Air pollution exposure assessment in sparsely monitored settings; applying machine-learning methods with remote sensing data in South Africa.

Ensemble averaging using remote sensing data to model spatiotemporal PM10 concentrations in sparsely monitored South Africa

Unsupervised machine learning in air pollution epidemiology in South Africa

This dataset consist of different scripts and do files, used to achieve objectives to assess the

Application of Machine Learning and Remote Sensing for Gap-filling Daily Precipitation Data of a Sparsely Gauged Basin in East Africa

Abstract Access to spatiotemporal distribution of precipitation is needed in many hydrological appl

Fatala River Basin (Republic of Guinea, Africa): Analysis of Current State, Air Pollution, and Anthropogenic Impact Using Geoinformatics Methods and Remote Sensing Data

This study conducts an in-depth analysis of anthropogenic transformation and air pollution within th

Reducing Air Pollution through Machine Learning

This paper presents a data-driven approach to mitigate the effects of air pollution from industrial

Cardiovascular Benefits of Reducing Household Air Pollution and Machine Learning-Based Approaches to Vascular Health Assessment in Low Resource Rural Settings

Cardiovascular disease (CVD) is the leading cause of premature morbidity and mortality worldwide, di