reflectance values and indicators, such as NDBI and NDVI were analyzed to identify the areas with damages such as collapsed buildings and landslides. From the after-event satellite images of PlanetScope and Sentinel-2, three areas were identified as severely affected based on news reports namely, Wajima City, Niemachi, and Noto Town. To verify the results of the analysis, aerial images provided by the Geographical Survey Institute of Japan, and Google Earth Street View Images were used. Through change detection methods, the locations of damaged areas were pinpointed using Optical Satellite Images after the earthquake incident.

ISPRS annals of the photogrammetry, remote sensing and spatial information sciencesVol. X-3-2024
Yamaguchi University (JP), University of the Philippines Diliman (PH)
Climate action, Sustainable cities and communities
Openalex Percentile: Top 70%
Remote-Sensing Image Classification
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Identifying Damaged Areas Caused by the Noto Peninsula 2024 Earthquake Using Change Detection from Optical Satellite Images — Fritz Rhaem M. Olivar, Rosalie Reyes, et al. · ISPRS annals of the photogrammetry, remote sensing and spatial information sciences (2024) | TGRS Research Map | TGRS