Digital soil mapping algorithms and covariates for soil organic carbon mapping and their implications: A review
This article reviews the current research and applications of various digital soil mapping
(DSM) techniques used to map Soil Organic Carbon (SOC) concentration and stocks …
(DSM) techniques used to map Soil Organic Carbon (SOC) concentration and stocks …
Agricultural land suitability analysis: State-of-the-art and outlooks for integration of climate change analysis
Agricultural land suitability analysis (ALSA) for crop production is one of the key tools for
ensuring sustainable agriculture and for attaining the current global food security goal in line …
ensuring sustainable agriculture and for attaining the current global food security goal in line …
Global predictions of primary soil salinization under changing climate in the 21st century
Soil salinization has become one of the major environmental and socioeconomic issues
globally and this is expected to be exacerbated further with projected climatic change …
globally and this is expected to be exacerbated further with projected climatic change …
[HTML][HTML] Mapping high resolution national soil information grids of China
Soil spatial information has traditionally been presented as polygon maps at coarse scales.
Solving global and local issues, including food security, water regulation, land degradation …
Solving global and local issues, including food security, water regulation, land degradation …
An unexpectedly large count of trees in the West African Sahara and Sahel
A large proportion of dryland trees and shrubs (hereafter referred to collectively as trees)
grow in isolation, without canopy closure. These non-forest trees have a crucial role in …
grow in isolation, without canopy closure. These non-forest trees have a crucial role in …
Predicting long-term dynamics of soil salinity and sodicity on a global scale
A Hassani, A Azapagic… - Proceedings of the …, 2020 - National Acad Sciences
Knowledge of spatiotemporal distribution and likelihood of (re) occurrence of salt-affected
soils is crucial to our understanding of land degradation and for planning effective …
soils is crucial to our understanding of land degradation and for planning effective …
[HTML][HTML] Random forest as a generic framework for predictive modeling of spatial and spatio-temporal variables
Random forest and similar Machine Learning techniques are already used to generate
spatial predictions, but spatial location of points (geography) is often ignored in the modeling …
spatial predictions, but spatial location of points (geography) is often ignored in the modeling …
Selecting appropriate machine learning methods for digital soil mapping
Y Khaledian, BA Miller - Applied Mathematical Modelling, 2020 - Elsevier
Digital soil mapping (DSM) increasingly makes use of machine learning algorithms to
identify relationships between soil properties and multiple covariates that can be detected …
identify relationships between soil properties and multiple covariates that can be detected …
Modelling and mapping soil organic carbon stocks in Brazil
Brazil has extensive forests and savannas on deep weathered soils and plays a key role in
the discussions about carbon sequestration, but the distribution of soil organic carbon (SOC) …
the discussions about carbon sequestration, but the distribution of soil organic carbon (SOC) …
SoilGrids250m: Global gridded soil information based on machine learning
This paper describes the technical development and accuracy assessment of the most
recent and improved version of the SoilGrids system at 250m resolution (June 2016 update) …
recent and improved version of the SoilGrids system at 250m resolution (June 2016 update) …