Estimate earth fissure hazard based on machine learning in the Qa' Jahran Basin, Yemen.

Earth fissures are potential hazards that often cause severe damage and affect infrastructure, the environment, and socio-economic development. Owing to the complexity of the causes of earth fissures, the prediction of earth fissures remains a challenging task. In this study, we assess earth fissure hazard susceptibility mapping through four advanced machine learning algorithms, namely random forest (RF), extreme gradient boosting (XGBoost), Naïve Bayes (NB), and K-nearest neighbor (KNN).

An Integrated Approach to Assess the Environmental Impacts of Large-Scale Gold Mining: The Nzema-Gold Mines in the Ellembelle District of Ghana as a Case Study.

The mining industry is a significant asset to the development of countries. Ghana, Africa's second-largest gold producer, has benefited from gold mining as the sector generates about 90% of the country's total exports. Just like all industries, mining is associated with benefits and risks to indigenes and the host environment.