[HTML][HTML] Digital mapping of GlobalSoilMap soil properties at a broad scale: A review
Soils are essential for supporting food production and providing ecosystem services but are
under pressure due to population growth, higher food demand, and land use competition …
under pressure due to population growth, higher food demand, and land use competition …
Soil salinity: A global threat to sustainable development
A Singh - Soil Use and Management, 2022 - Wiley Online Library
Soil is a vital resource for feeding the burgeoning global population, and it is also essential
for realizing most of the 'United Nations Sustainable Development Goals (SDGs)'. For …
for realizing most of the 'United Nations Sustainable Development Goals (SDGs)'. For …
[HTML][HTML] Predicting and mapping of soil organic carbon using machine learning algorithms in Northern Iran
Estimation of the soil organic carbon (SOC) content is of utmost importance in understanding
the chemical, physical, and biological functions of the soil. This study proposes machine …
the chemical, physical, and biological functions of the soil. This study proposes machine …
Improving the spatial prediction of soil organic carbon using environmental covariates selection: A comparison of a group of environmental covariates
In the digital soil mapping (DSM) framework, machine learning models quantify the
relationship between soil observations and environmental covariates. Generally, the most …
relationship between soil observations and environmental covariates. Generally, the most …
[HTML][HTML] Using machine learning algorithms to estimate soil organic carbon variability with environmental variables and soil nutrient indicators in an alluvial soil
K John, I Abraham Isong, N Michael Kebonye… - Land, 2020 - mdpi.com
Soil organic carbon (SOC) is an important indicator of soil quality and directly determines
soil fertility. Hence, understanding its spatial distribution and controlling factors is necessary …
soil fertility. Hence, understanding its spatial distribution and controlling factors is necessary …
Predicting heavy metal contents by applying machine learning approaches and environmental covariates in west of Iran
The cuurent study was performed to predict spatial distribution of some heavy metals (Ni, Fe,
Cu, Mn) in western Iran, using environmental covariates and applying two machine learning …
Cu, Mn) in western Iran, using environmental covariates and applying two machine learning …
[HTML][HTML] Forecasting of SPI and meteorological drought based on the artificial neural network and M5P model tree
Climate change has caused droughts to increase in frequency and severity worldwide,
which has attracted scientists to create drought prediction models to mitigate the impacts of …
which has attracted scientists to create drought prediction models to mitigate the impacts of …
Assessing the effects of deforestation and intensive agriculture on the soil quality through digital soil mapping
M Zeraatpisheh, E Bakhshandeh, M Hosseini, SM Alavi - Geoderma, 2020 - Elsevier
This study was designed to evaluate soil quality (SQ) in deforested and intensively cultured
lands in Mazandaran Province, Iran. For this purpose, three soil quality indices (SQIs …
lands in Mazandaran Province, Iran. For this purpose, three soil quality indices (SQIs …
Digital mapping of soil pH and carbonates at the European scale using environmental variables and machine learning
Q Lu, S Tian, L Wei - Science of the Total Environment, 2023 - Elsevier
Soil pH and carbonates (CaCO 3) are important indicators of soil chemistry and fertility, and
the prediction of their spatial distribution is critical for the agronomic and environmental …
the prediction of their spatial distribution is critical for the agronomic and environmental …
[HTML][HTML] Improving the spatial prediction of soil organic carbon content in two contrasting climatic regions by stacking machine learning models and rescanning …
R Taghizadeh-Mehrjardi, K Schmidt… - Remote Sensing, 2020 - mdpi.com
Understanding the spatial distribution of soil organic carbon (SOC) content over different
climatic regions will enhance our knowledge of carbon gains and losses due to climatic …
climatic regions will enhance our knowledge of carbon gains and losses due to climatic …