Results 1 to 10 of about 289,016 (300)
Digital soil mapping from conventional field soil observations [PDF]
Soil and Water Research, 2013 We tested the performance of a formalized digital soil mapping (DSM) approach comprising fuzzy k-means (FKM) classification and regression-kriging to produce soil type maps from a fine-scale soil observation network in Rišňovce, Slovakia.
Juraj BALKOVIČ +4 more
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Multivariate Random Forest for Digital Soil Mapping
Geoderma, 2022 In digital soil mapping (DSM), soil maps are usually produced in a univariate manner, that is, each soil map is produced independently and therefore, when multiple soil properties are mapped the underlying dependence structure between these soil properties is ignored. This may lead to inconsistent predictions and simulations.
Cornelius Stephanus van der Westhuizen +2 more
semanticscholar +3 more sources
Machine learning for digital soil mapping: applications, challenges and suggested solutions
Earth-Science Reviews, 2020 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 scientists have applied ML to a wide range of scenarios, by mapping soil properties
Alexandre M.J.‐C. Wadoux +2 more
openalex +3 more sources
Assessing Soil Prediction Distributions for Forest Management Using Digital Soil Mapping [PDF]
Soil SystemsTexture, soil organic matter (SOM), and soil depth (SoD) are crucial properties in forest management because they can supply spatial information on forest site productivity and guide fertilizer applications.
Gonzalo Gavilán-Acuña +5 more
openalex +2 more sources
Improving 3D Digital Soil Mapping Based on Spatialized Lab Soil Spectral Information
Remote Sensing, 2023 Readily available environmental covariates in current digital soil mapping usually do not indicate the spatial differences between deep soil attributes.
Zheng Sun +4 more
doaj +2 more sources
A review on digital mapping of soil carbon in cropland: progress, challenge, and prospect [PDF]
Environmental Research Letters, 2022 Cropland soil carbon not only serves food security but also contributes to the stability of the terrestrial ecosystem carbon pool due to the strong interconnection with atmospheric carbon dioxide.
Haili Huang +8 more
doaj +2 more sources
Including soil spatial neighbor information for digital soil mapping
GeodermaDigital soil mapping (DSM) is transforming how we understand and manage soil resources, offering high-resolution spatial–temporal soil information essential for addressing environmental challenges. The integration of environmental covariates has advanced
Zhongxing Chen +4 more
doaj +2 more sources
Game theory interpretation of digital soil mapping convolutional neural networks [PDF]
SOIL, 2020 The use of complex models such as deep neural networks has yielded large improvements in predictive tasks in many fields including digital soil mapping.
J. Padarian, A. B. McBratney, B. Minasny
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Open Remote Sensing Data in Digital Soil Organic Carbon Mapping: A Review
AgricultureThis review focuses on digital soil organic carbon (SOC) mapping at regional or national scales in spatial resolutions up to 1 km using open data remote sensing sources, emphasizing its importance in achieving United Nations’ Sustainable Development ...
Dorijan Radočaj +2 more
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GeodermaThis study presents a regional digital soil mapping (DSM) product that used a locally enhanced method in support of a bottom-up approach to create spatial soil predictions that were more accurate than one of the most accurate and detailed conventional ...
Meyer P. Bohn, Bradley A. Miller
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