Geocomputation and geospatial artificial intelligence (GeoAI) have essential roles in
advancing geographic information science (GIS) and Earth observation to a new stage …

Long-term climate change significantly affects the spatiotemporal dynamics of soil erosion.
To explore this, remote sensing technology, future climate scenarios, and deep learning are …

Pressure on land is a consequence of population expansion, increased food consumption,
and competition between land uses. Soils play a crucial role in supporting food production …

Digital soil maps are commonly data-driven as the development of physically-based models
for soil mapping is difficult due to the complexity of soils. However, physically-based …

Digital soil mapping (DSM) based on environmental similarity may be used to predict the soil
properties at unvisited locations based on the soil–environment relationship at each sample …

Digital soil mapping relies on relating soils to a particular set of covariates, which capture
inherent soil spatial variation. In digital mapping of soil classes, the most commonly used …

Digital soil mapping (DSM), which uses machine learning (ML) algorithms and
environmental covariates, is used worldwide for predicting soil properties and classes, due …

Digital soil mapping based on individual sample representativeness Page 1 Digital soil
mapping based on individual sample representativeness Fanghe Zhao Institute of …