Spatial prediction of landslide susceptibility by combining evidential belief function,logistic regression and logistic model tree

Abstract

In this study, we introduced novel hybrid of evidence believe function (EBF) with logistic regression (EBF-LR) and logistic model tree (EBF-LMT) for landslide susceptibility modelling. Fourteen conditioning factors were selected, including slope aspect, elevation, slope angle, profile curvature, plan curvature, topographic wetness index (TWI), stream sediment transport index (STI), stream power index (SPI), distance to rivers, distance to faults, distance to roads, lithology, normalized difference vegetation index (NDVI), and land use. The importance of factors was assessed using correlation attribute evaluation method. Finally, the performance of three models was evaluated using the area under the curve (AUC). The validation process indicated that the EBF-LMT model acquired the highest AUC for the training (84.7%) and validation (76.5%) datasets, followed by EBF-LR and EBF models. Our result also confirmed that combination of a decision tree-logistic regression-based algorithm with a bivariate statistical model lead to enhance the prediction power of individual landslide models.     

Wave-ice dynamical interaction: a numerical model and its application

In this paper, an ice floe inner stress caused by the wave-induced bending moment is derived to estimate the stress failure of ice floe. The strain and stress failures are combined to establish a wave-induced ice yield scheme. We added ice stress and strain failure module in the Finite-Volume Community Ocean Model (FVCOM), which already includes module of ice-induced wave attenuation. Thus a fully coupled wave-ice dynamical interaction model is established based on the ice and wave modules of FVCOM. This model is applied to reproduce the ice and wave fields of the breakup events observed during the second Sea Ice Physics and Ecosystem Experiment (SIPEX-2) voyage. The simulation results show that by adopting the combined wave-induced ice yield scheme, the model can successfully predict the ice breakup events, which the strain failure model is unable to predict. By comparing the critical significant wave height deduced from strain and stress failure schemes, it is concluded that the ice breakup is caused by the strain failure when wave periods are shorter than a threshold value, while the stress failure is the main reason for the ice breakup when wave periods are longer than the threshold value. Neglecting either of these two ice-break inducement mechanisms could overestimate the ice floe size, and thus underestimate the velocity of the ice lateral melt and increase the error of simulation of polar ice extent.     

FVCOM model estimate of the location of Air France 447

On June 1, 2009, Air France AF447 disappeared in the Equatorial Atlantic Ocean en route from Rio de Janeiro, Brazil, to Paris, France. On June 6–19, 2009, bodies and debris from the aircraft were recovered floating in the equatorial ocean. This paper describes efforts on using the global–local nested finite volume community ocean model (FVCOM) to model reversely the tracks of bodies and debris back to the time of the crash and to help searchers locate the cockpit voice and flight data recorders and learn why this tragic accident occurred. To validate the reliability and reality of FVCOM, eight surface drifters were deployed by the French Bureau d’Enquêtes et d’Analyses pour la sécurité de l’aviation civile (BEA) near the last known position in early June 2010 for a period of 3?weeks. These drifter data were used to optimize the spatial and temporal correlation scales of the adaptive sampling data assimilation method of FVCOM. Applying an optimized FVCOM system to assimilate all available drifter- and float-tracking-derived currents in May–June 2009 under three different wind conditions, we reproduced the June 2009 current fields in the area near the LKP and used these fields to reversely track bodies and debris from locations where they were found to the time when the crash occurred. Possible locations for the crashed plane were suggested based on our model results and were made available to the French investigators and the Woods Hole Oceanographic Institution REMUS autonomous underwater vehicle Operations Group who successfully located the aircraft debris field in April 2011 on the seafloor at a depth of 3,900?m.     

Impacts of sea level rise on future storm-induced coastal inundations over massachusetts coast

Natural Hazards - Hurricanes (tropical cyclones) and nor'easters (extratropical cyclones) are two major storm systems for flood risk over the Massachusetts coast. Severe coastal inundation...