InSAR for Geoscientists
Description of Tutorial:
Synthetic aperture radar interferometry (InSAR) utilizes phase differences between two or more SAR observations for deriving digital elevation models (DEMs) of the earth's surface, and estimating surface deformation due to oil, water, and natural gas extraction, and detecting displacements of glaciers, monitoring low deformation rates associated with mining practices over a large spatial extent. This half-day short course introduces the principles and applications of InSAR, DInSAR and TimeSAR, and provides in-depth discussions on the current data processing methods and algorithms required to infer surface bio/geophysical variables. New techniques including stacking, time-series analysis of linear/non-linear surface deformation, ScanSAR and polarimetric InSAR and amplitude based subpixel offset tracking will be reviewed with results from ongoing projects and recent publications. Interferometric data processing strategies with specific applications in DEM generation, measuring building sinking, and monitoring earthquake deformation, detecting subsidence from water withdrawal, underground mining, estimating tree height, and the conjunctive use of GPS with timeSAR will be discussed. The short course will also provide an opportunity to explore pros and cons of Radar w/ LiDAR in common application areas, and how and why each data and methods might be used.
The topics will be covered in this workshop:
I. Synthetic Aperture Radar Fundamentals
A. Basic SAR concepts
B. SAR principles
II. How to get SAR data?
A. SAR interferometry (InSAR)
B. Differential SAR interferometry (DInSAR)
C. timeSAR - Pertinent Scatterer Interferometry
D. Polarimetric SAR interferometry (PolInSAR)
IV. Interferometric data processing
A. InSAR general processing
B. Advanced InSAR processing and optimization
D. Quality control
V. Applications of SAR interferometry and case studies
About the Speakers
Dr. Abuduwasiti Wulamu
Dr. Wulamu (aka Ghulam in publications) is an Assistant Research Professor with the Department of Earth & Atmospheric Sciences. He received his B.S. in Physical Geography and M.S. in Cartography & GIS from Xinjiang University in 1998 and 2001, respectively, and earned his Ph.D. in Cartography & GIS from Peking University in 2006. After graduated from Peking University, he joined the Image Sciences, Computer Sciences and Remote Sensing Laboratory (LSIIT) UMR 7005 at University of Strasbourg (also known as University of Louis Pasteur), France as a Post Doctoral Research Associate in 2006. From 2007 to 2009, he held a Geospatial Analyst position in the Department of Biology, and served as the Chief Architect for GIS systems in the Center for Environmental Sciences at SLU.
He is currently teaching graduate and undergraduate courses in InSAR, Microwave Remote Sensing at Saint Louis University, USA, and has presented a number of papers and workshops in InSAR at national and international conferences. His research covers a wide spectrum of areas including retrieval of surface bio/geophysical variables using SAR and LiDAR, especially InSAR/DInSAR techniques and polarimetry, monitoring of natural hazards, with some sideline interests in remote sensing of arid environments.
Dr. Wulamu's professional and technical expertise encompasses optical, hyperspectral and thermal remote sensing, LiDAR, Synthetic Aperture Radar (SAR) and Interferometric SAR (InSAR) and polarimetric SAR data processing. Dr. Wulamu has authored over 25 peer-reviewed journal publications, one book chapter, and presented more than 25 conference papers and workshops.
Ghulam, A., Kusky, T., Teyip, T. and Qin, Q. (2011). Subcanopy soil moisture modeling in n-dimensional spectral feature space. Photogrammetric Engineering and Remote Sensing, 77(2):149-156.
Gabr, S., Ghulam, A., Kusky, T.M. (2010). Detecting areas of high-potential gold mineralization using ASTER data. Ore Geology Reviews,38(1-2): 59-69.
Kusky,T., Ghulam, A., Wang, L., et al. (2010). Focusing Seismic Energy Along faults through time-variable rapture modes: Wenchuan Earhtuake, China. Journal of Earth Science, 21 (6): 910-922.
Ghulam, A., Amer, R., Ripperdan, R. (2010). A filtering approach to improve deformation accuracy using large baseline, low coherence DInSAR phase images. Proceedings of the 2010 IEEE International Geoscience and Remote Sensing Symposium, July 25-30, 2010, Honolulu, Hawaii, pp. 3494-3497.
Zarauz, J., Ghulam, A., Pasken, R. (2010). Sulfur dioxide estimations in the planetary boundary layer using ozone monitoring instrument. ASPRS/CaGIS 2010 Specialty Conference - Geospatial Data and Geovisualization: Environment, Security, and Society, November 15-19, 2010. Orlando, FL.
Ghulam, A., Li, Z-L., Qin, Q., Yimit, H., Wang, J. (2008). Estimating crop water stress with ETM+ NIR and SWIR data. Agricultural and Forest Meteorology,148:1679-1695.
Ghulam, A., Qin, Q., Teyip, T., and Li, Z-L. (2007). Modified perpendicular drought index (MPDI): a real-time drought monitoring method. ISPRS Journal of Photogrammetry and Remote Sensing, 62: 150-164.