Simulating SAR constellations systems for rapid damage mapping in urban areas: Case study of the 2023 Turkey-Syria earthquake

IF 7.6 Q1 REMOTE SENSING
Riccardo Vitale , Pietro Milillo
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引用次数: 0

Abstract

This study evaluates the feasibility of using Synthetic Aperture Radar (SAR) constellations for rapid damage mapping in the aftermath of the 2023 Turkey-Syria earthquake. We specifically address the data acquisition latency challenges associated with X- and L-Band SAR constellations, including those operated by U.S. Capella Space, UMBRA Space, European ICEYE, and the Italian/Argentinian SIASGE constellation. Our analysis compares these constellations’ response times with established damage mapping techniques from open-access ESA Sentinel-1A/B and NASA NISAR missions. By integrating USGS shake maps with existing building maps, we demonstrate that the shorter revisit times and higher spatial resolutions of X-band SAR constellations can produce damage maps within hours, complementing the longer-term data provided by ESA and NASA missions. This research highlights the strengths and limitations of both approaches, emphasizing their roles in enhancing earthquake reconnaissance and damage detection efforts.
模拟合成孔径雷达星座系统,用于快速绘制城市地区的破坏地图:2023 年土耳其-叙利亚地震案例研究
本研究评估了在 2023 年土耳其-叙利亚地震后使用合成孔径雷达 (SAR) 星群快速绘制破坏地图的可行性。我们特别讨论了与 X 波段和 L 波段合成孔径雷达星座相关的数据采集延迟挑战,包括由美国 Capella Space、UMBRA Space、欧洲 ICEYE 和意大利/阿根廷 SIASGE 星座运营的星座。我们的分析将这些星座的响应时间与开放访问的欧空局哨兵-1A/B 和美国国家航空航天局 NISAR 任务的成熟破坏测绘技术进行了比较。通过将美国地质调查局的震动地图与现有的建筑物地图进行整合,我们证明了 X 波段合成孔径雷达星座较短的重访时间和较高的空间分辨率可以在数小时内绘制出破坏地图,从而对欧空局和 NASA 任务提供的较长期数据起到补充作用。这项研究突出了这两种方法的优势和局限性,强调了它们在加强地震侦察和破坏探测工作中的作用。
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来源期刊
International journal of applied earth observation and geoinformation : ITC journal
International journal of applied earth observation and geoinformation : ITC journal Global and Planetary Change, Management, Monitoring, Policy and Law, Earth-Surface Processes, Computers in Earth Sciences
CiteScore
12.00
自引率
0.00%
发文量
0
审稿时长
77 days
期刊介绍: The International Journal of Applied Earth Observation and Geoinformation publishes original papers that utilize earth observation data for natural resource and environmental inventory and management. These data primarily originate from remote sensing platforms, including satellites and aircraft, supplemented by surface and subsurface measurements. Addressing natural resources such as forests, agricultural land, soils, and water, as well as environmental concerns like biodiversity, land degradation, and hazards, the journal explores conceptual and data-driven approaches. It covers geoinformation themes like capturing, databasing, visualization, interpretation, data quality, and spatial uncertainty.
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