Journal
NATURAL HAZARDS AND EARTH SYSTEM SCIENCES
Volume 16, Issue 4, Pages 1035-1048Publisher
COPERNICUS GESELLSCHAFT MBH
DOI: 10.5194/nhess-16-1035-2016
Keywords
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Funding
- Fundacao para a Ciencia e a Tecnologia (FCT) in Portugal [PTDC/ECM/116611/2010]
- FCT [SFRH/BPD/84796/2012]
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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 km(2) 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.
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