Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-3/W3, 595-599, 2015
http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XL-3-W3/595/2015/
doi:10.5194/isprsarchives-XL-3-W3-595-2015
© Author(s) 2015. This work is distributed
under the Creative Commons Attribution 3.0 License.
 
20 Aug 2015
TOWARDS TIME-SERIES PROCESSING OF VHR SATELLITE IMAGES FOR SURFACE DEFORMATION DETECTON AND MEASUREMENTS
A. Stumpf1,2,3, C. Delacourt2, and J. P. Malet1 1Institut de Physique du Globe de Strasbourg - CNRS UMR 7516, University of Strasbourg/EOST, 5 rue Descartes, 67084 Strasbourg, France
2Laboratoire Domaines Océaniques - CNRS UMR 6538, Institut Universitaire Européen de la Mer, University of Western Brittany, rue Dumont d'Urville, 29280 Plouzané, France
3Laboratoire Image, Ville, Environnement - CNRS UMR 7362, University of Strasbourg, 3 rue de l'Argonne, 67000 Strasbourg, France
Keywords: deformation measurement, image correlation, high-performance computing, satellite remote sensing Abstract. The increasing fleet of VHR optical satellites (e.g. Pléiades, Spot 6/7, WorldView-3) offers new opportunities for the monitoring of surface deformation resulting from gravitational (e.g. glaciers, landslides) or tectonic forces (coseismic slip). Image correlation techniques have been developed and successfully employed in many geoscientific studies to quantify horizontal surface deformation at sub-pixel precision. The analysis of time-series, however, has received less attention in this context and there is still a lack of techniques that fully exploit archived image time-series and the increasing flux of incoming data. This study targets the development of an image correlation processing chain that relies on multiple pair-wise matching to exploit the redundancy of deformation measurements recorded at different view angles and over multiple time steps. The proposed processing chain is based on a hierarchical image correlation scheme that readily uses parallel processing. Since pair-wise matching can be performed independently the distribution of individual tasks is straightforward and yields to significant reductions of the overall runtime scaling with the available HPC infrastructure. We find that it is more convenient to implement experimental analytical tasks in a high-level programming language (i.e. R) and explore the use of parallel programming to compensate for performance bottlenecks of the interpreted language. Preliminary comparisons against maps from domain expert suggest that the proposed methodology is suitable to eliminate false detections and, thereby, enhances the reliability of correlation-based detections of surface deformation.
Conference paper (PDF, 3130 KB)


Citation: Stumpf, A., Delacourt, C., and Malet, J. P.: TOWARDS TIME-SERIES PROCESSING OF VHR SATELLITE IMAGES FOR SURFACE DEFORMATION DETECTON AND MEASUREMENTS, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-3/W3, 595-599, doi:10.5194/isprsarchives-XL-3-W3-595-2015, 2015.

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