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REMOTE SENSING FOR LAND & RESOURCES    2014, Vol. 26 Issue (4) : 125-130     DOI: 10.6046/gtzyyg.2014.04.20
Technology Application |
Inter-comparison and time series fusion of ascending and descending PSInSAR data for land subsidence monitoring
WANG Yan, GE Daqing, ZHANG Ling, LI Man, GUO Xiaofang, WANG Yi
China Aero Geophysical Surveying and Remote Sensing Center for Land and Resources, Beijing 100083, China
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Abstract  A joint analysis of ascending and descending tracks of PSInSAR provides deformation measurements with average velocity and time series of each coherent target for the same deformation zone, which allows the inter-comparison of the velocity map and the fusion of deformation time series. In this paper, the authors present the method of PSInSAR measurement inter-comparison and time series fusion by using ascending and descending ENVISAT data acquired from 2006 to 2010 for the purpose of subsidence monitoring. The inter-comparison of subsidence velocity in ascending and descending tracks demonstrates that the precision is higher than 2 mm, indicating the accuracy of single track PSInSAR measurement for land subsidence monitoring. The fusion of ascending and descending deformation series of each coherent target enables a detailed analysis of temporal behaviors because it provides dense observations in time.
Keywords shadow detection      HIS color space      geometric details      shadow compensation     
:  TP79  
Issue Date: 17 September 2014
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WANG Bo,ZHANG Yongjun,CHEN Qi. Inter-comparison and time series fusion of ascending and descending PSInSAR data for land subsidence monitoring[J]. REMOTE SENSING FOR LAND & RESOURCES, 2014, 26(4): 125-130.
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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2014.04.20     OR     https://www.gtzyyg.com/EN/Y2014/V26/I4/125
[1] Fialko Y,Sandwell D,Simons M,et al.Three-dimensional deformation caused by the Bam,Iran,earthquake and the origin of shallow slip deficit[J].Nature,2005,435(7040):295-299.
[2] Funning G J,Parson B,Wright T J,et al.Surface displacements and source parameters of the 2003 Bam(Iran)earthquake from Envisat advanced synthetic aperture Radar imagery[J].Journal of Geophysical Research,2005,110(B9):B09406.
[3] Fielding E J,Talebian M,Rosen P A,et al.Surface ruptures and building damage of the 2003 Bam,Iran,earthquake mapped by satellite synthetic aperture Radar interferometric correlation[J].Journal of Geophysical Research,2005,110(B3):B03302.
[4] Mora O,Mallorqui J J,Broquetas A,et al.Linear and nonlinear terrain deformation maps from a reduced set of interferometric SAR images[J].IEEE Trans Geosci Remote Sens,2003,41(10):2243- 2253.
[5] Ketelaar G,Van L F,Marinkovic P,et al.Multi-track PS-InSAR datum connection[C]//Proceeding of IEEE International Geoscience and Remote Sensing Symposium.Barcelona:IEEE,2007:2481-2484.
[6] 葛大庆,王艳,张玲,等.低相干条件下区域性地面沉降InSAR调查与监测技术研究[R].北京:中国国土资源航空物探遥感中心,2009. Ge D Q,Wang Y,Zhang L,et al.Research on key InSAR technology to monitor regional subsidence occurred in low correlated regions[R].Beijing:China Aero Geophysical Surveying and Remote Sensing Center for Land and Resources,2009.
[7] 葛大庆,殷跃平,王艳,等.地面沉降-回弹及地下水位波动的InSAR长时序监测——以德州市为例[J].国土资源遥感,2014,26(1):103-109. Ge D Q,Yin Y P,Wang Y,et al.Seasonal subsidence-rebound and ground water level changes monitoring by using coherent target InSAR technique:A case study in Dezhou[J].Remote Sensing for Land and Resources,2014,26(1):103-109.
[8] 王艳,张玲,葛大庆,等.升降轨PSInSAR观测反演沉降与水平向位移试验[J].国土资源遥感,2014,26(4):97-102. Wang Y,Zhang L,Ge D Q,et al.Experimental study on vertical and horizontal displacement retrieval by jointly analysis of ascending and descending PSInSAR data[J].Remote Sensing for Land and Resources,2014,26(4):97-102.
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