Single-polarization SAR Data Flood Water Detection Method Based on Markov Segmentation
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摘要:
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。
Abstract: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.
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Key words:
- SAR /
- GF-3 /
- Markov Random Field (MRF) /
- Flood disaster /
- Disaster reduction
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表 2 灾区水体自动提取效率分析(s)
计算
硬件生成
1B转换
8位一致性
滤波受灾区域
提取去除
阴影地理
编码总时间 4核CPU 1 1 713 2 43 2 762 8核CPU 1 1 218 1 15 1 237 36核CPU 1 1 55 1 8 1 67 64核CPU 1 1 27 1 5 1 36 
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张庆君. 高分3号卫星总体设计与关键技术[J]. 测绘学报, 2017, 46(3): 269–277. doi: 10.11947/j.AGCS.2017.20170049ZHANG Qingjun. System design and key technologies of the GF-3 satellite[J]. Acta Geodaetica et Cartographica Sinica, 2017, 46(3): 269–277. doi: 10.11947/j.AGCS.2017.20170049 张薇, 杨思全, 王磊, 等. 合成孔径雷达数据减灾应用潜力研究综述[J]. 遥感技术与应用, 2012, 27(6): 904–911.ZHANG Wei, YANG Siquan, WANG Lei, et al. Review on disaster reduction application potentiality of synthetic aperture radar[J]. Remote Sensing Technology and Application, 2012, 27(6): 904–911. 胡德勇. 遥感技术在防灾减灾中的应用[J]. 高科技与产业化, 2013, 3(11): 44–47.HU Deyong. Application of remote sensing technology in disaster prevention and mitigation[J]. High-Technology and Industrialization, 2013, 3(11): 44–47. 邓滢, 张红, 王超, 等. 结合纹理与极化分解的面向对象极化SAR水体提取方法[J]. 遥感技术与应用, 2016, 31(4): 714–723.DENG Ying, ZHANG Hong, WANG Chao, et al. An Object-oriented water extraction method based on texture and polarimetric decomposition feature[J]. Remote Sensing Technology and Application, 2016, 31(4): 714–723. 周广益, 钟华, 杨健. 基于负指数变换和 Mean-shift 算法的 SAR 图像可视化方法[J]. 清华大学学报: 自然科学版, 2011, 51(7): 983–987. doi: 10.12000/JR17024ZUOU Guangyi, ZHONG Hua, and YANG Jian. Visualization method for SAR images based on a negative exponential transformation and mean-shift algorithm[J]. Journal of Tsinghua University(Science and Technology) , 2011, 51(7): 983–987. doi: 10.12000/JR17024 YU Y and ACTION S T. Spcckle reducing anisotropic diffusion[J]. IEEE Transactions on image processing, 2002, 11(11): 1260–1270. doi: 10.1109/TIP.2002.804276 王峰, 尤红建. 基于级联变换的光学和SAR图像配准算法[J]. 红外与毫米波学报, 2015, 34(4): 486–492. doi: 10.11972/j.issn.1001-9014.2015.04.18WANG Feng and YOU Hongjian. Robust registration method of SAR and optical remote sensing Images based on cascade transforms[J]. Journal of Infrared and Millimeter Waves, 2015, 34(4): 486–492. doi: 10.11972/j.issn.1001-9014.2015.04.18 BLASCHKE T, HAY G J, KELLY M, et al. Geographic object-based image analysis-towards a new paradigm[J]. ISPRS Journal of Photogrammetry & Remote Sensing, 2014, 87(1): 180–191. doi: 10.11972/j.issn.1001-9014.2015.04.18 BENZ U C, HOFMANN P, WILLHAUCK G, et al. Multi-resolution, object-oriented fuzzy analysis of remote sensing data for GIS-ready information[J]. ISPRS Journal of Photogrammetry & Remote Sensing, 2011, 58(3): 239–258. YU Q and CLAUSI D A. IRGS: Image segmentation using edge penalties and region growing[J]. IEEE Transactions on Pattern Analysis & Machine Intelligence, 2008, 30(12): 2126–2139. 丁赤飚, 刘佳音, 雷斌, 等. 高分3号SAR卫星系统级几何定位精度初探[J]. 雷达学报, 2017, 6(1): 11–16. doi: 10.12000/JR17024DING Chibiao, LIU Jiayin, LEI Bin, et al. Preliminary exploration of systematic geolocation accuracy of GF-3 SAR satellite system[J]. Journal of Radars, 2017, 6(1): 11–16. doi: 10.12000/JR17024 -
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