Measurement of ground displacement from optical satellite image correlation using the free open-source software MicMac

被引:122
作者
Rosu, Ana-Maria [1 ]
Pierrot-Deseilligny, Marc [2 ]
Delorme, Arthur [1 ]
Binet, Renaud [3 ]
Klinger, Yann [1 ]
机构
[1] Inst Phys Globe Paris, Lab Tecton & Mecan Lithosphere, F-75238 Paris 05, France
[2] Inst Natl Informat Geog & Forestiere, Ecole Natl Sci Geog, Lab Geomat Appliquee, Champs Sur Marne, France
[3] Ctr Natl Etudes Spati, Lab PS TIS, Paris, France
关键词
Satellite image; Ground displacement; Image correlation; COSI-Corr; Medicis; MicMac; SLIP-DISTRIBUTION; TIBETAN PLATEAU; EARTHQUAKE; DEFORMATION; SURFACE; AERIAL; MODEL;
D O I
10.1016/j.isprsjprs.2014.03.002
中图分类号
P9 [自然地理学];
学科分类号
0705 ; 070501 ;
摘要
Image correlation is one of the most efficient techniques to determine horizontal ground displacements due to earthquakes, landslides, ice flows or sand dune migrations. Analyzing these deformations allows a better understanding of the causes and mechanisms of the events. By using sub-pixel correlation on before- and after-event ortho-images obtained from high resolution satellite images it is possible to compute the displacement field with high planimetric resolution. In this paper, we focus on measuring the ground displacements due to seismotectonic events. The three sub-pixel correlators used are: COSI-Corr - developed by Caltech, a free, closed-source correlator, dependent on commercial software (ENVI) and widely used by the geoscience community for measuring ground displacement; Medicis - developed by CNES, also a closed-source correlator capable of measuring this type of deformation; and MicMac - developed by IGN, the free open-source correlator we study and tune for measuring fine ground displacements. We measured horizontal ground deformation using these three correlators on SPOT images in three study cases: the 2001 Kokoxili earthquake, the 2005 dyke intrusion in the Afar depression and the 2008 Yutian earthquake. (C) 2014 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS) Published by Elsevier B.V. All rights reserved.
引用
收藏
页码:48 / 59
页数:12
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