基于形态学的多时相SAR洪水监测方法研究

洪涝灾害严重危害人类的生命和财产安全,且发生频繁,危害范围大,因此洪涝灾害的监测至关重要。文章基于灾前/中Sentinel-1A双极化SAR数据,首先分别利用VV和VH极化强度信息构造峡山水库洪涝灾害发生前后差异图,并采用Otsu法初步提取洪水范围,然后,为进一步减弱斑噪影响,引入形态学算法以获得更准确的洪水分布图,最后,将精确提取的VV和VH洪水受灾区域进行叠加整合,得到最终洪灾面积为28.82km2。与光学影像对比分析后得到检测精度为80.260%,高于不加入形态学算法和传统Otsu法的检测精度(77.125%和74.830%),因此本文方法精度更高,准确性更好。

Research on flood monitoring method of multi-temporal sentinel-1A SAR based on morphology

Flood disaster seriously endangers the safety of human life and property, and occurs frequently and damages a large range, so the monitoring of flood disaster is very important. This paper is based on dual-polarization Sentinel-1 A SAR data before and during disasters.First using the polarization intensity information of VV and VH structures difference map before and after the Xiashan reservoir flood disaster respectively, and using Otsu method to extract the flood scope.Then, to further weaken the impact of speckle noise, morphological algorithm is introduced to obtain more accurate flood distribution map.Finally, precisely extracted VV and VH flood affected areas are overlayed and integrated, and get the final flooding area of 28.82 km2. Compared with optical images, the detection accuracy is 80.260%, which is higher than the detection accuracy without morphological algorithm and traditional OTSU method(77.125% and 74.830%). Therefore, the method in this paper has higher precision and better accuracy.