基于马尔科夫分割的单极化SAR数据洪涝水体检测方法

Single-polarization SAR Data Flood Water Detection Method Based on Markov Segmentation

我国是个洪涝灾害多发的国家,每年7月、8月份洪涝灾害时常发生。因此,实现洪涝受灾区域的水体快速检测对灾害救援和评估具有重要的意义。高分3号SAR卫星数据采用主动式对地观测技术,全天时、全天候成像的特点在洪涝减灾应用中具有明显的优势。以湖南省洪涝灾害区域快速检测为目的,该文提出基于高分3号单极化SAR数据的洪涝区域水体快速检测方法,包括SAR预处理,顾及SAR分布特性且保边缘的马尔科夫模型洪涝水体提取,基于SAR几何构象模型的阴影虚警干扰去除等步骤,并利用人工检测结果进行相对精度评价。测试结果表明,所提方法可以实现洪涝受灾区域的快速、精确提取。

China is a flood disaster-prone country, where floods occur frequently every year, from July to August. Therefore, rapid disaster detection and assessment of floods affected areas is of great significance. GF-3 SAR satellite data has obvious advantages of all-day, all-weather imaging characteristics in flood disaster reduction applications because of its active observation technology. For the purpose of rapid water detection in flooding area, a rapid detection method of flood area based on GF-3 single-polarized SAR data is proposed, including SAR preprocessing, flood extraction based on Markov random fields, shadow false alarm removal. Its detecting accuracy is evaluated with manual detection result. The test results show that this method can realize the rapid and accurate extraction of waters in flood disaster area.