Learn More
Surface fissures are important indicators for slope instability and their patterns reveal information about the distribution of strain and mechanical processes. The increasing availability of sub-decimeter resolution aerial images may enable the detection and mapping of such features with imagery. This study combines Gaussian matched filters and first order(More)
—Active learning (AL) algorithms have been proven useful in reducing the number of required training samples for remote sensing applications; however, most methods query samples pointwise without considering spatial constraints on their distribution. This may often lead to a spatially dispersed distribution of training points unfavorable for visual image(More)
Analyse spatiale de la susceptibilité des versants aux glissements de terrain. ABSTRACT. GIS are more and more used to evaluate landslide susceptibility. Among the different methods generally used, bivariate analyses are considered as the more robust techniques, particularly the Weight of Evidence technique. However, one major drawback of this technique is(More)
Active learning (AL) is a powerful framework to reduce labeling costs in supervised classification. However, spatial constraints on the sampling design have not yet received much attention and still pose problems for the application of AL on remote sensing data. In this study such issues are addressed in the context of landslide inventory mapping and it is(More)
Spatial analysis and GIS technology are still seldom used to evaluate and map landslide risk. Especially, few studies concern the automatic mapping of landslide risk at large scales (1:10,000) corresponding to the scale of the legal regulation plans in France. Maquaire et al., Analyse spatiale du risque « glissement de terrain » 2 This paper presents a(More)
  • 1