Landslide prediction from machine learning     

Oliver Korup  Amelie Stolle 《Geology Today》2014,30(1):26-33

Predicting where and when landslides are likely to occur in a specific region of interest remains a key challenge in natural hazards research and mitigation. While the basic mechanics of slope‐failure initiation and runout can be cast into physical and numerical models, a scarcity of sufficiently detailed and real‐time measurements of soil, rock‐mass and groundwater conditions prohibits accurate landslide forecasting. Researchers are therefore increasingly exploring multivariate data analysis techniques from the fields of data mining or machine learning in order to approximate future occurrences of landslides from past distribution patterns. This work has elucidated patterns of spatial susceptibility, but temporal forecasts have remained largely empirical. Most machine learning techniques achieve overall success rates of 75–95 percent. Whilst this may seem very promising, issues remain with data input quality, potential overfitting and commensurate inadequate choice of prediction models, inadvertent inclusion of redundant or noise variables, and technical limits to predicting only certain types and sizes of landslides. Simpler models provide only slightly inferior predictions to more complex models, and should guide the way for a more widespread application of data mining in regional landslide prediction. This approach should especially be communicated to planners and decision makers. Future research may want to develop: (1) further best‐practice guidelines for model selection; (2) predictions of occurrence and runout of large slope failures at the regional scale; and (3) temporal forecasts of landslides.  相似文献   

Speciation of dissolved copper and cadmium in the Loire estuary and over the North Biscay continental shelf in spring     

Matthieu Waeles  Ricardo D. Riso  Jean-Yves Cabon  Jean-François Maguer  Stéphane L'Helguen 《Estuarine, Coastal and Shelf Science》2009

Dissolved cadmium and copper species were measured in the Loire estuary and the North Biscay Bay continental shelf (France) in spring 2002. Metal behaviours along the salinity gradient, metal fluxes from the Loire system and surface distributions on the continental shelf were described and compared with the ones obtained at a period of higher discharge (i.e., winter 2001). Vertical distributions at different stations were also examined with the aim to assess whether the Loire inputs affect the Cu and Cd speciation over the continental shelf. In the Loire estuary, different metal behaviours were observed from winter. Cu and its various species mostly followed a theoretical dilution line whereas a Cd addition composed of chloro- and organic complexes was observed. According to our estimations, the Cu flux was composed, as in winter, of 40% hydrophobic organic complexes. On the other hand, Cd organic complexes accounted for less in the total dissolved metal flux than they did in winter (55 and 78% for spring and winter, respectively). On the continental shelf, a C₁₈Cu-to-TDCu ratio of 40% was observed in the stratified area under Loire influence. For Cd, the organic fraction was relatively important in the surface waters near the mouth of the estuary and decreased deeper and seaward. Thus, the Cu and Cd speciation on the North Biscay Bay continental shelf are firstly determined by the extent of the estuarine plume. Beyond the estuarine influence, biological processes appeared to be the origin of the observed variations.  相似文献