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不同干扰条件下稀土矿区土地沙漠化的时空变化。

Spatiotemporal changes in desertified land in rare earth mining areas under different disturbance conditions.

机构信息

School of Civil and Surveying & Mapping Engineering, Jiangxi University of Science and Technology, No.86 Hongqi Road, Ganzhou, 341000, Jiangxi, China.

出版信息

Environ Sci Pollut Res Int. 2021 Jun;28(23):30323-30334. doi: 10.1007/s11356-021-12476-x. Epub 2021 Feb 15.

Abstract

Special mining methods and red soil lead to large-scale land degradation and desertification in ion-type rare earth (RE) mining areas. Therefore, it is crucial for ecological management and restoration of mining areas to accurately understand the evolution process of desertification. In this study, remote sensing Landsat images from 1986 to 2019 were used to extract desertified land information from the Lingbei mining areas, Dingnan County, Ganzhou, China. To improve the reliability of the experiment, samples selected from Google images were used for verification to compare the accuracy of the desertification difference index (DDI) model and random forest (RF) algorithm for extracting land desertification information. The results showed that compared with the DDI model, the overall accuracy and kappa coefficient of the RF model based on multiple features were improved by 7% and 9.37%, respectively, indicating its higher applicability. Spatiotemporal change analysis of desertification in the mining area showed that the total area of desertification in the mining area increased most rapidly during 1986-1994 and reached 60.75 km. The area of desertified land increased continuously from 1994 to 2004 and reached a maximum of 143.08 km in 2004. The area of desertified land decreased by 50.27 km, but the severe desertified land (SDL) area increased by 1.69 km during 2004-2011. The area of desertified land gradually declined and stabilized from 2011 to 2019. Analysis of the desertification process in mining areas under different disturbance conditions showed that the desertified land disturbed by RE mining was most severely damaged. There is still an area of 16.77 km in the process of restoration, of which 2.24 km belongs to the SDL level. Moderate desertified land (MDL) and light desertified land (LDL) have not been completely contained and require the attention of the relevant departments to ensure their timely reclamation.

摘要

特殊采矿方法和红壤导致离子型稀土(RE)矿区大规模土地退化和沙漠化。因此,准确了解沙漠化的演变过程对于矿区的生态管理和恢复至关重要。本研究利用中国赣州定南县岭背矿区 1986 年至 2019 年的遥感 Landsat 图像,提取矿区沙漠化土地信息。为了提高实验的可靠性,从 Google 图像中选择样本进行验证,比较沙漠化差值指数(DDI)模型和随机森林(RF)算法提取土地沙漠化信息的精度。结果表明,与 DDI 模型相比,基于多特征的 RF 模型的总体精度和kappa 系数分别提高了 7%和 9.37%,表明其适用性更高。矿区沙漠化时空变化分析表明,矿区沙漠化总面积在 1986-1994 年增长最快,达到 60.75km。1994 年至 2004 年,荒漠化土地面积不断增加,2004 年达到最大值 143.08km。2004-2011 年,荒漠化土地面积减少了 50.27km,但严重荒漠化土地(SDL)面积增加了 1.69km。2011 年至 2019 年,矿区荒漠化土地逐渐减少并趋于稳定。不同干扰条件下矿区沙漠化过程分析表明,受 RE 开采干扰的荒漠化土地受损最为严重。仍有 16.77km 的土地处于恢复过程中,其中 2.24km 属于 SDL 水平。中重度荒漠化(MDL)和轻度荒漠化(LDL)尚未完全得到遏制,需要相关部门的关注,以确保及时复垦。

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