This article reviews the current research and applications of various digital soil map**
(DSM) techniques used to map Soil Organic Carbon (SOC) concentration and stocks …

Agricultural land suitability analysis (ALSA) for crop production is one of the key tools for
ensuring sustainable agriculture and for attaining the current global food security goal in line …

Soil salinization has become one of the major environmental and socioeconomic issues
globally and this is expected to be exacerbated further with projected climatic change …

Soil spatial information has traditionally been presented as polygon maps at coarse scales.
Solving global and local issues, including food security, water regulation, land degradation …

A large proportion of dryland trees and shrubs (hereafter referred to collectively as trees)
grow in isolation, without canopy closure. These non-forest trees have a crucial role in …

Knowledge of spatiotemporal distribution and likelihood of (re) occurrence of salt-affected
soils is crucial to our understanding of land degradation and for planning effective …

Random forest and similar Machine Learning techniques are already used to generate
spatial predictions, but spatial location of points (geography) is often ignored in the modeling …

Digital soil map** (DSM) increasingly makes use of machine learning algorithms to
identify relationships between soil properties and multiple covariates that can be detected …

Brazil has extensive forests and savannas on deep weathered soils and plays a key role in
the discussions about carbon sequestration, but the distribution of soil organic carbon (SOC) …

This paper describes the technical development and accuracy assessment of the most
recent and improved version of the SoilGrids system at 250m resolution (June 2016 update) …