Articles | Volume 16, issue 4
https://doi.org/10.5194/nhess-16-1035-2016
https://doi.org/10.5194/nhess-16-1035-2016
Research article
 | 
26 Apr 2016
Research article |  | 26 Apr 2016

Semiautomated object-based classification of rain-induced landslides with VHR multispectral images on Madeira Island

Sandra Heleno, Magda Matias, Pedro Pina, and António Jorge Sousa

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The 20 February 2010 Madeira Island flash-floods: VHR satellite imagery processing in support of landslide inventory and sediment budget assessment
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Cited articles

Aksoy, B. and Ercanoglu, M.: Landslide identification and classification by object-based image analysis and fuzzy logic: an example from the Azdavay region (Kastamonu, Turkey), Comput. Geosci., 38, 87–98, 2012.
Baioni, D.: Human activity and damaging landslides and floods on Madeira Island, Nat. Hazards Earth Syst. Sci., 11, 3035–3046, https://doi.org/10.5194/nhess-11-3035-2011, 2011.
Barlow, J., Franklin, S., and Martin, Y.: High spatial resolution satellite imagery, DEM derivatives, and image segmentation for the detection of mass wasting processes, Photogramm. Eng. Rem. S., 72, 687–692, 2006.
Beucher, S. and Lantuejoul, C.: Use of watersheds in contour detection, International Workshop on Image Processing, Real-Time Edge and Motion Detection/Estimation, Rennes, France, 17–21 September 1979, 2.1–2.12, 1979.
Borghuis, A. M., Chang, K., and Lee, H. Y.: Comparison between automated and manual mapping of typhoon-triggered landslides from SPOT-5 imagery, Int. J. Remote Sens., 28, 1843–1856, 2007.
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Short summary
A method for semi-automatic landslide detection and mapping is presented and tested using a very high-resolution satellite image, sensed 3 days after a major damaging landslide event that occurred in Madeira Island (20 February 2010). The testing is developed in a 15 km2 wide area, where 95 % of the number of landslides scars is detected by this approach.
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