The remarkable complexity of soil and its importance to a wide range of ecosystem services
presents major challenges to the modeling of soil processes. Although major progress in soil …

Soil scientists are being challenged to provide assessments of soil condition from local
through to global scales. A particular issue is the need for estimates of the stores and fluxes …

80% of arable land in Africa has low soil fertility and suffers from physical soil problems.
Additionally, significant amounts of nutrients are lost every year due to unsustainable soil …

Digital soil map** (DSM) is a successful sub discipline of soil science with an active
research output. The success of digital soil map** is a confluence of several factors in the …

We developed a comprehensive, gridded Global Soil Dataset for use in Earth System
Models (GSDE) and other applications. The GSDE provides soil information, such as soil …

A comprehensive 30× 30 arc‐second resolution gridded soil characteristics data set of
China has been developed for use in the land surface modeling. It includes physical and …

The lack of detailed three-dimensional soil texture information largely restricts many
applications in agriculture, hydrology, climate, ecology and environment. This study …

Core Ideas Ensemble machine learning methods were used to obtain gridded soil property
and class maps. Final predictions were generated for six soil properties and two soil classes …

Estimation of carbon contents and stocks are important for carbon sequestration,
greenhouse gas emissions and national carbon balance inventories. For Denmark, we …

Soil carbon is a key component of functional ecosystems and crucial for food, soil, water and
energy security. Climate change and altered land-use are having a great impact on soils …