Soils are essential for supporting food production and providing ecosystem services but are
under pressure due to population growth, higher food demand, and land use competition …

Soil is a vital resource for feeding the burgeoning global population, and it is also essential
for realizing most of the 'United Nations Sustainable Development Goals (SDGs)'. For …

Estimation of the soil organic carbon (SOC) content is of utmost importance in understanding
the chemical, physical, and biological functions of the soil. This study proposes machine …

In the digital soil mapping (DSM) framework, machine learning models quantify the
relationship between soil observations and environmental covariates. Generally, the most …

Soil organic carbon (SOC) is an important indicator of soil quality and directly determines
soil fertility. Hence, understanding its spatial distribution and controlling factors is necessary …

The cuurent study was performed to predict spatial distribution of some heavy metals (Ni, Fe,
Cu, Mn) in western Iran, using environmental covariates and applying two machine learning …

Climate change has caused droughts to increase in frequency and severity worldwide,
which has attracted scientists to create drought prediction models to mitigate the impacts of …

This study was designed to evaluate soil quality (SQ) in deforested and intensively cultured
lands in Mazandaran Province, Iran. For this purpose, three soil quality indices (SQIs …

Soil pH and carbonates (CaCO 3) are important indicators of soil chemistry and fertility, and
the prediction of their spatial distribution is critical for the agronomic and environmental …

Understanding the spatial distribution of soil organic carbon (SOC) content over different
climatic regions will enhance our knowledge of carbon gains and losses due to climatic …