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Volume 42 Issue 5
May  2024
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Article Contents
ZHONG Anya, BAO Cheng, HU Chunming. SPATIOTEMPORAL DYNAMIC CHANGE MONITORING OF NDVI IN MINING AREAS OF DEXING FROM THE PERSPECTIVE OF ECOLOGICAL RESTORATION[J]. ENVIRONMENTAL ENGINEERING , 2024, 42(5): 122-130. doi: 10.13205/j.hjgc.202405016
Citation: ZHONG Anya, BAO Cheng, HU Chunming. SPATIOTEMPORAL DYNAMIC CHANGE MONITORING OF NDVI IN MINING AREAS OF DEXING FROM THE PERSPECTIVE OF ECOLOGICAL RESTORATION[J]. ENVIRONMENTAL ENGINEERING , 2024, 42(5): 122-130. doi: 10.13205/j.hjgc.202405016

SPATIOTEMPORAL DYNAMIC CHANGE MONITORING OF NDVI IN MINING AREAS OF DEXING FROM THE PERSPECTIVE OF ECOLOGICAL RESTORATION

doi: 10.13205/j.hjgc.202405016
  • Received Date: 2023-08-09
    Available Online: 2024-07-11
  • The monitoring of the dynamic change of regional vegetation is one of the important means of mine ecological environment restoration and its effect assessment. Based on the GEE (Google Earth Engine) cloud platform, this study extracted the normalized difference vegetation index (NDVI) dataset of the non-ferrous metal mining areas in Dexing year by year from 2012 to 2022 based on MODIS remote sensing data, and used Sen slope analysis, Mann-Kendall test and Hurst index to analyze the characteristics of spatial and temporal dynamic changes and future trends of NDVI in the historical legacy areas before and after the mine production, ecological restoration projects. The results showed that: 1) before the implementation of the ecological restoration project from 2012 to 2017, the historical area was in a natural re-greening state, and the rate of change of NDVI was 0.0024/a, and after the implementation of the ecological restoration project from 2018 to 2022, the rate of increase of NDVI was significant and reached 0.0135/a. The change of NDVI in the in-production mining area from 2012 to 2022 generally showed a fluctuating and stable low-level state; 2) the highest proportion of significant regional decrease of NDVI in the historical mining area from 2012 to 2017 reached 51.52%, and the highest proportion of increase of NDVI in this area from 2018 to 2022 reached 99.09%. The NDVI in the in-production mining area was dominated by a slightly significant increase from 2012 to 2022; 3) through predictive analysis, the historical legacy areas will undergo significant ecological restoration and governance, and continue to show strong and sustained positive development in the future; a certain proportion of the mining areas in the southwest of Dexing will show a reverse trend. This study can provide a reference for the construction of ecological restoration projects and environmental management in mining areas.
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  • [1]
    王琳, 李娜, 文广超, 等. 黄河流域河南段植被覆盖度变化及其驱动力[J]. 水土保持通报, 2022, 42(6): 393-399.
    [2]
    宋梦来, 陈海涛, 丁晗, 等. 1990—2020年天津市植被覆盖度时空演变特征及影响因素分析[J]. 水土保持研究, 2023, 30(1): 154-163.
    [3]
    郑颖娟, 刘军会, 刘洋, 等. 2000—2018年鄂尔多斯市植被覆盖度变化及驱动因素分析[J]. 环境科学研究, 2022, 35(11): 2458-2468.
    [4]
    吕勇, 修丽娜, 姚晓军. 2000—2020年湟水流域植被NDVI变化及其驱动力分析[J]. 水土保持学报, 2023, 37(4): 150-157.
    [5]
    杨坤士, 卢远, 汤传勇. 广西南流江流域1986—2020年植被覆盖度时空变化及预测[J]. 科学技术与工程, 2022, 22(32): 14148-14158.
    [6]
    尘福艳, 杨创, 徐凯磊, 等. 基于Landsat遥感影像的杨伙盘矿区生态环境动态监测与评价研究[J]. 环境工程, 2023, 41(增刊1): 497-500.
    [7]
    庞博, 杨文鑫, 崔保山, 等. 黄河三角洲湿地生物多样性保护工程植被修复效果评估[J]. 环境工程, 2023, 41(1): 213-221.
    [8]
    邓目丽, 蒋馥根, 孙华, 等. 神木市植被覆盖度时空动态变化分析[J]. 森林与环境学报, 2021, 41(6): 611-619.
    [9]
    林妍敏, 南雄雄, 胡志瑞, 等. 西北典型生态脆弱区植被覆盖度时空变化及其生态安全评价:以宁夏贺兰山为例[J]. 生态与农村环境学报, 2022, 38(5): 599-608.
    [10]
    张进德, 郗富瑞. 我国废弃矿山生态修复研究[J]. 生态学报, 2020, 40(21): 7921-7930.
    [11]
    张东, 龙军, 杨微, 等. 萤石型铅锌尾矿渣的基质改良与矿山修复应用[J]. 环境工程, 2023, 41(2): 156-165.
    [12]
    邵泽强, 刘书奇, 陆文龙, 等. 基于Citespace的矿山生态修复的文献计量分析[J]. 环境工程, 2023, 41(增刊2): 707-711.
    [13]
    邢龙飞, 黄赳, 雷少刚, 等. 锡林浩特市胜利矿区近30 a植被覆盖度变化研究[J]. 河南理工大学学报(自然科学版), 2019, 38(3

