Monitoring Heavy Metals and Metalloids in Soils and Vegetation by Remote Sensing: A Review

被引:1
|
作者
Lovynska, Viktoriia [1 ,2 ]
Bayat, Bagher [1 ]
Bol, Roland [1 ]
Moradi, Shirin [1 ]
Rahmati, Mehdi [1 ]
Raj, Rahul [1 ]
Sytnyk, Svitlana [2 ,3 ]
Wiche, Oliver [4 ]
Wu, Bei [1 ]
Montzka, Carsten [1 ]
机构
[1] Forschungszentrum Julich, Inst Bioand Geosci Agrosphere IBG 3, D-52425 Julich, Germany
[2] Dnipro State Agrarian & Econ Univ, Lab Forestry, UA-49009 Dnipro, Ukraine
[3] Bielefeld Univ, Chem Ecol Grp, D-33615 Bielefeld, Germany
[4] Zittau Gorlitz Univ Appl Sci, Fac Nat & Environm Sci, Appl Geoecol Grp, D-02763 Zittau, Germany
关键词
heavy metal; metalloids; pollution; remote sensing; INFRARED REFLECTANCE SPECTROSCOPY; COMBINED GEOCHEMISTRY; FIELD SPECTROSCOPY; REGIONAL-SCALE; MINING AREA; STRESS; CONTAMINATION; PREDICTION; POLLUTION; RICE;
D O I
10.3390/rs16173221
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Heavy metal contamination in soils and vegetation poses a significant problem due to its toxicity and persistence. Toxic effects on vegetation include not only impaired growth, reduced yields, and even plant death but also biodiversity loss and ecosystem degradation. Addressing this issue requires comprehensive monitoring and remediation efforts to mitigate the environmental, human health, and ecological impacts. This review examines the state-of-the-art methodologies and advancements in remote sensing applications for detecting and monitoring heavy metal contamination in soil and its subsequent effects on vegetation. By synthesizing the current research findings and technological developments, this review offers insights into the efficacy and potential of remote sensing for monitoring heavy metal contamination in terrestrial ecosystems. However, current studies focus on regression and AI methods to link spectral reflectances and indices to heavy metal concentrations, which poses limited transferability to other areas, times, spectral discretizations, and heavy metal elements. We conclude that one important way forward is the more thorough understanding and simulation of the related physico-chemical processes in soils and plants and their effects on the spectral signatures. This would offer a profound basis for remote sensing applications for individual circumstances and would allow disentangling heavy metal effects from other stressors such as droughts or soil salinity.
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页数:30
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