摘要
介绍了一种基于序列差分干涉纹图的地表形变速率提取算法。该算法根据空间离散分布的相干目标,利用Delaunay三角网构成相位解缠网络,应用最小费用流算法完成相位解缠;根据序列差分干涉相位,利用线性模型解算相干目标形变速率,进而抑制大气波动对形变信号的影响。以廊坊地区2004～2005年ASAR数据为例,获取了该地区地表沉降线性速率及其演变状况。
The conventional repeat -pass differential SAR Interferometry （D -InSAR） was proved to be a remarkable potential technology for mapping surface deformation. However, a full operational capability has not yet been achieved due to phase decorrelation and atmospheric disturbances. A stacking differential interferograms strategy is presented for surface deformation rate derivation in this paper. In this algorithm, the pixels that preserve a good coherence level in the whole interferograms stack are identified to generate the triangulation network with Delaunay criteria. The Minimum Cost Flow （MCF） algorithm is used for phase unwrapping of individual interferogram. The unwrapped phase series of each point is used to estimate the linear deformation rate, and the standard deviation of the estimates of the linear subsidence rate is calculated to indicate the nonlinear subsidence of the pixel. The algorithm was tested with 9 scenes ASAR data acquired from 2004 to 2005 to derive the linear subsidence rate of Langfang City.
出处
《国土资源遥感》
CSCD
2007年第1期24-26,31,I0002-I0004,共7页
Remote Sensing for Land & Resources
基金
中国地质调查局计划项目"干涉雷达在地表形变监测中的应用研究"(项目编号:1212010560705)
关键词
D—InSAR
失相干
大气波动
干涉纹图集
线性形变速率
D - InSAR
Decorrelation
Atmosphere disturbance
Interferograms stack
Linear deformation rate
