1.昆明理工大学国土资源工程学院,昆明 650093
2.云南省定量遥感重点实验室,昆明 650093
3.云南省山地灾害天空地一体化智慧监测国际联合实验室,昆明 650093
4.云南大学国际河流与;生态安全研究院,昆明 650500
5.国家林业和草原局西南调查规划院,昆明 650031
陈志元(2002—),男,硕士研究生,主要从事遥感图像处理与信息分析研究。E-mail:20252101048@stu.kust.edu.cn
陈国坤(1989—),男,博士,硕士生导师,副教授,主要从事土壤侵蚀与水土保持研究。E-mail:chengk@radi.ac.cn
收稿:2026-04-28,
修回:2026-05-26,
录用:2026-06-09,
网络首发:2026-08-26,
纸质出版:2026-10-28
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陈志元,陈国坤,胡春田,等.多指标协同的典型石漠化区植被动态遥感监测及治理成效分析[J].水土保持学报,2026,40(5):22-34.
Chen Zhiyuan, Chen Guokun, Hu Chuntian, et al. Multi-indicator synergistic monitoring of vegetation dynamics and restoration effectiveness in typical karst rocky desertification regions[J]. Journal of Soil and Water Conservation,2026,40(5):22-34.
陈志元,陈国坤,胡春田,等.多指标协同的典型石漠化区植被动态遥感监测及治理成效分析[J].水土保持学报,2026,40(5):22-34. DOI: 10.13870/j.cnki.stbcxb.2026.05.040. CSTR: 32310.14.stbcxb.2026.05.040.
Chen Zhiyuan, Chen Guokun, Hu Chuntian, et al. Multi-indicator synergistic monitoring of vegetation dynamics and restoration effectiveness in typical karst rocky desertification regions[J]. Journal of Soil and Water Conservation,2026,40(5):22-34. DOI: 10.13870/j.cnki.stbcxb.2026.05.040. CSTR: 32310.14.stbcxb.2026.05.040.
目的
2
本研究以文山州石漠化重点治理工程区为主要研究对象,旨在通过分析喀斯特石漠化区植被覆盖度、相对裸露度和潜在侵蚀风险等指标的协同变化特征及差异,为治理工程成效评估提供参考。
方法
2
基于2021—2025年Sentinel-2生长季遥感影像,以2021年作为遥感监测基线年,计算归一化植被指数(NDVI)、增强型植被指数(EVI)、植被覆盖度(FVC)、归一化差异岩石指数(NDRI)及基于NDRI的相对裸露度(BERI);同时构建降雨侵蚀力加权的植被覆盖与管理因子(
C
)。结合CHIRPS降水、ERA5-Land气温和6个月标准化降水指数(SPI6)干旱指数,采用分区统计、显著性检验、工程-非工程变化量之差、基线FVC分层和Pearson相关分析,开展不同治理工程类型的植被动态遥感监测及治理成效分析。
结果
2
1)2021—2025年,工程区整体NDVI、EVI和FVC分别提高5.47%、5.03%和8.58%,
C
因子
下降58.10%,植被覆盖状况总体改善,潜在侵蚀风险降低;BERI下降2.14%,但未达到显著水平,说明相对裸露度变化较植被恢复存在滞后。2)不同治理措施响应幅度存在差异,草原改良区NDVI和FVC增幅最大,分别为11.17%和19.65%;退化林修复区BERI降幅最大,其相对裸露度改善较为明显,各治理措施类型
C
因子均呈下降趋势。3)受气候扰动和年际波动影响,2023年各分区普遍出现NDVI、FVC下降及BERI、
C
因子升高等阶段性波动,其中草原改良区对降水变化最为敏感。4)基线FVC分层比较和Pearson相关分析表明,不同治理类型的响应幅度也存在差异。在相近初始覆盖条件下,工程区中、高覆盖层FVC改善幅度高于非工程区,显示工程区在部分基线条件下具有相对恢复优势;植被覆盖、相对裸露度和潜在侵蚀风险之间具有一定协同变化关系。
结论
2
文山州石漠化重点治理工程区总体表现出生态改善的特征,但不同治理类型区的植被恢复程度、BERI响应强度并不一致。多指标协同监测能够较完整地揭示不同治理措施的差异,为喀斯特石漠化治理成效评估和生态修复措施优化提供参考。
Objective
2
This study focuses on the key rocky desertification control project areas in Wenshan Prefecture, aiming to analyze the synergistic variation characteristics and differences in vegetation cover, relative bareness, and potential erosion risk in karst rocky desertification regions, thereby providing references for evaluating the effectiveness of ecological restoration projects.
Methods
2
Based on Sentinel-2 growing-season remote sensing images from 2021 to 2025, with 2021 set as the baseline year, we calculated NDVI, EVI, FVC, NDRI, and NDRI-based BERI. A rainfall erosivity-weighted vegetation cover and management factor (
C
factor) was constructed by integrating CHIRPS precipitation data, ERA5-Land temperature data, and the SPI6 drought index. Zonal statistics, significance testing, difference in changes between project and non-project areas, stratified analysis based on baseline FVC, and Pearson correlation analysis were employed to monitor vegetation dynamics and assess restoration effectiveness across different treatment types.
Results
2
1) From 2021 to 2025, overall NDVI, EVI, and FVC in the project area increased by 5.47%, 5.03%, and 8.58%, respectively; the
C
factor decreased by 58.10%, indicating an overall improvement in vegetation cover and a reduction in potential erosion ris
k. BERI declined by 2.14%, but not significantly, suggesting that changes in relative bareness lag behind vegetation recovery. 2) Different restoration measures showed varying responses: grassland improvement areas exhibited the largest increases in NDVI (11.17%) and FVC (19.65%); degraded forest restoration areas had the greatest decline in BERI, reflecting notable improvement in relative bareness; all treatment types showed decreasing trends in the
C
factor. 3) Influenced by climatic fluctuations and inter-annual variability, NDVI and FVC generally declined in 2023, while BERI and the
C
factor increased temporarily; grassland improvement areas were most sensitive to precipitation variations. 4) Stratified comparison by baseline FVC and Pearson correlation analysis revealed differential responses among treatment types: under similar initial coverage conditions, medium and high coverage in the project area improved more than those in non-project areas, indicating relative restoration advantages under certain baseline conditions; vegetation cover, relative bareness, and potential erosion risk displayed significant synergistic variation patterns.
Conclusion
2
The key rocky desertification control project areas in Wenshan have shown overall ecological improvement, yet vegetation recovery rates and BERI response intensities vary among different treatment zones. Multi-indicator synergistic monitoring provides a relatively comprehensive approach to distinguishing the effects of different restoration measures, offering scientific references for effectiveness evaluation and optimization of ecological restoration strategies in karst rocky desertification regions.
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