朱煜峰;王升;

• 1:东华理工大学测绘工程学院

摘要(Abstract)：

针对干涉合成孔径雷达的干涉相位在水体区域几乎完全失真,不能够反映真实的干涉相位,并且会降低水体周围区域反演的DEM的精度的问题,该文提出一种估计水体干涉相位算法,使用该算法处理两幅不同区域的Sentinel-1A卫星影像的C波段SAR干涉相位数据,并使用处理后的相位干涉数据反演成DEM,定量分析两次实验反演的水体周围区域的DEM精度,反映DEM精度的指标都大于0。表明经过该算法处理之后,提高了InSAR反演DEM的精度,从而间接验证了本文提出算法的有效性。

关键词(KeyWords)： 水体;干涉相位;相干性;相位估计算法;DEM精度

Abstract:

Keywords:

基金项目(Foundation): 国家自然科学基金项目(41464001);; 江西省自然科学基金项目(20151BAB203042)

作者(Authors): 朱煜峰;王升;

DOI: 10.16251/j.cnki.1009-2307.2020.09.015

参考文献(References)：

• [1] 朱建军,李志伟,胡俊.InSAR变形监测方法与研究进展[J].测绘学报,2017,46(10):1717-1733.(ZHU Jianjun,LI Zhiwei,HU Jun.Research progress and methods of InSAR for deformation monitoring[J].Acta Geodaetica et Cartographica Sinica,2017,46(10):1717-1733.)
• [2] 赵争.地形复杂区域InSAR高精度DEM提取方法[D].武汉:武汉大学,2014.(ZHAO Zheng.Methods on high-accuracy DEM extraction from interferometric SAR in sophisticated terrain areas[D].Wuhan:Wuhan University,2014.)
• [3] 韩松涛,向茂生.一种干涉雷达阴影区的处理方法[J].电子测量技术,2008,31(3):4-6.(HAN Songtao,XIANG Maosheng.Approach for shadow in interferometric synthetic aperture radar[J].Electronic Measurement Technology,2008,31(3):4-6.)
• [4] 陈春森.机载干涉SAR图像低相干区域提取及相位重构方法研究[D].阜新:辽宁工程技术大学,2011.(CHEN Chunsen.Study on extracting and phase reconstruction of low-coherence region with airborne interferometric SAR images[D].Fuxin:Liaoning Technical University,2011.)
• [5] HONG S H,WDOWINSKI S,KIM S W,et al.Multi-temporal monitoring of wetland water levels in the Florida Evergla using interferometric synthetic aperture radar (InSAR)[J].Remote Sensing of Environment,2010,114:2436-2447.
• [6] KIM J W,LU Z,LEE H,et al.Integrated analysis of PALSAR/Radarsat-1 InSAR and ENVISAT altimeter data for mapping of absolute water level changes in Louisiana wetlands[J].Remote Sensing of Environment,2009,113(11):2356-2365.
• [7] 禹文豪,艾廷华.核密度估计法支持下的网络空间POI点可视化与分析[J].测绘学报,2015,44(1):82-90.(YU Wenhao,AI Tinghua.The visualization and analysis of POI features under network space supported by kernel density estimation[J].Acta Geodaeticaet Cartographica Sinica,2015,44(1):82-90.)
• [8] 熊敏诠.滑动窗口的普通克里格方法在降水量插值中的应用[J].气象,2013,39(4):486-493.(XIONG Minquan.Application of the moving window ordinary Kriging method in precipitation interpolation[J].Meteorological Monthly,2013,39(4):486-493.)
• [9] 武汉大学测绘学院测量平差学科组.误差理论与测量平差基础[M].武汉:武汉大学出版社,2015:43.(Subject Group of Surveying Adjustment,School of Surveying and Mapping,Wuhan University.Error theory and foundation of surveying adjustment[M].Wuhan:Wuhan University Press,2015:43.)
• [10] 周艺,谢光磊,王世新,等.利用伪归一化差异水体指数提取城镇周边细小河流信息[J].地球信息科学学报,2014,16(1):102-107.(ZHOU Yi,XIE Guanglei,WANG Shixin,et al.Information extraction of thin rivers around built-up lands with false NDWI[J].Journal of Geo-Information Science,2014,16(1):102-107.)
• [11] 沈占峰,夏列钢,李均力,等.采用高斯归一化水体指数实现遥感影像河流的精确提取[J].中国图象图形学报,2013,18(4):421-428.(SHEM Zhanfeng,XIA Liegang,LI Junli,et al.Automatic and high-precision extraction of rivers from remotely sensed images with Gaussian normalized water index[J].Journal of Image and Graphics,2013,18(4):421-428.)
• [12] 董志鹏,王密,李德仁,等.利用对象光谱与纹理实现高分辨率遥感影像云检测方法[J].测绘学报,2018,47(7):996-1006.(DONG Zhipeng,WANG Mi,LI Deren,et al.A cloud detection method for high resolution remote sensing imagery based on the spectrum and texture of objects[J].Acta Geodaetica et Cartographica Sinica,2018,47(7):996-1006.)
• [13]郭海涛，徐雷，赵红叶，等．一种抑制声呐图像散斑噪声的形态学滤波器[J]．仪器仪表学报，2015,36(3):654-660.(GUO Haitao,XU Lei,ZHAO Hongye,et al.A morphological filter for despeckling of a sonar image[J].Chinese Journal of Scientific Instrument,2015,36(3):654-660.)
• [14]GONZALEZ R C,WOODS R E.Digital image processing[M].New York:Prentice Hall,2007:650-653.
• [15]李娜．基于数学形态学的藻类图像去噪算法研究[D]．青岛：中国海洋大学，2013.(LI Na.The research of algae image denoising algorithm based on mathematical morphology[D].Qingdao:Ocean University of China,2013.)
• [16]梁瀚月．基于Sentinel-1数据的江西省南昌县早稻信息提取研究[D]．成都：成都理工大学，2017.(LIANG Hanyue.Extraction of early paddy rice information in nanchang county of Jiangxi province based on Sentinel-1data[D].Chengdu:Chengdu University of Technology,2017.)
• [17]KARIM B.Analyzing TOPS coregistration models and their influence on coherence[D].Wuhan:Wuhan University,2017.
• [18]张岩．DEM构建中InSAR技术应用与分析[D]．昆明：昆明理工大学，2017.(ZHANG Yan.Application andaccuracy analysis of InSAR technology in DEM construction[D].Kunming:Kunming University of Science and Technology,2017.)
• [19]杨斌，李丹，王磊，等．基于Sentinel-2A岷江上游地表生物量反演与植被特征分析[J]．科技导报，2017,35(21):74-80.(YANG Bin,LI Dan,WANG Lei,et al.Retrieval of surface vegetation biomass information and analysis of vegetation feature based on Sentinel-2Ain the upper of Minjiang River[J].Science&Technology Review,2017,35(21):74-80.)
• [20]曹霖，彭道黎，王雪军，等．应用Sentinel-2A卫星光谱与纹理信息的森林蓄积量估算[J]．东北林业大学学报，2018,46(9):54-58.(CAO Lin,PENG Daoli,WANG Xuejun,et al.Estimation of forest stock volume with spectral and textural information from the Sentinel-2A[J].Journal of Northeast Forestry University,2018,46(9):54-58.)
• [21]陈树．Sentinel-1数据在同震形变和震后形变研究中的应用[D]．北京：中国地震局地震预测研究所，2018.(CHEN Shu.Application of Sentinel-1 data in coseismic deformation and post-seismic deformation research[D].Beijing:Institute of Earthquake Science,China Earthquake Administration,2018.)