Reference : Multi-Temporal DInSAR to Characterise Landslide Ground Deformations in a Tropical Urb...
Scientific journals : Article
Physical, chemical, mathematical & earth Sciences : Earth sciences & physical geography
http://hdl.handle.net/2268/226530
Multi-Temporal DInSAR to Characterise Landslide Ground Deformations in a Tropical Urban Environment: Focus on Bukavu (DR Congo)
English
Nobile, Adriano mailto [Royal Museum for Central Africa > Department of Earth Sciences > Natural Hazards > >]
Dille, Antoine mailto [Royal Museum for Central Africa > Earth Sciences > Natural Hazards > >]
Monsieurs, Elise mailto [Université de Liège - ULiège > Département de géographie > Unité de géographie physique et quaternaire (UGPQ) >]
Basimike, Joseph mailto [Université Officielle de Bukavu > Department of Geology > > >]
Mugaruka Bibentyo, Toussaint mailto [Université Officielle de Bukavu > Department of Geology > > >]
d'Oreye, Nicolas mailto [National Museum of Natural History > Department of Geophysics/Astrophysics > > >]
Kervyn, François mailto [Royal Museum for Central Africa > Earth Sciences > Natural Hazards > >]
Dewitte, Olivier mailto [Royal Museum for Central Africa > Earth Sciences > Natural Hazards > >]
2018
Remote Sensing
MDPI AG
10
4
Radar Interferometry for Geohazards
626
Yes (verified by ORBi)
International
2072-4292
[en] DInSAR ; landslide ; validation ; tropical environment ; urban environment
[en] Landslides can lead to high impacts in less developed countries, particularly in tropical environments where a combination of intense rainfall, active tectonics, steep topography, and high population density can be found. However, the processes controlling landslide initiation and their evolution through time remains poorly understood. Here we show the relevance of the use of the multi-temporal differential radar interferometric (DInSAR) technique to characterise ground deformations associated with landslides in the rapidly-expanding city of Bukavu (DR Congo). We use 70 COSMO-SkyMed synthetic aperture radar images acquired between March 2015 and April 2016 with a mean revisiting time of eight days to produce ground deformation rate maps and displacement time series using the small baseline subset approach. We find that various landslide processes of different ages, mechanisms, and states of activity can be identified. Ground deformations revealed by DInSAR are found consistent with field observations and differential GPS measurements. Our analysis highlights the ability of DInSAR to grasp landslide deformation patterns affecting the complex tropical-urban environment of the city of Bukavu. However, longer time series will be needed to infer landside responses to climate, seismic, and anthropogenic drivers.
http://hdl.handle.net/2268/226530
10.3390/rs10040626

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