VIRS based detection in combination with machine learning for mapping soil pollution

X Jia, D O'Connor, Z Shi, D Hou - Environmental Pollution, 2021 - Elsevier
Widespread soil contamination threatens living standards and weakens global efforts
towards the Sustainable Development Goals (SDGs). Detailed soil mapping is needed to …

Estimation of heavy metals using deep neural network with visible and infrared spectroscopy of soil

JC Pyo, SM Hong, YS Kwon, MS Kim… - Science of the Total …, 2020 - Elsevier
Heavy metal contamination in soil disturbs the chemical, biological, and physical soil
conditions and adversely affects the health of living organisms. Visible and near-infrared …

Trend analysis of global usage of digital soil mapping models in the prediction of potentially toxic elements in soil/sediments: a bibliometric review

PC Agyeman, SK Ahado, L Borůvka, JKM Biney… - Environmental …, 2021 - Springer
The rising and continuous pollution of the soil from anthropogenic activities is of great
concern. Owing to this concern, the advent of digital soil mapping (DSM) has been a tool that …

Mapping soil arsenic pollution at a brownfield site using satellite hyperspectral imagery and machine learning

X Jia, D Hou - Science of The Total Environment, 2023 - Elsevier
Heavy metal contamination is ubiquitous in brownfields. Traditional site investigation
employs geostatistical interpolation methods (GIMs) to predict the distribution of soil …

Possibility of optimized indices for the assessment of heavy metal contents in soil around an open pit coal mine area

R Sawut, N Kasim, A Abliz, L Hu, A Yalkun… - International journal of …, 2018 - Elsevier
Possibility of optimized indices for the assessment of heavy metal contents in soil around an
open pit coal mine area - ScienceDirect Skip to main contentSkip to article Elsevier logo …

A transferable spectroscopic diagnosis model for predicting arsenic contamination in soil

C Tao, Y Wang, W Cui, B Zou, Z Zou, Y Tu - Science of the Total …, 2019 - Elsevier
Visible and near-infrared reflectance (VNIR) spectroscopy is considered to be a potential
and efficient means for monitoring soil arsenic (As) contamination. While current studies …

Regional scale soil moisture content estimation based on multi-source remote sensing parameters

M Ainiwaer, J Ding, N Kasim, J Wang… - International Journal of …, 2020 - Taylor & Francis
Soil moisture content (SMC) is a basic condition for crop growth, and a key parameter for
crop yield prediction and drought monitoring. An advantage of large-scale synchronous …

Near infrared spectroscopy as a tool to monitor contaminants in soil, sediments and water—State of the art, advantages and pitfalls

D Cozzolino - Trends in Environmental Analytical Chemistry, 2016 - Elsevier
Public awareness related with environmental issues (eg soil and water contamination) is on
the increase, determining the advent of more astringent safety standards where new …

A new three-band spectral and metal element index for estimating soil arsenic content around the mining area

P Fu, K Yang, F Meng, W Zhang, Y Cui, F Feng… - Process Safety and …, 2022 - Elsevier
Owing to the advantages of fast and non-destructive measurement, visible and near-infrared
reflectance (VNIR) spectra have been widely used in the study of heavy metal pollution …

Field hyperspectral data and OLI8 multispectral imagery for heavy metal content prediction and mapping around an abandoned Pb–Zn mining site in northern Tunisia

N Mezned, F Alayet, B Dkhala, S Abdeljaouad - Heliyon, 2022 - cell.com
Mining and smelting releases toxic contaminants such as zinc (Zn), lead (Pb) or cadmium
(Cd) into the soil thereby poisoning it and rendering it unproductive. Remotely alternatives …