整合光学和雷达卫星数据,用于乌克兰与冲突有关的变化检测
Kinga Karwowska1, Jakub Slesinski1, Aleksandra Sekrecka2
1Department of Imagery Intelligence, Faculty of Civil Engineering and Geodesy, Military University of Technology, 00-908, Warsaw, Poland.
Scientific reports
|March 9, 2026
概括
这项研究引入了一种使用Sentinel卫星数据的自动化方法,用于在冲突地区快速地表变化和损害检测. 该方法可以准确地识别受损的建筑物和建筑区,克服地面评估的安全限制.
科学领域:
- 遥感 遥感 遥感 遥感
- 地理空间分析的研究.
- 环境监测 环境监测
背景情况:
- 乌克兰战争造成了重大破坏,但地面评估受到安全考虑的限制.
- 开放的卫星数据为监测环境和基础设施变化提供了可行的替代方案.
研究的目的:
- 开发一种使用Sentinel-1和Sentinel-2数据进行冲突后分析的自动化变化检测方法.
- 根据土地覆盖类型 (城市与非城市) 量身定制变化分析,减少分类文物.
主要方法:
- 集成的基于合成孔径雷达 (SAR) 的变化检测与光学图像分类.
- 采用上下文意识的平滑来减少本地分类文物.
- 自动化土地覆盖类型分类和适应性分析策略选择.
主要成果:
- 实现了超过80%的损坏建筑物的检测,回忆率为78.8%,精度为87.5%.
- 情境感知光滑方法提高了建筑区检测准确度至0.98,超过了AlphaEarth (0.87).
- 在受冲突影响的地区展示了有效的快速土地覆盖变化分析和损害检测.
结论:
- 拟议的方法允许使用自由可用的卫星数据进行有效和准确的冲突后损害评估.
- 这种方法对于安全问题限制了现场损害评估的地区至关重要.
- 自动化系统为人道主义援助和重建规划提供可靠的数据.
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