Multi-Temporal DInSAR to Characterise Landslide Ground Deformations in a Tropical Urban Environment: Focus on Bukavu (DR Congo)
| dc.contributor.author | Nobile, A. | |
| dc.contributor.author | Dille, A. | |
| dc.contributor.author | Monsieurs, E. | |
| dc.contributor.author | Basimike, J. | |
| dc.contributor.author | Bibentyo, T. M. | |
| dc.contributor.author | d Oreye, N. | |
| dc.contributor.author | Kervyn , F. | |
| dc.contributor.author | Dewitte, O. | |
| dc.coverage.spatial | Africa - Central | |
| dc.coverage.spatial | Congo, The Democratic Republic of the | |
| dc.coverage.temporal | 2015-2016 | |
| dc.date | 2018 | |
| dc.date.accessioned | 2024-03-14T13:16:19Z | |
| dc.date.available | 2024-03-14T13:16:19Z | |
| dc.identifier.uri | https://orfeo.belnet.be/handle/internal/12119 | |
| dc.description | 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. | |
| dc.language | eng | |
| dc.publisher | mdpi | |
| dc.title | Multi-Temporal DInSAR to Characterise Landslide Ground Deformations in a Tropical Urban Environment: Focus on Bukavu (DR Congo) | |
| dc.type | Article | |
| dc.subject.frascati | Earth and related Environmental sciences | |
| dc.audience | Scientific | |
| dc.subject.free | Natural hazards | |
| dc.source.title | Remote Sensing | |
| dc.source.volume | 10; Radar Interferometry for Geohazards | |
| Orfeo.peerreviewed | Yes | |
| dc.identifier.doi | doi:10.3390/rs10040626 | |
| dc.identifier.url | http://www.mdpi.com/2072-4292/10/4/626 | |
| dc.identifier.rmca | 5342 |