Abstract This paper proposes a simple and fast method for the identification of structural changes affecting buildings in urban environments by using a combination of Synthetic Aperture Radar (SAR) imagery and Geospatial Information System (GIS) processing. The identification of changes in urban settlements is of great interest for damage assessment after natural disasters, cadastral mapping and monitoring urban development or illegal activities, such as the construction of unauthorized buildings. Satellite remote sensing is useful in this scenario and SAR data is attractive due to its wide and ubiquitous coverage, the day and night all-weather availability, the exact repetition of the acquisition geometry, the repeated illumination and the sensitivity to slight changes in the geometrical structure of the targets in the scene. This sensibility is an advantage, but turns into a drawback especially in an urban environment where every subtle change may cause an unwanted detection. This environment is indeed one of the most challenging for the detection of those changes that are of any real interest since these events are masked by thousands of irrelevant detections. This paper tackle this problem with a combination of an improved, high-resolution coherent change detection technique called M-CCD and with a GIS post-processing. The result is a map of changes affecting buildings that are of a significant scale and consequently of a certain interest in an urban environment. In this contribution, the complete workflow is detailed and an assessment of the detected changes is done with high resolution optical images through visual photo-interpretation. A comparison with other SAR and optical change detection methods is also carried out.

中文翻译：

---

星载SAR图像与GIS技术在城市相干变化检测中的联合开发

摘要 本文提出了一种简单快速的方法，通过结合使用合成孔径雷达 (SAR) 图像和地理空间信息系统 (GIS) 处理来识别影响城市环境中建筑物的结构变化。城市住区变化的识别对于自然灾害后的损害评估、地籍测绘和监测城市发展或非法活动（如建造违章建筑）具有重要意义。卫星遥感在这种情况下很有用，并且 SAR 数据因其广泛而无处不在的覆盖范围、昼夜全天候可用性、采集几何的精确重复、重复照明以及对几何微小变化的敏感性而具有吸引力。场景中目标的结构。这种敏感性是一个优势，但会变成一个缺点，尤其是在城市环境中，每一个细微的变化都可能导致不必要的检测。这种环境对于检测那些真正感兴趣的变化来说确实是最具挑战性的环境之一，因为这些事件被数千个不相关的检测所掩盖。本文通过将改进的高分辨率相干变化检测技术称为 M-CCD 和 GIS 后处理相结合来解决这个问题。结果是一张影响建筑物的变化地图，这些建筑物的规模很大，因此对城市环境有一定的兴趣。在这篇文章中，详细介绍了完整的工作流程，并通过视觉照片解释使用高分辨率光学图像对检测到的变化进行了评估。