结合先验概率估计的GF-3影像水体概率估计方法

doi:10.11947/j.AGCS.2019.20170732

测绘学报 ›› 2019, Vol. 48 ›› Issue (4): 439-447.doi: 10.11947/j.AGCS.2019.20170732

结合先验概率估计的GF-3影像水体概率估计方法

孟令奎^1,2, 毛旭东¹, 魏祖帅¹, 张文¹

1. 武汉大学遥感信息工程学院, 湖北武汉 430079;
2. 地球空间信息技术协同创新中心, 湖北武汉 430079

收稿日期:2017-12-20 修回日期:2018-08-24 出版日期:2019-04-20 发布日期:2019-05-15
通讯作者: 张文 E-mail:wen_zhang@whu.edu.cn
作者简介:孟令奎(1967-),男,教授,研究方向为网络GIS、水利遥感技术及应用。E-mail:lkmeng@whu.edu.cn
基金资助:
国家重点研发计划（2017YFC0405806）

Probabilistic water body mapping of GF-3 images based on prior probability estimation

MENG Lingkui^1,2, MAO Xudong¹, WEI Zushuai¹, ZHANG Wen¹

1. School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China;
2. Collaborative Innovation Center of Geospatial Technology, Wuhan 430079, China

Received:2017-12-20 Revised:2018-08-24 Online:2019-04-20 Published:2019-05-15
Supported by:
The National Key Research and Development Program of China (No. 2017YFC0405806)

摘要/Abstract

摘要： 综合SAR（synthetic aperture radar）影像的统计模型假设与k-means聚类算法，提出了一种结合水体分布先验概率估计的水体概率估计方法。首先，用贝叶斯推断对研究区域后向散射系数做统计模型假设。随后，结合聚类算法对像元作分类，估计水体分布先验概率，结合统计分布直方图使用非线性最小二乘拟合完成模型参数估计。试验选取了高分三号（GF-3）多种工作模式数据，并用高分一号（GF-1）影像进行验证。结果表明，该方法可有效实现SAR影像的高精度水体概率估计。

关键词: 水体概率估计, 参数估计, 合成孔径雷达(SAR), 高分三号

Abstract: We combine k-means cluster algorithm with the statistical model of SAR(synthetic aperture radar) images and develop the probabilistic water body mapping algorithm based on the priori probability estimation. Firstly, we make the statistical model assumption about backscatter values based on Bayesian theory. Then, we classify the images based on cluster algorithm, calculate the prior probability of the water body mapping and estimate the parameters of the statistical model of water distribution.Thewater body probabilistic maps based on GF-3 images in Luquan and Xianning are calculated and then validated with GF-1 images. The algorithm is effective on high-precision probabilistic water body mapping of SAR images.

Key words: probabilistic water body mapping, parameter estimation, synthetic aperture radar (SAR), GF-3

中图分类号:

P237

孟令奎, 毛旭东, 魏祖帅, 张文. 结合先验概率估计的GF-3影像水体概率估计方法[J]. 测绘学报, 2019, 48(4): 439-447.

MENG Lingkui, MAO Xudong, WEI Zushuai, ZHANG Wen. Probabilistic water body mapping of GF-3 images based on prior probability estimation[J]. Acta Geodaetica et Cartographica Sinica, 2019, 48(4): 439-447.

