Digital map** to extrapolate the selected soil fertility attributes in calcareous soils of a semiarid region in Iran
P Khosravani, M Baghernejad, AA Moosavi… - Journal of Soils and …, 2023 - Springer
Purpose Spatial variability of soil properties is considered as one of the most important
reasons for the variability of crop productions. The current research was conducted to …
reasons for the variability of crop productions. The current research was conducted to …
Digital map** of soil properties using ensemble machine learning approaches in an agricultural lowland area of Lombardy, Italy
Sustainable agricultural landscape management needs reliable and accurate soil maps and
updated geospatial soil information. Recently, machine learning (ML) models have …
updated geospatial soil information. Recently, machine learning (ML) models have …
Incorporating forest canopy openness and environmental covariates in predicting soil organic carbon in oak forest
The historical conversion of forests to rainfed agricultural lands in the semi-arid forest
ecosystems is one of the primary sources of human-induced, greenhouse gas emission and …
ecosystems is one of the primary sources of human-induced, greenhouse gas emission and …
Co** with imbalanced data problem in digital map** of soil classes
An unsolved problem in the digital map** of categorical soil variables and soil types is the
imbalanced number of observations, which leads to reduced accuracy and the loss of the …
imbalanced number of observations, which leads to reduced accuracy and the loss of the …
Combining spatial autocorrelation with artificial intelligence models to estimate spatial distribution and risks of heavy metal pollution in agricultural soils
Abstract Information on spatial distribution and potential sources of heavy metals in
agricultural lands is very important for human health and food safety. In this study, pollution …
agricultural lands is very important for human health and food safety. In this study, pollution …
Impact of Land Cover Changes on Soil Type Map** in Plain Areas: Evidence from Tongzhou District of Bei**g, China
X Wu, K Wu, H Zhao, S Hao, Z Zhou - Land, 2023 - mdpi.com
The flat terrain in the plain areas of Bei**g, China makes the land easily accessible for
cultivation and farming, providing vast opportunities for agricultural development …
cultivation and farming, providing vast opportunities for agricultural development …
[HTML][HTML] A framework for optimizing environmental covariates to support model interpretability in digital soil map**
B Kasraei, MG Schmidt, J Zhang, CE Bulmer… - Geoderma, 2024 - Elsevier
A common practice in digital soil map** (DSM) is to incorporate many environmental
covariates into a machine-learning algorithm to predict the spatial patterns of soil attributes …
covariates into a machine-learning algorithm to predict the spatial patterns of soil attributes …
Map** Soil Organic Carbon Stock and Uncertainties in an Alpine Valley (Northern Italy) Using Machine Learning Models
S Agaba, C Ferré, M Musetti, R Comolli - Land, 2024 - mdpi.com
In this study, we conducted a comprehensive analysis of the spatial distribution of soil
organic carbon stock (SOC stock) and the associated uncertainties in two soil layers (0–10 …
organic carbon stock (SOC stock) and the associated uncertainties in two soil layers (0–10 …
Accuracy Assessment of Kriging, artificial neural network, and a hybrid approach integrating spatial and terrain data in estimating and map** of soil organic carbon
This study aimed to produce a soil organic carbon (SOC) content map with high accuracy
and spatial resolution using the most effective factors in the model. The spatial SOC …
and spatial resolution using the most effective factors in the model. The spatial SOC …
[HTML][HTML] Filling the gaps in soil data: A multi-model framework for addressing data gaps using pedotransfer functions and machine-learning with uncertainty estimates …
M Schmidt, J Zhang, C Bulmer, D Filatow, B Kasraei… - Catena, 2024 - Elsevier
Legacy soil datasets are a valuable resource and should be used to the greatest extent
possible. However, such datasets may be incomplete, and lack observations for every …
possible. However, such datasets may be incomplete, and lack observations for every …