[HTML][HTML] Rapid estimation of soil Mn content by machine learning and soil spectra in large-scale

M Zhou, T Hu, M Wu, C Ma, C Qi - Ecological Informatics, 2024 - Elsevier
Manganese (Mn) is an essential element in both plants and the human body; however,
traditional methods for monitoring Mn in soil are costly and inefficient. As such, it is …

The effect of covariates on Soil Organic Matter and pH variability: A digital soil mapping approach using random forest model

Y Bouslihim, K John, A Miftah, R Azmi, R Aboutayeb… - Annals of …, 2024 - Taylor & Francis
This research focuses on understanding the spatial variation of Soil Organic Matter (SOM)
and pH levels in the North of Morocco. The study employs a comprehensive approach to …

[HTML][HTML] Global soil respiration predictions with associated uncertainties from different spatio-temporal data subsets

J Jiang, L Feng, J Hu, H Liu, C Zhu, B Chen… - Ecological Informatics, 2024 - Elsevier
Soil respiration (Rs), the second-largest flux in the global carbon cycle, is a crucial but
uncertain component. To improve the understanding of global Rs, we constructed single …

Tree-level biomass estimation using unmanned aerial vehicle (UAV) imagery and allometric equation

X Jia, C Wang, Y Da, X Tian, W Ge - Biomass and Bioenergy, 2024 - Elsevier
Estimating forest biomass is imperative for comprehensively understanding the function of
forest in regulating climate, providing theoretical support for vegetation management …

Improving prediction of groundwater quality in situations of limited monitoring data based on virtual sample generation and Gaussian process regression

J Zhang, C Xiao, W Yang, X Liang, L Zhang, X Wang… - Water Research, 2024 - Elsevier
The increasing pollution of aquifers by human activities over recent decades poses a threat
to drinking water safety. While Gaussian Process Regression (GPR) is a robust tool for …

Comparative analysis of nonlinear impacts on the built environment within station areas with different metro ridership segments

J Peng, X Fu, C Wu, Q Dai, H Yang - Travel Behaviour and Society, 2025 - Elsevier
A plethora of studies have investigated the nonlinear correlation between the built
environment and metro ridership. However, the spatiotemporal heterogeneity of this …

Machine Learning Approach to Biomass Estimation: Integrating Satellite and Ground Data in Sal Forests of Jharkhand

K Anandita, AK Sinha, C Jeganathan - Journal of the Indian Society of …, 2024 - Springer
Abstract Accurately estimating Above Ground Biomass (AGB) is crucial for understanding
forest carbon dynamics and improving ecological monitoring. This study refines AGB …

Sample Size Optimization for Digital Soil Mapping: An Empirical Example

DD Saurette, RJ Heck, AW Gillespie, AA Berg… - Land, 2024 - mdpi.com
In the evolving field of digital soil mapping (DSM), the determination of sample size remains
a pivotal challenge, particularly for large-scale regional projects. We introduced the Jensen …

[HTML][HTML] A novel model for mapping soil organic matter: Integrating temporal and spatial characteristics

X Zhang, G Zhang, S Zhang, H Ai, Y Han, C Luo… - Ecological …, 2024 - Elsevier
Mapping the spatial distribution of soil organic matter (SOM) content is crucial for land
management decisions, yet its accurate mapping faces challenges due to complex soil …

[HTML][HTML] Digital mapping of soil salinity with time-windows features optimization and ensemble learning model

S Shi, N Wang, S Chen, B Hu, J Peng, Z Shi - Ecological Informatics, 2024 - Elsevier
Soil salinization poses considerable global environmental and ecological risks. Remote-
sensing time-series data enable more accurate monitoring and prediction of soil salinity …