| 于天娇,林 鹏,王彩霞,赵 凯.露天矿山植被覆盖率提取及评价方法研究[J].甘肃地质,2025,(1):70-75 |
| 露天矿山植被覆盖率提取及评价方法研究 |
| Extraction ａnd Evaluation Methods ｏf Fractional Vegetation Cover ｉn Open Pit Mines |
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| DOI： |
| 中文关键词: 矿山生态修复 植被覆盖率 机器学习 分级量化 |
| 英文关键词:mine ecological restoration fractional vegetation cover machine learning hierarchical quantization |
| 基金项目:自然资源部部省合作试点项目（2023ZRBSHZ013）；甘肃省自然资源厅科技创新项目（202429） |
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| 中文摘要: |
| 植被覆盖率作为植被重建成效中一个重要的评估指标，可以用来评估露天矿山生态修复的成效。本文利用高清航摄影像为分析底图，基于ENVI软件和机器学习对每个矿山生态修复区及周边区域的植被覆盖率进行了计算分析，通过对比生态修复区植被覆盖率和周边原生植被覆盖率的比值大小，量化分级，为整个矿山的成效评估提供指标数据。研究结果表明：以甘南黄河上游25处历史遗留废弃矿山生态修复工程为例，采用机器学习的方法对其植被覆盖率进行提取并评价，经检验该方法可行。 |
| 英文摘要: |
| Fractional Vegetation Cover is an important evaluation index in the evaluation of ecological restoration effect of mines, this study examines 25 historical abandoned mine ecological restoration projects in the upper reaches of the Yellow River in Gannan as samples. It utilizes high-resolution aerial photography as an analysis base map and employs ENVI software and machine learning to calculate and analyze the fractional vegetation cover of each mine ecological restoration area and its surrounding areas. By comparing the ratio between the fractional vegetation cover of the ecological restoration area and that of the surrounding native vegetation, it provides quantitative classification for index data used in evaluating the effectiveness of the entire mine.
The results show that fractional vegetation cover extracted by ENVI software is consistent with the actual survey results, and it is feasible to use the comparison method to classify the index data. |
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