This review focuses on digital soil organic carbon (SOC) mapping at regional or national
scales in spatial resolutions up to 1 km using open data remote sensing sources …

The remarkable adaptability and rapid proliferation of Prosopis juliflora have led to its
invasive status in the rangelands of Kenya, detrimentally impacting native vegetation and …

Accurate geospatial prediction of soil parameters provides a basis for large-scale digital soil
mapping, making efficient use of the expensive and time-consuming process of field soil …

This study presents a regional digital soil mapping (DSM) product that used a locally
enhanced method in support of a bottom-up approach to create spatial soil predictions that …

This study employed an ensemble machine learning approach to evaluate the effect of
bioclimatic covariates on the prediction accuracy of soil total carbon (TC) in the Pannonian …

Inclusion of edaphic conditions in biogeographical studies typically provides a better fit and
deeper understanding of plant distributions. Increased reliance on soil data calls for easily …

Soil information is critical for a wide range of land resource and environmental decisions.
These decisions will be compromised when the soil information quality is unsatisfactory …

Agricultural soil maps (ASMs) showing the agricultural land of Poland were prepared at a 1:
5000 scale in the 1960s and 1970s. These maps show land suitability groups, soil type, and …

Platycodon grandiflorus has long been used for its medicinal, culinary and ornamental
properties. With increasing market demand and the depletion of wild resources …

Soil categorical data is an important aspect in soil science because it effectively facilitates
communication between policymakers and stakeholders. Furthermore, soil categorical data …