Use of hyperspectral imagery to detect affected vegetation and heavy metal polluted areas: a coal mining area, China. Issue 10 (21st July 2022)

• Record Type: Journal Article
• Authors: Yang, Xingchen; Lei, Shaogang; Zhao, Yibo; Cheng, Wei
• Is Part Of: Geocarto international. Volume 37:Issue 10(2022)
• Page Start: 2893
• Page End: 2912
• Publication Date: 2022-07-21
• Subjects: Hyperspectral -- threshold value -- heavy metal -- mining area -- inversion; Remote sensing -- Periodicals; Geographic information systems -- Periodicals; Geology -- Periodicals; Cartography -- Periodicals; 621.3678
• DOI: 10.1080/10106049.2020.1844308
• Languages: English
• ISSNs: 1010-6049

Abstract

Abstract: Some indicators for evaluating heavy metal pollution have been proposed. However, a threshold is lacking to judge if the heavy metal concentration has reached the extent that is harmful to plant health. In order to get the threshold, aerial hyperspectral images were obtained. The spatial patterns of six soil heavy metals (Cu, Zn, As, Sn, Cr and Cd) were obtained by establishing random forest inversion models. The normalized difference vegetation index (NDVI) under different soil heavy metal concentrations was analysed. Cu, Zn, As, Sn and Cr exhibited that low concentrations stimulated plant growth while high concentrations suppressed it. When the concentrations of Cu, Zn, As, Sn and Cr exceeded 19.960 mg/kg, 49.040 mg/kg, 14.049 mg/kg, 0.193 mg/kg and 89.799 mg/kg, respectively, heavy metals began to inhibit the growth of vegetation. The lower reaches of the river and the downwind area of the mining area were easily to exceed the threshold.