Floodwater detection in urban areas using Sentinel-1 and WorldDEM data
Floodwater detection in urban areas using Sentinel-1 and WorldDEM data
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DOI：
10.1117/1.jrs.15.032003
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发表时间：
2021-02
影响因子：
1.7
通讯作者：
D. Mason;S. Dance;H. Cloke
中科院分区：
文献类型：
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作者：
D. Mason;S. Dance;H. Cloke
抽象的。利用合成孔径雷达(SAR)进行遥感是应急洪涝事件管理的重要工具。目前，业务服务主要针对农村地区的洪水测绘，因为城市地区的测绘受到那里复杂的后向散射机制的阻碍。提出了一种在可能包含密集住房的城市地区进行高分辨率洪水检测的方法。这在很大程度上使用了在全球范围内容易获得的遥感数据集，包括开放获取的Sentinel-1合成孔径雷达数据、WorldDEM数字地面模型(DSM)和开放获取的世界住区足迹数据，以确定城市地区。这种方法是一种变化检测技术，可以在当地估计城市地区的洪水水位。它在洪水后的图像中搜索由于水(而不是未被洪水淹没的地面)与邻近建筑物之间的二次散射而增加的SAR后向散射，以及在远离高斜坡的区域减少的SAR后向散射。通过将内插的洪水水位面与DSM进行比较来检测城市洪水区域。该方法在2019-2020年冬季英国发生的两次洪水事件上进行了测试。在中等密度的房屋中，城市洪水检测的准确率很高。当街道宽度变得与DSM分辨率相当时，在密集住房中发生的事件的准确性会降低，尽管它仍然对事件管理有用。该方法有可能在全球范围内近乎实时地检测城市洪水。
Abstract. Remote sensing using synthetic aperture radar (SAR) is an important tool for emergency flood incident management. At present, operational services are mainly aimed at flood mapping in rural areas, as mapping in urban areas is hampered by the complicated backscattering mechanisms occurring there. A method for detecting flooding at high resolution in urban areas that may contain dense housing is presented. This largely uses remotely sensed data sets that are readily available on a global basis, including open-access Sentinel-1 SAR data, the WorldDEM digital surface model (DSM), and open-access World Settlement Footprint data to identify urban areas. The method is a change detection technique that locally estimates flood levels in urban areas. It searches for increased SAR backscatter in the post-flood image due to double scattering between water (rather than unflooded ground) and adjacent buildings, and reduced SAR backscatter in areas away from high slopes. Areas of urban flooding are detected by comparing an interpolated flood level surface to the DSM. The method was tested on two flood events that occurred in the UK during the storms of Winter 2019–2020. High urban flood detection accuracies were achieved for the event in moderate density housing. The accuracy was reduced for the event in dense housing, when street widths became comparable to the DSM resolution, though it would still be useful for incident management. The method has potential for operational use for detecting urban flooding in near real-time on a global basis.