A hierarchical residual correction-based hyperspectral inversion method for soil heavy metals considering spatial heterogeneity-Reference-Cited by-同舟云学术

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A hierarchical residual correction-based hyperspectral inversion method for soil heavy metals considering spatial heterogeneity

Published:2024-11 Issue: Volume:479 Page:135699
ISSN:0304-3894
Container-title:Journal of Hazardous Materials
language:en
Short-container-title:Journal of Hazardous Materials

Author:

Wang Yulong,Zou Bin,Li Sha,Tian Rongcai,Zhang Bo,Feng Huihui,Tang Yuqi

Funder

Fundamental Research Funds for Central Universities of the Central South University

Publisher

Elsevier BV

Reference64 articles.

1. Regional and global hotspots of arsenic contamination of topsoil identified by deep learning;Wu;Commun Earth Environ,2024

2. Spatial distribution prediction of soil As in a large-scale arsenic slag contaminated site based on an integrated model and multi-source environmental data;Liu;Environ Pollut,2020

3. Data fusion for the measurement of potentially toxic elements in soil using portable spectrometers;Xu;Environ Pollut,2020

4. Hyperspectral sensing of heavy metals in soil and vegetation: Feasibility and challenges;Wang;ISPRS J Photogramm Remote Sens,2018

5. Monitoring of soil heavy metals based on hyperspectral remote sensing: A review;Wang;Earth-Sci Rev,2024

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