2000~2020年石林县植被NDVI变化特征分析
Analysis of Vegetation NDVI Change Characteristics in Shilin County, Yunnan Province, from 2000 to 2020
摘要: 植被覆盖变化能够反映一个区域的生态环境变化情况,对喀斯特生态安全与石漠化防控具有重要指示意义。本文基于MODIS NDVI库的云南省石林县2000~2020年植被NDVI变化数据,采用Theil-Sen趋势分析法与Mann-Kendall检验相结合的方法对研究区石林县植被时空变化趋势进行检验,并结合Hurst指数预测未来变化趋势。结果表明:(1) NDVI呈显著上升趋势,年均值由2000年的0.653增至2020年的0.758,累计增幅16.1%;(2) NDVI空间上具有异质性,高值区主要集中在东北部的山区,NDVI > 0.60,占比69.8%,低值区(8.5%)分布在城镇与石漠化地区;(3) 未来植被以持续改善为主(63.7%),但仍有9.8%区域存在“由改善转退化”的风险。本研究成果可为区域石漠化治理提供依据。
Abstract: Vegetation cover change reflects the ecological environment changes in a region and has important indicative significance for karst ecological security and rocky desertification control. This paper uses vegetation NDVI change data from 2000 to 2020 in Shilin County, Yunnan Province, from the MODIS NDVI database. The Theil-Sen trend analysis method combined with the Mann-Kendall test was used to examine the spatiotemporal change trend of vegetation in the study area of Shilin County, and the Hurst index was used to predict future trends. The results showed that: (1) NDVI showed a significant upward trend, with the annual average increasing from 0.653 in 2000 to 0.758 in 2020, a cumulative increase of 16.1%; (2) NDVI exhibited spatial heterogeneity, with high-value areas mainly concentrated in the mountainous areas of the northeast (NDVI > 0.60, accounting for 69.8%), while low-value areas (8.5%) were distributed in urban areas and rocky desertification areas; (3) Future vegetation is expected to continue to improve (63.7%), but 9.8% of the areas still face the risk of “transitioning from improvement to degradation”. The findings of this study can provide a basis for regional rocky desertification control.
文章引用:曾浚恒. 2000~2020年石林县植被NDVI变化特征分析[J]. 世界生态学, 2026, 15(2): 260-265. https://doi.org/10.12677/ije.2026.152027

参考文献

[1] 陈棋, 张超, 田湘云, 史小蓉, 张玉薇, 王妍. 云南省2000-2020年石漠化时空演变分析[J]. 浙江农林大学学报, 2023, 40(2): 417-426.
[2] 李加顺, 刘丽. 2000-2020年云南省植被时空变化及影响因素分析[J]. 草地学报, 2023, 31(11): 3503-3513.
[3] 夏凯, 黄义忠. 基于MODIS-NDVI的云南省植被时空变化及驱动因素分析[J]. 南方农业学报, 2023, 54(11): 3427-3437.
[4] Didan, K. (2021) MOD13Q1 MODIS/Terra Vegetation Indices 16-Day L3 Global 250m SIN Grid V061. NASA EOSDIS Land Processes DAAC.
[5] 和彩霞, 靖娟利, 边占新, 窦世卿, 徐勇, 何宏昌. 1982-2015年西南岩溶区NDVI时空变化及未来变化趋势[J]. 桂林理工大学学报, 2023, 43(2): 260-268.
[6] Anuradha, and Gupta, S. (2024) Assessment of Spatio-Temporal Changes in Land Use and Land Cover—A Case Study of Yamunanagar District (Haryana), India. Asian Journal of Water, Environment and Pollution, 21, 161-171. [Google Scholar] [CrossRef
[7] Wang, T., Zhao, M., Gao, Y., Yu, Z. and Zhao, Z. (2023) Analyzing Spatial-Temporal Change of Vegetation Ecological Quality and Its Influencing Factors in Anhui Province, Eastern China Using Multiscale Geographically Weighted Regression. Applied Sciences, 13, Article 6359. [Google Scholar] [CrossRef
[8] 李颖, 马双, 徐菀笛, 马霄雪, 刘自颖, 彭飞, 常艺琼. 东北三省干旱时空特征及其对植被覆盖变化的影响[J]. 生态学报, 2026, 46(5): 2701-2723.
[9] Bojago, E., Tadila, G. and Masha, M. (2025) Monitoring Spatio-Temporal Changes in Land Use, Land Cover, and NDVI Using MODIS Data in Ethiopia’s Gambela Region. Discover Applied Sciences, 7, Article No. 1361. [Google Scholar] [CrossRef
[10] 鞠洋, 马国忠, 尤宏宇. 大兴安岭地区降水与植被NDVI时空变化特征及其耦合协调关系[J]. 西北林学院学报, 2025, 40(6): 251-260.