参考文献

[1] 徐川, 华凤, 眭海刚, 等. 多尺度水平集SAR影像水体自动分割方法[J]. 武汉大学学报(信息科学版), 2014, 39(1):27-31. XU Chuan, HUA Feng, SUI Haigang, et al. Automatic water segmentation method in SAR images using multi-scale level Set[J]. Geomatics and Information Science of Wuhan University, 2014, 39(1):27-31.
[2] 张庆君. 高分三号卫星总体设计与关键技术[J]. 测绘学报, 2017, 46(3):269-277. ZHANG Qingjun. System design and key technologies of the GF-3 satellite[J]. Acta Geodaetica et Cartographica Sinica, 2017, 46(3):269-277.
[3] 李景刚, 黄诗峰, 李纪人. ENVISAT卫星先进合成孔径雷达数据水体提取研究——改进的最大类间方差阈值法[J]. 自然灾害学报, 2010, 19(3):139-145. LI Jinggang, HUANG Shifeng, LI Jiren. Research on extrac-tion of water body from envisat ASAR images:a modified otsu threshold method[J]. Journal of Natural Disasters, 2010, 19(3):139-145.
[4] OTSU N. A threshold selection method from gray-level histograms[J]. IEEE Transactions on Systems, Man, and Cybernetics, 1979, 9(1):62-66.
[5] LÜ Wentao, YU Qiuze, YU Wenxian. Water extraction in SAR images using GLCM and support vector machine[C]//IEEE 10th International Conference on Signal Processing Proceedings. Beijing, China:IEEE, 2010.
[6] SILVEIRA M, HELENO S. Separation between water and land in SAR images using region-based level sets[J]. IEEE Geoscience and Remote Sensing Letters, 2009, 6(3):471-475.
[7] KASS M, WITKIN A, TERZOPOULOS D. Snakes:active contour models[J]. International Journal of Computer Vision, 1988, 1(4):321-331.
[8] 孟令奎, 吕琪菲. 复杂水体边界提取的改进正交T-Snake模型[J]. 测绘学报, 2015, 44(6):670-677. DOI:10.11947/j.AGCS.2015.20140404. MENG Lingkui, LÜ Qifei. Improved orthogonal T-snake model for complex water boundary extraction[J]. Acta Geodaetica et Cartographica Sinica, 2015, 44(6):670-677. DOI:10.11947/j.AGCS.2015.20140404.
[9] 韩斌, 吴一全. SAR图像河流分割的加权指数区域能量模型[J]. 测绘学报, 2017, 46(9):1174-1181. DOI:10.11947/j.AGCS.2017.20170134. HAN Bin, WU Yiquan. Weighted exponential region energy model for river segmentation of SAR images[J]. Acta Geodaetica et Cartographica Sinica, 2017, 46(9):1174-1181. DOI:10.11947/j.AGCS.2017.20170134.
[10] GIUSTARINI L, VERNIEUWE H, VERWAEREN J, et al. Accounting for image uncertainty in SAR-based flood mapping[J]. International Journal of Applied Earth Observation and Geoinformation, 2015(34):70-77.
[11] GIUSTARINI L, HOSTACHE R, KAVETSKI D, et al. Probabilistic flood mapping using synthetic aperture radar data[J]. IEEE Transactions on Geoscience and Remote Sensing, 2016, 54(12):6958-6969.
[12] HOSTACHE R, MATGEN P, SCHUMANN G, et al. Water level estimation and reduction of hydraulic model calibration uncertainties using satellite SAR images of floods[J]. IEEE Transactions on Geoscience and Remote Sensing, 2009, 47(2):431-441.
[13] SCHUMANN G, MATGEN P, PAPPENBERGER F. Conditioning water stages from satellite imagery on uncertain data points[J]. IEEE Geoscience and Remote Sensing Letters, 2008, 5(4):810-813.
[14] DI BALDASSARRE G, SCHUMANN G, BATES P D. A technique for the calibration of hydraulic models using uncertain satellite observations of flood extent[J]. Journal of Hydrology, 2009, 367(3-4):276-282.
[15] MONTANARI M, HOSTACHE R, MATGEN P, et al. Calibration and sequential updating of a coupled hydrologic-hydraulic modelusing remote-sensing derived water stages[J]. Hydrology and Earth System Sciences, 2009, 13(3):367-380.
[16] BEVEN K. A manifesto for the equifinality thesis[J]. Journal of Hydrology, 2006, 320(1-2):18-36.
[17] WESTERHOFF R S, WINSEMIUS H C, HUIZINGA H J, et al. Automated global water mapping based on wide-swath orbital synthetic-aperture radar[J]. Hydrology and Earth System Sciences, 2013, 17(2):651-663.
[18] CHINI M, GIUSTARINI L, HOSTACHE R, et al. An automatic SAR-based flood mapping algorithm combining hierarchical tiling and change detection[C]//ESA Living Planet Symposium. Prague, Czech Republic:ESA, 2016.
[19] ULABY F T, MOORE R K, FUNG A K. Microwave remote sensing, active and passive:Vol Ⅱ:radar remote sensing and surface scattering and emission theory[M].[S.l.]:Artech House, 1982.
[20] XIE Hua, PIERCE L E, ULABY F T. Statistical properties of logarithmically transformed speckle[J]. IEEE Transactions on Geoscience and Remote Sensing, 2002, 40(3):721-727.
[21] WILKS D S. Statistical methods in the atmospheric sciences[M]. Oxford:Academic Press, 2011:34.
[22] MARQUARDT D W. An algorithm for least-squares estimation of nonlinear parameters[J]. Journal of the Society for Industrial and Applied Mathematics, 1963, 11(2):431-441.
[23] CHINI M, HOSTACHE R, GIUSTARINI L, et al. A hierarchical split-based approach for parametric thresholding of SAR images:flood inundation as a test case[J]. IEEE Transactions on Geoscience and Remote Sensing, 2017, 55(12):6975-6988.
[24] SHI Zhenghao, FUNG K B. A comparison of digital speckle filters[C]//1994 IEEE International Geoscience and Remote Sensing Symposium. Pasadena, CA:IEEE.
[25] HOSTACHE R, MATGEN P, MONTANARI A, et al. Propagation of uncertainties in coupled hydro-meteorological forecasting systems:a stochastic approach for the assessment of the total predictive uncertainty[J]. Atmospheric Research, 2011, 100(2-3):263-274.
[26] HORRITT M S. A methodology for the validation of uncertain flood inundation models[J]. Journal of Hydrology, 2006, 326(1-4):153-165.
[27] BRÖCKER J, SMITH L A. Increasing the reliability of reliability diagrams[J]. Weather and Forecasting, 2007, 22(3):651-661.

