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 …

The uptake of machine learning (ML) algorithms in digital soil mapping (DSM) is
transforming the way soil scientists produce their maps. Within the past two decades, soil …

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

Abstract Machine-learning is the automated process of uncovering patterns in large datasets
using computer-based statistical models, where a fitted model may then be used for …

Abstract The Land Use and Cover Area frame Statistical survey (LUCAS) aimed at the
collecting harmonised data about the state of land use/cover over the extent of European …

Pedology focuses on understanding soil genesis in the field and includes soil classification
and mapping. Digital soil mapping (DSM) has evolved from traditional soil classification and …

A new complete map of soil series probabilities has been produced for the contiguous
United States at a 30 m spatial resolution. This innovative database, named POLARIS, is …

To deal with the global and regional issues including food security, climate change, land
degradation, biodiversity loss, water resource management, and ecosystem health, detailed …

Agriculture is essential to a flourishing economy. Although soil is essential for sustainable
food production, its quality can decline as cultivation becomes more intensive and demand …

The Soil and Landscape Grid of Australia (SLGA) is the first continental version of the
GlobalSoilMap concept and the first nationally consistent, fine spatial resolution set of …