    ): 61-69.
    [14]
    钟琪, 胡晋山, 康建荣. 基于像元二分法的大宁矿区植被覆盖度研究[J]. 金属矿山, 2021(11): 197-203.
    [15]
    钟安亚, 谷海红, 艾艳君,等. 我国矿区生态环境评价可视化研究分析[J]. 矿业研究与开发, 2022, 42(3): 186-194.
    [16]
    李微, 岳彩荣. 基于GEE云平台的2005—2017年云南省森林覆盖变化监测[J]. 西北林学院学报, 2022, 37(5): 182-187.
    [17]
    郝金虎, 韦玮, 李胜男, 等. 基于GEE平台的京津冀长时序水体时空格局及其影响因素[J]. 生态环境学报, 2023, 32(3): 556-566.
    [18]
    白淑英, 朱倩文, 沈渭寿, 等. 白云鄂博矿区生态退化研究[J]. 生态与农村环境学报, 2016, 32(3): 367-373.
    [19]
    裴子萱, 李强, 刘婷婷, 等. 基于GlobeLand30的城市生态用地时空变化特征:以北京市为例[J]. 生态学报, 2022, 42(24): 10072-10087.
    [20]
    FERN R R, FOXLEY E A, BRUNO A, et al. Suitability of NDVI and OSAVI as estimators of green biomass and coverage in a semi-arid rangeland[J]. Ecological Indicators, 2018, 94: 16-21.
    [21]
    吴秦豫, 姚喜军, 梁洁, 等. 鄂尔多斯市煤矿区植被覆盖改善和退化效应的时空强度[J]. 干旱区资源与环境, 2022, 36(8): 101-109.
    [22]
    艾丽亚, 王永芳, 郭恩亮, 等. 基于GEE的大青山国家级自然保护区NDVI变化及影响因素分析[J]. 干旱区地理, 2023, 46(8): 1279-1290.
    [23]
    王佃来, 刘文萍, 黄心渊. 基于Sen+Mann-Kendall的北京植被变化趋势分析[J]. 计算机工程与应用, 2013, 49(5): 13-17.
    [24]
    刘明霞. 赣江上游流域植被覆盖度变化及其驱动因素研究[D]. 赣州: 江西理工大学, 2021.
    [25]
    李林峰, 黄洁, 杨显华, 等. 露天煤矿区植被变化遥感监测与受损程度评估[J]. 地理空间信息, 2019, 17(1): 72-76

    ,11.
    [26]
    李晶, 崔绿园, 闫萧萧, 等. 草原矿区长时序植被覆盖度变化趋势对比分析[J]. 测绘通报, 2019(8): 130-134,157.
    [27]
    涂映红, 徐素琴. 德兴绿色发展让废弃矿山焕发新生机[N]. 上饶日报, 2022.
    [28]
    蒋美琛, 田淑芳, 詹骞. 北京周边重点矿山开采区的植被恢复状况评价[J]. 中国矿业, 2017, 26(6): 88-94.
    [29]
    包勤跃, 谷正楠, 张震. 基于Google Earth Engine的有色金属资源型地区植被覆盖度动态变化分析:以安徽省铜陵市为例[J]. 世界有色金属, 2022(14): 169-172.
    [30]
    孙炼. 基于NDVI的四川省植被变化动态监测及驱动因素分析[J]. 西南农业学报, 2023, 36(5): 1082-1089.
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