Abstract
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.
Highlights
Landslides are complex mass movements that occur on hill slopes due to the action of gravity; they play an important role in the evolution of landforms, while constituting a serious natural hazard in many regions throughout the world
Following the methodology already described, landslide classification maps were produced for the 15 km2 wide study area located within one of the regions most affected by the 2010 landslide event on Madeira
We present a method for semiautomated landslide recognition and mapping of landslide source and run-out area, suitable for Very highresolution (VHR) remote sensing images of rain-induced landslide events
Summary
Landslides are complex mass movements that occur on hill slopes due to the action of gravity; they play an important role in the evolution of landforms, while constituting a serious natural hazard in many regions throughout the world. Landslides can involve flowing, sliding, toppling, or falling and are commonly associated with a trigger: slope failures generally occur within minutes after an earthquake, hours to days after a snowmelt, and days to weeks after an intense rainfall (Guzzetti et al, 2012; Malamud et al, 2004). Urban expansion into hilly or mountainous regions results in more people being exposed to the hazard, increasing landslide risk. Landslide susceptibility and hazard assessment are important tools in land-use planning, in particular to avoid urban expansion into vulnerable areas, reducing future economic and human losses. Past landslides are one of the best indicators of future landslide activity, and mapping landslides is an essential step in hazard assessment (Bucknam et al, 2001; Lahousse et al, 2011; Aksoy et al, 2012; Guzzetti et al, 2012)
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
