Spatial analysis of surface deformation distribution detected by persistent scatterer interferometry in Lanzhou Region, China

Abstract Persistent scatterer synthetic aperture radar interferometry (PS-InSAR) is a remote sensing method that can be used to detect surface deformation, which is an indicator of potential geohazards. By capturing such deformations over time, it is possible to obtain valuable information regarding geohazards such as landslides. This study focused on the use of PS-InSAR to investigate the distribution and causes of surface deformation in the Lanzhou region of Gansu Province in China. Between 2003 and 2010, 41 advanced synthetic aperture radar images were captured by the Envisat satellite and analyzed using PS-InSAR, and the correlation between the observed surface deformation and topographic, geologic, and anthropogenic factors was derived based on a geographic information system platform. It was found that the largest number and highest density of surface deformations occurred at elevations of 1486–1686 m. It was also established that slope ranges of 25°–30° and 35°–40° are threshold values at which surface deformation changes abruptly, and that slopes with north and northwest aspects are most prone to surface deformation. The lithologies most susceptible to surface deformation are clay, sandy soil, and loess. The normalized difference vegetation index indicated that surface deformation occurred most often in areas with sparse vegetation. Anthropogenic activities, e.g., construction and wastewater discharge, could be inferred as causal mechanisms of surface deformation. Comparison of the distributions of geohazards and surface deformation showed considerable consistency, which proves surface deformation can induce geohazards. These results could help governments improve urban planning and geohazard mitigation.

[1]  Fabio Rocca,et al.  Monitoring landslides and tectonic motions with the Permanent Scatterers Technique , 2003 .

[2]  A. Clerici,et al.  A procedure for landslide susceptibility zonation by the conditional analysis method , 2002 .

[3]  L. Mallen,et al.  Iso-Kinematic Maps from statistical analysis of PS-InSAR data of Piemonte, NW Italy: Comparison with geological kinematic trends , 2011 .

[4]  Howard A. Zebker,et al.  Decorrelation in interferometric radar echoes , 1992, IEEE Trans. Geosci. Remote. Sens..

[5]  Charles Werner,et al.  Accuracy of topographic maps derived from ERS-1 interferometric radar , 1994, IEEE Trans. Geosci. Remote. Sens..

[6]  Janusz Wasowski,et al.  Investigating landslides with space-borne Synthetic Aperture Radar (SAR) interferometry , 2006 .

[7]  K. Feigl,et al.  Radar interferometry and its application to changes in the Earth's surface , 1998 .

[8]  R. Hanssen Radar Interferometry: Data Interpretation and Error Analysis , 2001 .

[9]  C. Rogers,et al.  Hydroconsolidation and subsidence of loess: studies from China, Russia, North America and Europe , 1994 .

[10]  Ramon F. Hanssen,et al.  PS-InSAR processing methodologies in the detection of field surface deformation—Study of the Granada basin (Central Betic Cordilleras, southern Spain) , 2010 .

[11]  Andrew Hooper,et al.  Phase unwrapping in three dimensions with application to InSAR time series. , 2007, Journal of the Optical Society of America. A, Optics, image science, and vision.

[12]  Helmut Rott,et al.  The contribution of radar interferometry to the assessment of landslide hazards , 2006 .

[13]  Zhang Ji-xun Types and Distribution of Geological Hazards in Lanzhou City , 2010 .

[14]  H. Zebker,et al.  Persistent scatterer interferometric synthetic aperture radar for crustal deformation analysis, with application to Volcán Alcedo, Galápagos , 2007 .

[15]  Wenjun Zheng,et al.  Landslides triggered by the 22 July 2013 Minxian–Zhangxian, China, Mw 5.9 earthquake: Inventory compiling and spatial distribution analysis , 2014 .

[16]  Zhong Lu,et al.  Monitoring of urban subsidence with SAR interferometric point target analysis: A case study in Suzhou, China , 2011, Int. J. Appl. Earth Obs. Geoinformation.

[17]  R. Goldstein,et al.  Mapping small elevation changes over large areas: Differential radar interferometry , 1989 .

[18]  Measuring land subsidence from space , 2000 .

[19]  H. Zebker,et al.  A new method for measuring deformation on volcanoes and other natural terrains using InSAR persistent scatterers , 2004 .

[20]  Xing-min Meng,et al.  Landslides in the thick loess terrain of Northwest China , 2000 .

[21]  A. Hooper,et al.  Recent advances in SAR interferometry time series analysis for measuring crustal deformation , 2012 .

[22]  J. Wasowski,et al.  Using COSMO/SkyMed X-band and ENVISAT C-band SAR interferometry for landslides analysis , 2012 .

[23]  Michele Crosetto,et al.  Spaceborne Differential SAR Interferometry: Data Analysis Tools for Deformation Measurement , 2011, Remote. Sens..

[24]  Chung-Pai Chang,et al.  Surface deformation from persistent scatterers SAR interferometry and fusion with leveling data: A case study over the Choushui River Alluvial Fan, Taiwan , 2011 .

[25]  J. N. Lima,et al.  Persistent Scatterers Interferometry detects and measures ground subsidence in Lisbon , 2011 .

[26]  David T. Sandwell,et al.  Fault creep along the southern San Andreas from interferometric synthetic aperture radar, permanent scatterers, and stacking , 2003 .

[27]  Yngvar Larsen,et al.  Detailed rockslide mapping in northern Norway with small baseline and persistent scatterer interferometric SAR time series methods. , 2010 .

[28]  T. Wright,et al.  Measurement of interseismic strain accumulation across the North Anatolian Fault by satellite radar interferometry , 2001 .

[29]  Fabio Rocca,et al.  Permanent scatterers in SAR interferometry , 2001, IEEE Trans. Geosci. Remote. Sens..

[30]  David T. Sandwell,et al.  Small‐scale deformations associated with the 1992 Landers, California, earthquake mapped by synthetic aperture radar interferometry phase gradients , 1998 .

[31]  E. J. Price,et al.  Coseismic and postseismic deformations associated with the 1992 Landers, California, earthquake measured by synthetic aperture radar interferometry , 1999 .

[32]  Ramon F. Hanssen,et al.  Persistent Scatterer InSAR: A comparison of methodologies based on a model of temporal deformation vs. spatial correlation selection criteria , 2011 .

[33]  Fabio Rocca,et al.  Nonlinear subsidence rate estimation using permanent scatterers in differential SAR interferometry , 2000, IEEE Trans. Geosci. Remote. Sens..

[34]  K. Feigl,et al.  The displacement field of the Landers earthquake mapped by radar interferometry , 1993, Nature.

[35]  Christopher D. F. Rogers,et al.  Particle packing in loess deposits and the problem of structure collapse and hydroconsolidation , 1995 .