The history of digital soil mapping and modeling (DSMM) is marked by adoption of new
mapping tools and techniques, data management systems, innovative delivery of soil data …

Heavy metal pollution in urban soil is one of the global environmental problems, and
monitoring its spatial distribution can provide basic data for assessing and managing the …

Mapping the spatial distribution of soil taxonomic classes is important for informing soil use
and management decisions. Digital soil mapping (DSM) can quantitatively predict the spatial …

The globally important nature of wetland ecosystems has led to their increased protection
and restoration as well as their use in engineered systems. Underpinning the beneficial …

Soil texture which is spatially variable in nature, is an important soil physical property that
governs most physical, chemical, biological, and hydrological processes in soils. Detailed …

The swift rise of omics-approaches allows for investigating microbial diversity and plant-
microbe interactions across diverse ecological communities and spatio-temporal scales. The …

The use of Markov chain Monte Carlo (MCMC) methods for estimating hierarchical models
involves complex data structures and is often described as a revolutionary development. An …

This paper aims to investigate the potential of using soil-landscape pattern extracted from a
soil map to predict soil distribution at unvisited location. Recent machine learning advances …

An intermediate-level treatment of Bayesian hierarchical models and their applications, this
book demonstrates the advantages of a Bayesian approach to data sets involving inferences …

Soil mapping in Denmark has a long history and a series of soil maps based on
conventional mapping approaches have been produced. In this study, a national soil map of …