Mass Movement

Characterization of Landslide Deformations in Three Gorges Area Using Multiple InSAR Data Stacks

In the areas with steep topography and vulnerable geological condition, landslide deformation monitoring is an important task for risk assessment and management.

External Contact Person: 

Lu Zhang

Email: 

luzhang [at] whu.edu.cn
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Bibliographic reference: 

Tantianuparp, P., Shi, X., Zhang, L., Balz, T., & Liao, M. (2013). Characterization of landslide deformations in three gorges area using multiple InSAR data stacks. Remote Sensing5(6), 2704-2719.

Bréifne Area Landslides Susceptibility Mapping

The aims of this project were to identify and map landslide occurences in the Bréifne area in norwth-west Ireland; to proue a landslide susceptibility map using GIS; and to test a first approach for a methodology for systematic landslide mapping for the whole of Ireland. The methodology used to derive the final susceibility maps was compiled from several literature examples (Santacana et a l. 2003, Tangestani 2003, Morton et al. 2003).

External Contact Person: 

Email: 

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Bibliographic reference: 

Pellicer, X. M., & Verbruggen, K. (2006). Testing a Remote Sensing based methodology for systematic production of landslides susceptibility maps for Ireland. In Geophysical Research Abstracts (Vol. 8, p. 06847).

Use of LIDAR in landslide investigations: a review

This paper presents a short history of the appraisal of laser scanner technologies in geosciences used for imaging relief by high-resolution digital elevation models (HRDEMs) or 3D models.

External Contact Person: 

Michel Jaboyedoff

Email: 

michel.jaboyedoff [at] unil.ch
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Bibliographic reference: 

Teshebaeva, K., Sudhaus, H., Wetzel, H. U., Echtler, H., Zubovich, A., & Roessner, S. (2013, October). Radar remote sensing for surveying and monitoring of earthquakes and mass movements in Southern Kyrgyzstan. Inand Young Researchers’ Forum.

Radar remote sensing for surveying and monitoring of earthquakes and mass movements in Southern Kyrgyzstan

Kyrgyzstan is landlocked mountainous nation of around five million people, which borders China, Kazakhstan, Tajikistan and Uzbekistan. The total area of high mountainous terrain, alpine meadows and pastures exceeds 70% of the Republic’s territory, whereas the greater part of the Kyrgyz Republic is occupied by the Tien-Shan mountains. Kyrgyzstan is a highly active seismic region and has been shaken by numerous significant earthquakes as a consequence of the ongoing collision between the Indian and Eurasian tectonic plates.

External Contact Person: 

Kanayim Teshebaeva

Email: 

k.teshebaeva [at] caiag.kg
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Bibliographic reference: 

Teshebaeva, K., Sudhaus, H., Wetzel, H. U., Echtler, H., Zubovich, A., & Roessner, S. (2013, October). Radar remote sensing for surveying and monitoring of earthquakes and mass movements in Southern Kyrgyzstan. Inand Young Researchers’ Forum.

Remote sensing as a tool for development of landslide databases: The case of the Messina Province (Italy) geodatabase

Landslide geodatabases, including inventories and thematic data, today are fundamental tools for national and/or local authorities in susceptibility,

External Contact Person: 

Email: 

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Bibliographic reference: 

Ciampalini, A., Raspini, F., Bianchini, S., Frodella, W., Bardi, F., Lagomarsino, D., ... & Casagli, N. (2015). Remote sensing as tool for development of landslide databases: The case of the Messina Province (Italy) geodatabase.Geomorphology.

Robust Automated Image Co-Registration of Optical Multi-Sensor Time Series Data: Database Generation for Multi-Temporal Landslide Detection

Reliable multi-temporal landslide detection over longer periods of time requires multi-sensor time series data characterized by high internal geometric stability, as well as high relative and absolute accuracy.

External Contact Person: 

Robert Behling

Email: 

behling [at] gfz-potsdam.de
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Bibliographic reference: 

Behling, R., Roessner, S., Segl, K., Kleinschmit, B., & Kaufmann, H. (2014). Robust automated image co-registration of optical multi-sensor time series data: Database generation for multi-temporal landslide detection. Remote Sensing6(3), 2572-2600.

Automated Spatiotemporal Landslide Mapping over Large Areas Using RapidEye Time Series Data

In the past, different approaches for automated landslide identification based on multispectral satellite remote sensing were developed to focus on the analysis of the spatial distribution of landslide occurrences related to distinct triggering events.

External Contact Person: 

Robert Behling

Email: 

behling [at] gfz-potsdam.de
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Bibliographic reference: 

Behling, R., Roessner, S., Kaufmann, H., & Kleinschmit, B. (2014). Automated spatiotemporal landslide mapping over large areas using rapideye time series dataRemote Sensing6(9), 8026-8055.

Semi-automatic recognition and mapping of rainfall induced shallow landslides using optical satellite images

We present a method for the semi-automatic recognition and mapping of recent rainfall induced shallow landslides. The method exploits VHR panchromatic and HR multispectral satellite images, and was tested in a 9.4 km2 area in Sicily, Italy, where on 1 October 2009 a high intensity rainfall event caused shallow landslides, soil erosion, and inundation.

External Contact Person: 

Alessandro Mondini

Email: 

Alessandro.Mondini [at] irpi.cnr.it
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Bibliographic reference: 

Mondini, A. C., Guzzetti, F., Reichenbach, P., Rossi, M., Cardinali, M., & Ardizzone, F. (2011). Semi-automatic recognition and mapping of rainfall induced shallow landslides using optical satellite images. Remote Sensing of Environment115(7), 1743-1757.

Remote-sensing techniques for analysing landslide kinematics: a review

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
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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.

Quantitative assessment of landslide susceptibility using high-resolution

As a geological

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 modelInternational Journal of Remote Sensing29(1), 247-264.

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