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Nat. Hazards Earth Syst. Sci., 16, 1035-1048, 2016
https://doi.org/10.5194/nhess-16-1035-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
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 CERENA, Instituto Superior Técnico, University of Lisbon, Lisbon, Portugal
Abstract. A method for semiautomated landslide detection and mapping, with the ability to separate source and run-out areas, is presented in this paper. It combines object-based image analysis and a support vector machine classifier and is tested using a GeoEye-1 multispectral image, sensed 3 days after a major damaging landslide event that occurred on Madeira Island (20 February 2010), and a pre-event lidar digital terrain model. The testing is developed in a 15 km2 wide study area, where 95 % of the number of landslides scars are detected by this supervised approach. The classifier presents a good performance in the delineation of the overall landslide area, with commission errors below 26 % and omission errors below 24 %. In addition, fair results are achieved in the separation of the source from the run-out landslide areas, although in less illuminated slopes this discrimination is less effective than in sunnier, east-facing slopes.

Citation: Heleno, S., Matias, M., Pina, P., and Sousa, A. J.: Semiautomated object-based classification of rain-induced landslides with VHR multispectral images on Madeira Island, Nat. Hazards Earth Syst. Sci., 16, 1035-1048, https://doi.org/10.5194/nhess-16-1035-2016, 2016.
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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.
A method for semi-automatic landslide detection and mapping is presented and tested using a very...
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