Remote Sensing Technology and Application, Volume. 40, Issue 2, 429(2025)
Monitoring of Vegetation Restoration Effectiveness based on Multiple-Source Remote Sensing：A Case Study of Beijing’s Mine Restoration Areas
Figures & Tables(9)
Fig. 3. FVC distribution maps and difference map of the mining area
Fig. 6. Calculation results of structural parameters in mining areas
Fig. 7. Mining area different structural parameter area proportion statistics
Fig. 8. Correlation analysis results between FVC and structural indicators in 2022
Table 1.
Analysis of FVC change trends in mining areas from 2018 to 2022 View tableView in ArticleTable 1.
Analysis of FVC change trends in mining areas from 2018 to 2022 植被覆盖度变化趋势 变化率 显著水平 A矿区面积占比/% B矿区面积占比/% C矿区面积占比/% D矿区面积占比/% 显著增长 Slope>0 P<0.05 5.79 5.07 15.72 7.13 不显著增长 Slope>0 P>0.05 54.14 43.10 60.87 66.63 基本稳定 Slope=0 0.00 0.04 0.13 0.00 显著减少 Slope<0 P<0.05 2.48 7.07 0.35 1.13 不显著减少 Slope<0 P>0.05 37.58 44.73 22.92 25.13
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Danyang LIN, Huaguo HUANG, Haitao YANG, Kai CHENG, Mengchao BAI, Qiang ZHANG, Wenhui ZHAO, Hanlin WANG, Haifeng LU, Huawei WAN, Lingjun LI, Qinghua GUO. Monitoring of Vegetation Restoration Effectiveness based on Multiple-Source Remote Sensing：A Case Study of Beijing’s Mine Restoration Areas[J]. Remote Sensing Technology and Application, 2025, 40(2): 429
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Received: Mar. 18, 2024
Accepted: --
Published Online: May. 23, 2025
The Author Email: Huaguo HUANG (huaguo_huang@bjfu.edu.cn)
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