Results 61 to 70 of about 897 (206)
Present global maps of soil water retention (SWR) are mostly derived from pedotransfer functions (PTFs) applied to maps of other basic soil properties.
Maria Eliza Turek +6 more
doaj +1 more source
The application of GIS based decision-tree models for generating the spatial distribution of hydromorphic organic landscapes in relation to digital terrain data [PDF]
Accurate information about organic/mineral soil occurrence is a prerequisite for many land resources management applications (including climate change mitigation).
M. B. Greve +3 more
core +2 more sources
A Note on Spurious Correlations and Explainable Machine Learning in Digital Soil Mapping
ABSTRACT The use of machine learning as a method for knowledge discovery is often critically discussed in soil science and related environmental disciplines. Reviews of the use of machine learning in digital soil mapping identified few studies that incorporated existing soil knowledge of transformation and translocation processes in soils and ...
Tobias Rentschler, Thomas Scholten
wiley +1 more source
Soil legacy data: An opportunity for digital soil mapping [PDF]
Soil legacy data is past information on soils available from various sources (e.g. survey reports and maps). When compiled and organized, data obtained through historical retrieval can be used as basic input or validation data for digital soil mapping. A
Beatriz Macêdo Medeiros +5 more
doaj +1 more source
Environmental Information: Placing Biodiversity Phenomena in an Ecological and Environmental Context [PDF]
Environmental models are increasingly being used as surrogates to determine plant and animal species’ distributions for a range of uses. This use of models has become an important part of the recent science that has become known as biodiversity ...
Chapman, Arthur D +2 more
core +4 more sources
Artificial intelligence in soil science
ABSTRACT Few would disagree that artificial intelligence (AI) holds potential for advancing knowledge and innovation. Over the past decades, substantial research has been devoted to the development and application of AI in soil science. While most of today's AI applications in soil science are related to machine learning (ML), AI also encompasses other
Alexandre M. J.‐C. Wadoux
wiley +1 more source
Abstract The increasing global demand for sustainable agriculture requires accurate and efficient soil analysis methods. Conventional laboratory techniques are often time‐consuming, costly and environmentally damaging. To address this challenge, we developed and validated locally calibrated mid‐infrared (MIR) spectroscopy models for predicting key soil
Anru‐Louis Kock +2 more
wiley +1 more source
Understanding soil variability supports improved land use and soil security. This study aimed to generate uniform geophysical classes by integrating data from three proximal geophysical sensors with synthetic soil and satellite images using machine ...
Gustavo Vieira Veloso +13 more
doaj +1 more source
Abstract The soil supports many ecosystem services (ES) essential to human well‐being. Rapid developments in digital soil mapping (DSM) allow the mapping of soil types and soil properties with improved resolution and accuracy. However, the potential of DSM to improve the assessment and mapping of ES is not fully exploited.
David Paré +9 more
wiley +1 more source
History of Soil Geography in the Context of Scale [PDF]
We review historical soil maps from a geographical perspective, in contrast to the more traditional temporal–historical perspective. Our geographical approach examines and compares soil maps based on their scale and classification system.
Miller, Bradley +2 more
core +2 more sources

