/pdf/landslide-inventory-maps-new-tools-for-an-old-problem-wkxin2jqxg.pdf

Landslide inventory maps: New tools for an old problem

A review of statistically-based landslide susceptibility models

This paper presents recommended methodologies for the quantitative analysis of landslide hazard, vulnerability and risk at different spatial scales (site-specific, local, regional and national), as well as for the verification and validation of the results. The methodologies described focus on the evaluation of the probabilities of occurrence of different landslide types with certain characteristics. Methods used to determine the spatial distribution of landslide intensity, the characterisation of the elements at risk, the assessment of the potential degree of damage and the quantification of the vulnerability of the elements at risk, and those used to perform the quantitative risk analysis are also described. The paper is intended for use by scientists and practising engineers, geologists and other landslide experts.

/pdf/recommendations-for-the-quantitative-analysis-of-landslide-1culjw5db2.pdf

Recommendations for the quantitative analysis of landslide risk

In this study, we present a flexible, cost-effective, and accurate method to monitor landslides using a small unmanned aerial vehicle (UAV) to collect aerial photography. In the first part, we apply a Structure from Motion (SfM) workflow to derive a 3D model of a landslide in southeast Tasmania from multi-view UAV photography. The geometric accuracy of the 3D model and resulting DEMs and orthophoto mosaics was tested with ground control points coordinated with geodetic GPS receivers. A horizontal accuracy of 7 cm and vertical accuracy of 6 cm was achieved. In the second part, two DEMs and orthophoto mosaics acquired on 16 July 2011 and 10 November 2011 were compared to study landslide dynamics. The COSI-Corr image correlation technique was evaluated to quantify and map terrain displacements. The magnitude and direction of the displacement vectors derived from correlating two hillshaded DEM layers corresponded to a visual interpretation of landslide change. Results show that the algorithm can accurately map displacements of the toes, chunks of soil, and vegetation patches on top of the landslide, but is not capable of mapping the retreat of the main scarp. The conclusion is that UAV-based imagery in combination with 3D scene reconstruction and image correlation algorithms provide flexible and effective tools to map and monitor landslide dynamics.

/pdf/mapping-landslide-displacements-using-structure-from-motion-33k7h9fhei.pdf

Mapping landslide displacements using Structure from Motion (SfM) and image correlation of multi-temporal UAV photography:

http://www.un-spider.org/sites/default/files/Stumpf%20and%20Kerle%202011.pdf

Object-oriented mapping of landslides using Random Forests

http://meetingorganizer.copernicus.org/EGU2010/EGU2010-4437.pdf

Chuan Tang

Papers

Distribution pattern of earthquake-induced landslides triggered by the 12 May 2008 Wenchuan earthquake

GIS modelling of earthquake damage zones using satellite remote sensing and DEM data