结合先验概率估计的GF-3影像水体概率估计方法

Probabilistic water body mapping of GF-3 images based on prior probability estimation

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 10

编辑推荐

Metrics

本文评价

[1]	王珂, 刘国林, 付政庆, 王路遥. 基于Moore-Penrose广义逆及立体矩阵的可分离非线性最小二乘解算方法[J]. 测绘学报, 2022, 51(3): 340-350.
[2]	丁刘建, 陶秋香, 李涛, 陈乾福, 陈洋. 高分三号SAR影像广域范围联合几何检校技术[J]. 测绘学报, 2020, 49(5): 598-610.
[3]	邓兴升, 彭思淳, 游扬声. 加权整体最小二乘EIO模型与算法[J]. 测绘学报, 2019, 48(7): 926-930.
[4]	王乐洋, 余航, 邹传义, 鲁铁定. 加权整体最小二乘EIV模型与算法——与“加权整体最小二乘EIO模型与算法”一文的讨论[J]. 测绘学报, 2019, 48(7): 931-937.
[5]	吕冠南, 唐新明, 艾波, 李涛, 陈乾福. 稀少控制的多平台星载SAR联合几何定标方法[J]. 测绘学报, 2018, 47(7): 986-995.
[6]	张庆君. 高分三号卫星总体设计与关键技术[J]. 测绘学报, 2017, 46(3): 269-277.
[7]	潘雄, 罗静, 汪耀. P范分布的实数阶与对数矩估计法[J]. 测绘学报, 2016, 45(3): 302-309.
[8]	程春泉, 黄国满, 杨杰. POS与DEM辅助机载SAR多普勒参数估计[J]. 测绘学报, 2015, 44(5): 510-517.
[9]	杨元喜景一帆曾安敏. 自适应参数估计与内外部精度的关系[J]. 测绘学报, 2014, 43(5): 441-445.
[10]	张平. 合成孔径雷达空间变迹带宽外推超分辨算法[J]. 测绘学报, 2010, 39(1): 0-82.