Forest fire disaster is currently the subject of intense research worldwide. The development of accurate strategies to prevent potential impacts and minimize the occurrence of disastrous …
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 …
In various types of geo-environmental problems in the fringing area of Chhotanagpur plateau in India, gully erosion is one of the vulnerable issue. In our current research, using …
In the digital soil mapping (DSM) framework, machine learning models quantify the relationship between soil observations and environmental covariates. Generally, the most …
Flood is one of the most destructive natural disasters which cause great financial and life losses per year. Therefore, producing susceptibility maps for flood management are …
This study aimed to develop a novel framework for risk assessment of nitrate groundwater contamination by integrating chemical and statistical analysis for an arid region. A standard …
S Talukdar, KU Eibek, S Akhter, SK Ziaul… - Ecological …, 2021 - Elsevier
Land-use and land-cover (LULC) changes have become a crucial issue that urgently needs to be addressed due to global environmental change. Many studies have employed remote …
Gully erosion is one of the most effective drivers of sediment removal and runoff from highland areas to valley floors and stable channels, where continued off-site effects of water …
This work proposes a new approach by integrating statistical, machine learning, and multi- criteria decision analysis, including artificial neural network (ANN), logistic regression (LR) …