Surface displacement field of landslides is a key parameter to access to their geometries and mechanical properties. Surface displacements can be calculated using remote-sensing methods such as interferometry for radar data and image correlation for optical data.
External Contact Person:
Christophe Delacourt
Email:
christophe.delacourt [at] univ-brest.fr
Undefined
Bibliographic reference:
Delacourt, C., Allemand, P., Berthier, E., Raucoules, D., Casson, B., Grandjean, P., ... & Varel, E. (2007). Remote-sensing techniques for analysing landslide kinematics: a review. Bulletin de la Société Géologique de France,178(2), 89-100.
As a geological hazard, landslides cause extensive property damage and sometimes result in loss of life. Thus, it is necessary to assess areas that are vulnerable to future landslide events to mitigate potential damage. For this purpose, change detection analysis and a generalized additive model were applied to investigate potential landslide occurrences within the Sacheoncheon area, Korea. An unsupervised change detection analysis based on multi-temporal object-based segmentation of high-resolution remote sensing data and thresholding was adopted to detect landslide-prone areas.
External Contact Person:
N.W. Park
Email:
nwpark [at] kigam.re.kr
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Bibliographic reference:
Park, N. W., & Chi, K. H. (2008). Quantitative assessment of landslide susceptibility using high‐resolution remote sensing data and a generalized additive model. International Journal of Remote Sensing, 29(1), 247-264.
In the recent years radar interferometry (InSAR) has become an important tool in various studies. It can be used to produce accurate digital elevation models and observe small surface displacements. Differential interferometry (DInSAR) can detect movements in the radar look direction that are in the order of wavelength used, i.e. less than one centimetre with ERS data. In the presented study DInSAR has been used to observe surface movements in western Slovenia.
External Contact Person:
Kristof Ostir
Email:
kristof [at] zrc-sazu.si
Undefined
Bibliographic reference:
Oštir, K., & Komac, M. (2007). PSInSAR and DInSAR methodology comparison and their applicability in the field of surface deformations—a case of NW Slovenia. Geologija, 50(1), 77-96.
Landslide inventory mapping is an indispensable prerequisite for reliable hazard and risk analysis, and with the increasing availability of very high resolution (VHR) remote sensing imagery the creation and updating of such inventories on regular bases and directly after major events is becoming possible. The diversity of landslide processes and spectral similarities of affected areas with other landscape elements pose major challenges for automated image processing, and time-consuming manual image interpretation and field surveys are still the most commonly applied mapping techniques.
External Contact Person:
Email:
Undefined
Bibliographic reference:
Stumpf, A., & Kerle, N. (2011). Object-oriented mapping of landslides using Random Forests. Remote Sensing of Environment, 115(10), 2564-2577.
Landslides are a major type of geohazards claiming thousands of casualties and billions of dollars in property damages every year. Catastrophic landslide activities are often triggered by some extreme events such as earthquakes, excessive precipitations, or volcanic eruptions. Quickly identifying the spatial distribution of landslides induced by these extreme events is crucial for coordinating rescue efforts and planning in situ investigations.
External Contact Person:
Email:
Undefined
Bibliographic reference:
Yang, X., & Chen, L. (2010). Using multi-temporal remote sensor imagery to detect earthquake-triggered landslides. International Journal of Applied Earth Observation and Geoinformation, 12(6), 487-495.
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