IEEE Geoscience and Remote Sensing Letters
The assessment of sediments produced, displaced, and deposited by landslides is important for hazard evaluation and mitigation. However, existing methods for landslide identification seldom address the effective separation of their internal constituents (source and transport). This letter presents a methodology to classify these constituents in very high resolution remotely sensed images. It is based on an ensemble of Texton classifiers using spectral and textural information. An experimental strategy is devised to evaluate different ensembles of features. An overall accuracy of above 90% is obtained in a cross-validation procedure in GeoEye-1 images from test sites in Madeira Island. © 2004-2012 IEEE.
Year of publication: 2016