Digital soil map** algorithms and covariates for soil organic carbon map** and their implications: A review
This article reviews the current research and applications of various digital soil map**
(DSM) techniques used to map Soil Organic Carbon (SOC) concentration and stocks …
(DSM) techniques used to map Soil Organic Carbon (SOC) concentration and stocks …
A map of the topsoil organic carbon content of Europe generated by a generalized additive model
D de Brogniez, C Ballabio, A Stevens… - European Journal of …, 2015 - Wiley Online Library
There is an increasing demand for up‐to‐date soil organic carbon (OC) data for global
environmental and climatic modelling. The aim of this study was to create a map of topsoil …
environmental and climatic modelling. The aim of this study was to create a map of topsoil …
[HTML][HTML] SoilGrids 2.0: producing soil information for the globe with quantified spatial uncertainty
SoilGrids produces maps of soil properties for the entire globe at medium spatial resolution
(250 m cell size) using state-of-the-art machine learning methods to generate the necessary …
(250 m cell size) using state-of-the-art machine learning methods to generate the necessary …
[HTML][HTML] Map** 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 …
[PDF][PDF] Global soil carbon: understanding and managing the largest terrestrial carbon pool
JPW Scharlemann, EVJ Tanner, R Hiederer… - Carbon …, 2014 - researchgate.net
Carbon stored in soils worldwide exceeds the amount of carbon stored in phytomass and
the atmosphere. Despite the large quantity of carbon stored as soil organic carbon (SOC) …
the atmosphere. Despite the large quantity of carbon stored as soil organic carbon (SOC) …
Machine learning for predicting soil classes in three semi-arid landscapes
Map** the spatial distribution of soil taxonomic classes is important for informing soil use
and management decisions. Digital soil map** (DSM) can quantitatively predict the spatial …
and management decisions. Digital soil map** (DSM) can quantitatively predict the spatial …
An advanced soil organic carbon content prediction model via fused temporal-spatial-spectral (TSS) information based on machine learning and deep learning …
X Meng, Y Bao, Y Wang, X Zhang, H Liu - Remote Sensing of Environment, 2022 - Elsevier
Abstract Knowledge of the soil organic carbon (SOC) content is critical for environmental
sustainability and carbon neutrality. With the development of remote sensing data and …
sustainability and carbon neutrality. With the development of remote sensing data and …
Monitoring changes in global soil organic carbon stocks from space
Soils are under threat globally, with declining soil productivity and soil health in many
places. As a key indicator of soil functioning, soil organic carbon (SOC) is crucial for …
places. As a key indicator of soil functioning, soil organic carbon (SOC) is crucial for …
Evaluation of digital soil map** approaches with large sets of environmental covariates
The spatial assessment of soil functions requires maps of basic soil properties.
Unfortunately, these are either missing for many regions or are not available at the desired …
Unfortunately, these are either missing for many regions or are not available at the desired …
Soil map**, classification, and pedologic modeling: History and future directions
Soil map**, classification, and pedologic modeling have been important drivers in the
advancement of our understanding of soil from the earliest days of the scientific study of …
advancement of our understanding of soil from the earliest days of the scientific study of …