Predicting soil chemical properties such as soil organic carbon (SOC) and available
phosphorus (Ava-P) content is critical in areas where different land uses exist. The …

Soil texture classes (STCs) influence the physical, chemical and biological properties of the
soil, and accurate spatial predictions of STCs are essential for agro-ecological modeling …

An accurate and fine map of soil organic carbon (SOC) plays a vital role in understanding
the global carbon cycle and achieving soil carbon sequestration potential. Although global …

Satellite-based soil organic carbon content (SOC) mapping over wide regions is generally
hampered by the low soil sampling density and the diversity of soil sampling periods. Some …

In the last two decades, machine learning (ML) methods have been widely used in digital
soil mapping (DSM), but the regression kriging (RK) model which combines the advantages …

Water and nutrient holding capacities are primarily controlled by the secondary soil
parameters of water retention characteristics and cation exchange capacities (CEC) …

Soil pH is one of the critical indicators of soil quality. A fine resolution map of soil pH is
urgently required to address practical issues of agricultural production, environmental …

This research focuses on understanding the spatial variation of Soil Organic Matter (SOM)
and pH levels in the North of Morocco. The study employs a comprehensive approach to …

In digital soil mapping, machine learning models have been widely applied. However, the
accuracy of machine learning models can be limited by the use of a single model and a …

Cropland soil organic matter (SOM) is recognized as a significant carbon reservoir in
terrestrial ecosystems. Digital mapping of SOM in croplands is essential for comprehending …