Rabin Chakrabortty

TL;DR: In this article, an attempt has been made to delineate the groundwater potenstation in a remote sensing and geographical information system (RS-GIS) based model for modeling and mapping of groundwater resources.

TL;DR: In this article, the effectiveness of EBF, binomial logistic regression (LR) and ensemble EBF and LR (EBF-LR) model with remote sensing and GIS techniques for flood susceptibility mapping and spatial prediction of flood-susceptible areas in the Koiya river basin of West Bengal, India.

TL;DR: Topographical and hydrological parameters, e.g., altitude, slope, rainfall, and the river’s distance, were the most effective parameters in the flash flood susceptibility modeling of Kalvan watershed.

TL;DR: It can be concluded that the DLNN model and its ensemble with the PSO algorithm can be used as a novel and practical method to predict gully erosion susceptibility, which can help planners and managers to manage and reduce the risk of this phenomenon.

TL;DR: In this paper, the authors presented flood susceptible areas in Ajoy River basin using Support Vector Machine (SVM), Random Forest (RF) and Biogeography Based Optimization (BBO) model in GIS environment.