Remote sensing for geotechnical earthquake reconnaissance

Abstract This paper describes recent efforts that incorporate remote sensing techniques and platforms into geotechnical earthquake reconnaissance to document damage patterns, collect three-dimensional geometries of failures, and measure ground movements. The most-commonly used remote sensing techniques in geotechnical engineering (satellite imagery and LIDAR), as well as unmanned aerial vehicles (UAV), are introduced and recent case histories of the use of these techniques in reconnaissance efforts are provided. These examples demonstrate the potential for remote sensing to improve our understanding of geotechnical effects both at a regional scale and at a local level. The use of remote sensing to measure ground movements is particularly noteworthy and has the potential to provide data sets that will improve our ability to quantitatively predict the consequences of liquefaction and landslides. However, to realize this potential, investments must be made in collecting appropriate pre-earthquake data.

[1]  Paolo Pasquali,et al.  The 2010-2011 Canterbury, New Zealand, seismic sequence: Multiple source analysis from InSAR data and modeling , 2012 .

[2]  Sébastien Leprince,et al.  Automatic and Precise Orthorectification, Coregistration, and Subpixel Correlation of Satellite Images, Application to Ground Deformation Measurements , 2007, IEEE Transactions on Geoscience and Remote Sensing.

[3]  Xiao Zhang,et al.  Change Detection From Differential Airborne LiDAR Using a Weighted Anisotropic Iterative Closest Point Algorithm , 2015, IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens..

[4]  D. Marr,et al.  Representation and recognition of the spatial organization of three-dimensional shapes , 1978, Proceedings of the Royal Society of London. Series B. Biological Sciences.

[5]  Ryoji Isoyama,et al.  Study on permanent ground displacement induced by seismic liquefaction , 1987 .

[6]  Thomas Oommen,et al.  Documenting Earthquake-Induced Liquefaction Using Satellite Remote Sensing Image TransformationsDocumenting Liquefaction , 2013 .

[7]  M. Crawford,et al.  Spaceborne and Airborne Remote Sensing for Geotechnical Applications , 2006 .

[8]  J. Gong,et al.  Earthquake-induced geological hazards detection under hierarchical stripping classification framework in the Beichuan area , 2010 .

[9]  Paul J. Besl,et al.  A Method for Registration of 3-D Shapes , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[10]  Robert E. Kayen,et al.  Terrestrial-LIDAR Visualization of Surface and Structural Deformations of the 2004 Niigata Ken Chuetsu, Japan, Earthquake , 2006 .

[11]  Reginald DesRoches,et al.  Crowdsourcing for Rapid Damage Assessment: The Global Earth Observation Catastrophe Assessment Network (GEO-CAN) , 2011 .

[12]  R. Crippen Measurement of subresolution terrain displacements using SPOT panchromatic imagery , 1992 .

[13]  Yuri Fialko,et al.  Slip model of the 2015 Mw 7.8 Gorkha (Nepal) earthquake from inversions of ALOS‐2 and GPS data , 2015 .

[14]  Richard Szeliski,et al.  Modeling the World from Internet Photo Collections , 2008, International Journal of Computer Vision.

[15]  J. Malet,et al.  Detection of landslides from aerial and satellite images with a semi-automatic method. Application to the Barcelonnette basin (Alpes-de-Hautes-Provence, France) , 2009 .

[16]  Chong Xu,et al.  Preparation of earthquake-triggered landslide inventory maps using remote sensing and GIS technologies: Principles and case studies , 2015 .

[17]  J. Travelletti,et al.  UAV-based remote sensing of the Super-Sauze landslide : evaluation and results. , 2012 .

[18]  Robert E. Kayen,et al.  REMOTE SENSING OBSERVATIONS OF LANDSLIDES AND GROUND DEFORMATION FROM THE 2004 NIIGATA KEN CHUETSU EARTHQUAKE , 2006 .

[19]  S. M. Jong,et al.  Mapping landslide displacements using Structure from Motion (SfM) and image correlation of multi-temporal UAV photography , 2014 .

[20]  Tingwei Cui,et al.  Remote Sensing of Spatiotemporal Variation of Apparent Optical Properties in Bohai Sea , 2015, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[21]  Shailesh Nayak,et al.  Mapping the liquefaction induced soil moisture changes using remote sensing technique: an attempt to map the earthquake induced liquefaction around Bhuj, Gujarat, India , 2006 .

[22]  Ellen M. Rathje,et al.  Liquefaction-Induced Horizontal Displacements from the Canterbury Earthquake Sequence in New Zealand Measured from Remote Sensing Techniques , 2017 .

[23]  Hiroshi P. Sato,et al.  Landslide inventories: The essential part of seismic landslide hazard analyses , 2011 .

[24]  J. Avouac,et al.  Measuring earthquakes from optical satellite images. , 2000, Applied optics.

[25]  Salman Ashraf,et al.  Using different atmospheric correction methods to classify remotely sensed data to detect liquefaction of the February 2011 earthquake in Christchurch , 2013 .

[26]  Alejandro Hinojosa-Corona,et al.  Optimization of legacy lidar data sets for measuring near‐field earthquake displacements , 2014 .

[27]  Kazuya Ishitsuka,et al.  Detection and mapping of soil liquefaction in the 2011 Tohoku earthquake using SAR interferometry , 2012, Earth, Planets and Space.

[28]  Wen Bin Wu,et al.  Application of Unmanned Aerial Vehicle Remote Sensing for Geological Disaster Reconnaissance along Transportation Lines: A Case Study , 2012 .

[29]  Ellen M. Rathje,et al.  The Role of Remote Sensing in Earthquake Science and Engineering: Opportunities and Challenges , 2008 .

[30]  Arko Lucieer,et al.  Time Series Analysis of Landslide Dynamics Using an Unmanned Aerial Vehicle (UAV) , 2015, Remote. Sens..

[31]  Eric J. Fielding,et al.  Near-Field Deformation from the El Mayor–Cucapah Earthquake Revealed by Differential LIDAR , 2012, Science.