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Evaluation of Spatial-Temporal Variation of Vegetation Restoration in Dexing Copper Mine Area Using Remote Sensing Data

机译:利用遥感数据评价德兴铜矿地区植被恢复的空间变化

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Taking the Dexing Copper Mine in Jiangxi Province, China as an study area, we used the long-term sequence summer Landsat images in 2002-2019 to investigate the variation of vegetation growth status and their ecological restoration effects. According to the specific situation of the study area, the Green-Red Normalized Difference Vegetation Index (GRNDVI) calculated from remote sensing data was used to analyse the growth of mine vegetation and the dynamic change in the whole mining area. Moreover, the annual growth changes were compared with normal vegetation growth. The CV method, Hurst method, and Sen+Mann-Kendall method were combined used to evaluate the intensity of vegetation growth, change patterns and change sustainability analysis to obtain the overall growth and change of vegetation and then predict the vegetation growth trend in the study area. The results show that this method can assess accurately the vegetation growth trend in the study area.
机译:以江西省德兴铜矿作为一家学习区,我们在2002 - 2019年使用了长期序列夏季地岸图像,探讨了植被生长状态的变化及其生态恢复效应。根据研究领域的具体情况,采用了从遥感数据计算的绿色归一化差异植被指数(GRNDVI)分析矿山植被的生长和整个矿区的动态变化。此外,与常规植被增长进行了年生长变化。组合CV方法,赫斯特方法和SEN + MANN-KENDALL方法用于评估植被生长,改变模式和变化可持续性分析的强度,以获得植被的整体生长和变化,然后预测研究中的植被增长趋势区域。结果表明,该方法可以准确评估研究区域的植被生长趋势。

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