Floods are one of nature's most destructive disasters because of the immense damage to
land, buildings, and human fatalities. It is difficult to forecast the areas that are vulnerable to …

To assess the status of hotspots and research trends on geographic information system
(GIS)–based landslide susceptibility (LS), we analysed 1142 articles from the Thomas …

This study deals with landslide susceptibility mapping in the northern part of Lecco Province,
Lombardy Region, Italy. In so doing, a valid landslide inventory map and thirteen …

Recently, floods are occurring more frequently every year around the world due to increased
anthropogenic activities and climate change. There is a need to develop accurate models for …

In this study, we have investigated rainfall induced landslide susceptibility of the Uttarkashi
district of India through the developmentof different novel GIS based soft computing …

Piping erosion is one of the water erosions that cause significant changes in the landscape,
leading to environmental degradation. To prevent losses resulting from tube growth and …

A novel machine learning ensemble model that is a hybridization of Bagging and random
subspace–based naïve Bayes tree (RSNBtree), named as BRSNBtree, was used to prepare …

Preparation of a flood probability map serves as the first step in a flood management
program. This research develops a probability flood map for floods resulting from climate …

In this paper, we developed highly accurate ensemble machine learning models integrating
Reduced Error Pruning Tree (REPT) as a base classifier with the Bagging (B), Decorate (D) …

Determining areas of high groundwater potential is important for exploitation, management,
and protection of water resources. This study assesses the spatial distribution of …