Near-real-time non-obstructed flood inundation mapping using synthetic aperture radar
Near-real-time non-obstructed flood inundation mapping using synthetic aperture radar
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DOI：
10.1016/j.rse.2018.11.008
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发表时间：
2019-02-01
影响因子：
13.5
通讯作者：
Kettner, Albert J.
中科院分区：
文献类型：
--
作者：
Shen, Xinyi;Anagnostou, Emmanouil N.;Kettner, Albert J.
在发生洪水灾害时，第一反应机构需要以接近真实的时间（NRT）制作的洪水地图。这种地图可以利用卫星信息生成。在这项研究中，我们开发的测绘技术，依赖于合成孔径雷达（SAR）上的地球轨道平台。合成孔径雷达通过云层覆盖提供有效的地面测量，分辨率高，采样频率最近通过多次飞行任务得到提高。尽管作出了许多努力，但自动处理合成孔径雷达数据以得出准确的淹没图仍然是一个挑战。为了解决这些问题，我们开发了一个名为RAdarProduced Inundation Diary（RAPID）的NRT系统。RAPID集成了四个处理步骤：基于统计的分类，形态学处理，基于多阈值的补偿和机器学习校正。除合成孔径雷达数据外，该系统还集成了多波段遥感数据产品，包括土地覆盖分类、水体分布、水文、水类型和河流宽度产品。与专家手工制作的洪水图相比，全自动RAPID系统的“总体”、“生产者”和“用户”准确率分别为93%、77%和75%。RAPID适应常见的过度检测和欠检测，这些错误由噪声样斑点、水样雷达响应区域、强散射体和孤立的淹没区域引起，在通常的实践中，这些错误被忽略、屏蔽或通过粗化有效分辨率而被过滤掉。RAPID可以作为核心算法，从现有的和将要发射的配备高分辨率合成孔径雷达传感器的卫星，包括环境卫星、雷达卫星、NISAR、高级陆地观测卫星（ALOS）-1/2、哨兵-1和TerraSAR-X中获得洪水淹没产品。
In the event of a flood disaster, first response agencies need inundation maps produced in near real time (NRT). Such maps can be generated using satellite-based information. In this study, we developed mapping techniques that rely on synthetic aperture radar (SAR) on-board earth-orbiting platforms. SAR provides valid ground surface measurements through cloud cover with high resolution and sampling frequency that has recently increased through multiple missions. Despite numerous efforts, automatic processing of SAR data to derive accurate inundation maps still poses challenges. To address them, we have developed an NRT system named RAdarProduced Inundation Diary (RAPID). RAPID integrates four processing steps: classification based on statistics, morphological processing, multi-threshold-based compensation, and machine-leaming correction. Besides SAR data, the system integrates multisource remote-sensing data products, including land cover classification, water occurrence, hydrographical, water type, and river width products. In comparison to expert handmade flood maps, the fully-automated RAPID system exhibited "overall," "producer," and "user" accuracies of 93%, 77%, and 75%, respectively. RAPID accommodates commonly encountered over- and under-detections caused by noise-like speckle, water-like radar response areas, strong scatterers, and isolated inundation areas errors that are in common practice to ignore, mask out, or be filtered out by coarsening the effective resolution. RAPID can serve as the kernel algorithm to derive flood inundation products from satellites both existing and to be launched equipped with high-resolution SAR sensors, including Envisat, Radarsat, NISAR, Advanced Land Observation Satellite (ALOS)-1/2, Sentinel-1, and TerraSAR-X.