Flood susceptibility map** with machine learning, multi-criteria decision analysis and ensemble using Dempster Shafer Theory
Floods are one of the most widespread natural hazards occurring across the globe. The
main objective of this study was to produce flood susceptibility maps for the province of …
main objective of this study was to produce flood susceptibility maps for the province of …
An ensemble prediction of flood susceptibility using multivariate discriminant analysis, classification and regression trees, and support vector machines
Floods, as a catastrophic phenomenon, have a profound impact on ecosystems and human
life. Modeling flood susceptibility in watersheds and reducing the damages caused by …
life. Modeling flood susceptibility in watersheds and reducing the damages caused by …
Predictive Performances of ensemble machine learning algorithms in landslide susceptibility map** using random forest, extreme gradient boosting (XGBoost) and …
Across the globe, landslides have been recognized as one of the most detrimental
geological calamities, especially in hilly terrains. However, the correct determination of …
geological calamities, especially in hilly terrains. However, the correct determination of …
Flood susceptibility assessment using GIS-based support vector machine model with different kernel types
Statistical learning theory is the basis of support vector machine (SVM) technique. This
technique in natural hazard assessment is getting extremely popular these days. It contains …
technique in natural hazard assessment is getting extremely popular these days. It contains …
Flood detection and susceptibility map** using sentinel-1 remote sensing data and a machine learning approach: Hybrid intelligence of bagging ensemble based …
Map** flood-prone areas is a key activity in flood disaster management. In this paper, we
propose a new flood susceptibility map** technique. We employ new ensemble models …
propose a new flood susceptibility map** technique. We employ new ensemble models …
Landslide susceptibility map** using certainty factor, index of entropy and logistic regression models in GIS and their comparison at Mugling–Narayanghat road …
Landslide susceptibility maps are vital for disaster management and for planning
development activities in the mountainous country like Nepal. In the present study, landslide …
development activities in the mountainous country like Nepal. In the present study, landslide …
Landslide spatial modeling: Introducing new ensembles of ANN, MaxEnt, and SVM machine learning techniques
W Chen, HR Pourghasemi, A Kornejady, N Zhang - Geoderma, 2017 - Elsevier
Abstract “Spatial contraindication” is what exactly landslide susceptibility models have been
seeking. They are designed for depicting perilous land activities, be it natural or …
seeking. They are designed for depicting perilous land activities, be it natural or …
Identifying the essential conditioning factors of landslide susceptibility models under different grid resolutions using hybrid machine learning: A case of Wushan and …
This study attempts to identify the essential conditioning factors of landslides to increase the
predictive ability of landslide susceptibility models and explore the effects of different grid …
predictive ability of landslide susceptibility models and explore the effects of different grid …
Landslide susceptibility map** using GIS-based multi-criteria decision analysis, support vector machines, and logistic regression
Identification of landslides and production of landslide susceptibility maps are crucial steps
that can help planners, local administrations, and decision makers in disaster planning …
that can help planners, local administrations, and decision makers in disaster planning …
Ensemble machine-learning-based geospatial approach for flood risk assessment using multi-sensor remote-sensing data and GIS
In this paper, an ensemble method, which demonstrated efficiency in GIS based flood
modeling, was used to create flood probability indices for the Damansara River catchment in …
modeling, was used to create flood probability indices for the Damansara River catchment in …