生态环境学报 ›› 2024, Vol. 33 ›› Issue (2): 180-191.DOI: 10.16258/j.cnki.1674-5906.2024.02.002

• 研究论文【生态学】 • 上一篇    下一篇

中国沿海地区植被NDVI时空变化及驱动力分析

李霞1(), 陈永昊1, 陈喆2,*(), 张国壮1, 唐梦雅1   

  1. 1.长安大学土地工程学院，陕西 西安 710054
    2.国家林业和草原局西北调查规划院，陕西 西安 710048
  • 收稿日期:2023-12-01 出版日期:2024-02-18 发布日期:2024-04-03
  • 通讯作者: *陈喆。E-mail: 414409439@qq.com
  • 作者简介:李霞（1977年生），女，副教授，主要研究方向是地理信息技术及生态遥感。E-mail: lixia666@chd.edu.cn
  • 基金资助:
    科技部外国文教专家项目(DL202317002L)

Analysis of Spatio-temporal Changes and Driving Vegetation NDVI in Coastal Areas of China

LI Xia1(), CHEN Yonghao1, CHEN Zhe2,*(), ZHANG Guozhuang1, TANG Mengya1   

  1. 1. School of Land Engineering, Chang'an University, Xi'an 710054, P. R. China
    2. Northwest Research and Planning Institute of State Forestry and Grassland Administration, Xi'an 710048, P. R. China
  • Received:2023-12-01 Online:2024-02-18 Published:2024-04-03

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摘要：

研究植被变化对区域生态修复具有重要意义。以中国沿海地区为例，基于归一化植被指数（NDVI）和降水、夜间灯光等自然和人为因子数据，运用Theil-Sen Median趋势分析+Mann-Kendall检验、最优参数地理探测器（OPGD）、相关分析和Hurst指数，多时空尺度探讨了中国沿海地区植被NDVI时空变化规律及其驱动力。结果表明：1）2001-2020年研究区植被状况较好，NDVI多年均值为0.762，具体到各分区，东北沿海的NDVI均值最高，其次是华南沿海，华东沿海和华北沿海；全区NDVI逐年变化率为0.019/10 a（P<0.01），不同分区的上升趋势从大到小为华南沿海、东北沿海、华北沿海和华东沿海，区域内植被状况不断改善，退耕还林还草和沿海防护林等生态工程效益不断显现；2）夜间灯光指数在全区各个因子中的解释力最大（q值为0.354），人为因素对NDVI的解释力明显大于自然因素，其对植被恢复产生了积极影响，并且随时间推移逐渐增强；3）两因子结合后的解释力大于单因子，表现为双因子增强和非线性增强。在全区范围内，影响最大的一对交互作用为土壤类型∩夜间灯光，其他分区则为日照时数∩夜间灯光（东北沿海地区），土壤类型∩夜间灯光（华北沿海和华东沿海地区），人口密度∩夜间灯光（华南沿海地区），自然因素和人类活动因素作用后影响力有了显著提升，但人类活动因素仍占据主导地位；4）Hurst指数均值为0.463，未来一段时间内，研究区内植被变化有66.3%的地区表现出一定的反持续性。研究结果有利于为中国沿海地区生态保护和高质量发展提供科学支撑。

关键词: NDVI, 时空变化, 驱动力, 最优参数地理探测器, 相关分析, 中国沿海地区

Abstract:

The study of vegetation changes is of great significance for regional ecological restoration. Taking the coastal areas of China as an example, this study explored spatiotemporal changes in vegetation and their driving forces using the Normalized Difference Vegetation Index (NDVI), in conjunction with data on precipitation, nighttime lights, and other natural and anthropogenic factors. Theil-Sen Median trend analysis, Mann-Kendall test, correlation analysis, Optimal Parameter Geographic Detector (OPGD), and Hurst index were employed at multiple scales. The findings were as follows: 1) the vegetation condition in the research area was good from 2001 to 2020, with an annual average NDVI of 0.762. Among the specific regions, the highest average NDVI value was found in the Northeast China coastal area, followed by the coastal areas of the southern, eastern, and northern regions of China. The overall annual change rate of NDVI was 0.019/10 a (P<0.01). The different regions are listed from high to low according to the rising trend: the southern, northeastern, northern, and eastern coastal regions. Vegetation conditions have continuously improved in the region, and the benefits of ecological projects, such as returning farmland to forests, grasslands, and coastal shelterbelts are continuously emerging. 2) Nighttime lights had the greatest explanatory power among various factors (q=0.354). Human activities showed more significant explanatory power for NDVI than natural factors, generating a positive impact on vegetation change that gradually strengthened over time. 3) The explanatory power of the combination of two factors was greater than that of a single factor, showing both synergistic and nonlinear enhancements. Within the entire region, the most significant interaction effect was observed between soil types ∩ nighttime lights, while in specific regions, it was sunshine hours ∩ nighttime lights (Coastal Northeast China), soil types ∩ nighttime lights (Coastal North China and Coastal East China), and population density ∩ nighttime lights (Coastal South China). Although the integrated influence of natural factors and human activities has increased significantly, human factors have remained dominant. 4) The mean value of the Hurst index was 0.463. Over the next period, certain levels of reversibility in terms of vegetation changes were observed in 66.3% of the study area. The research findings provide scientific support for ecological conservation and high-quality development of China's coastal areas.

Key words: NDVI, spatio-temporal change, driving forces, OPGD, correlation analysis, coastal areas of China

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