日本リモートセンシング学会誌
Online ISSN : 1883-1184
Print ISSN : 0289-7911
ISSN-L : 0289-7911
企業事例紹介特集 事例紹介
小型SAR衛星StriXを用いた浸水解析の国内外洪水事例への適用
和智 明日香, 小澤 剛, 片桐 佑介
著者情報
ジャーナル フリー

2026 年 46 巻 3 号 p. 223-226

詳細
抄録

Synthetic Aperture Radar (SAR) satellites play a critical role in disaster response by providing all-weather, day-and-night observation capabilities. SAR is particularly valuable for flood disasters, which often occur under cloud cover and at night when optical satellites are ineffective. This paper presents the application of single-image flood inundation analysis using Synspective’s small SAR satellite “StriX” to three flood events that occurred in 2025: Kamiamakusa City in Kumamoto Prefecture, Japan (August 2025); Calbayog City in the Philippines (December 2025); and Hoi An in Vietnam (October 2025). The single-image inundation analysis method extracts inundated areas from a single SAR image without requiring pre-event archive data, making it particularly suitable for rapid disaster response and applications in regions with limited archive coverage. In Kamiamakusa, an emergency observation was conducted by StriX-3, and the entire workflow from tasking registration to delivery of the analysis report was completed within approximately three hours, with the extracted inundation areas showing distributions consistent with on-site live camera footage. In Calbayog, four consecutive observations were performed twice daily over two days, capturing the temporal evolution of inundation areas and demonstrating the value of high-frequency monitoring for evacuation and flood response decision-making. In Hoi An, the inundation map produced by StriX was compared with that from ESA’s Sentinel-1, confirming a generally consistent distribution while delivering the result the day after the event, independent of the 12-day revisit cycle. These cases demonstrate that the combination of single-image inundation analysis and the expanding StriX constellation enables rapid and reliable flood disaster response both domestically and internationally.

著者関連情報
© 2026 社団法人 日本リモートセンシング学会
前の記事 次の記事
feedback
Top