Imaging and Computing Seminar

Sebastien Leprince, Geological and Planetary Sciences, Caltech

Title:
Environmental Monitoring from Space using Optical Imagery: The Versatility of Sub-Pixel Image Matching.

Group website, Imagin'Labs website.

Abstract:
COSI-Corr is a suite of algorithms for precise “Co-registration of Optically Sensed Images and Correlation,” which was developed within the Division of Geological and Planetary Sciences at Caltech and was first released to the academic community in 2007. Its capability to accurately monitor the Earth's surface deformation using satellite or aerial imagery has since proved useful for a wide variety of applications. I will present the fundamental principles of COSI-Corr, which are the key ingredients to achieve sub-pixel registration and sub-pixel measurement accuracy between multi-temporal images. In particular, I will show how these principles can be applied to various types of images to extract 2D, 3D, or even 4D deformation fields of a given surface. Examples are drawn from recent collaborative studies and include: (1) The study of the Icelandic Krafla rifting crisis that occurred from 1975 to 1984 where we used a combination of archived airborne photographs, declassified spy satellite imagery, and modern satellite acquisitions to propose a detailed 2D displacement field of the ground; (2) The estimation of glacial velocities; (3) The derivation of sand ripples migration rates on Mars using HiRISE imagery; (4) The estimation of ocean swell; (5) The derivation of the 3D ground displacement field induced by the 2010 Mw 7.2 El Mayor- Cucapah Earthquake, as recorded from pre- and post-event LiDAR acquisitions; (6) And, a new space mission concept, in partnership with the NASA Jet Propulsion Laboratory, where sub-pixel image matching could be used to image the propagation of seismic waves at the surface of the Earth. Finally, I will highlight the potential for applying these techniques on a large scale to provide global monitoring of our environment.