生态环境学报 ›› 2024, Vol. 33 ›› Issue (7): 1008-1018.DOI: 10.16258/j.cnki.1674-5906.2024.07.002

• 研究论文【生态学】 • 上一篇    下一篇

气候变化背景下内蒙古中西部植被覆盖度演变特征研究

徐佳乐1(), 杨兴川1,*(), 赵文吉1, 杨志强1, 钟一雪1, 师乐颜1, 马鹏飞2   

  1. 1.首都师范大学资源环境与旅游学院,北京 100048
    2.国家环境保护卫星遥感重点实验室,北京 100094
  • 收稿日期:2024-04-22 出版日期:2024-07-18 发布日期:2024-09-04
  • 通讯作者: *杨兴川。E-mail: mxoyxc@163.com
  • 作者简介:徐佳乐(2002年生),男,硕士研究生,主要从事生态遥感与地学应用研究。E-mail: 2230902132@cnu.edu.cn
  • 基金资助:
    国家自然科学基金青年科学基金项目(42305198)

Evolution Characteristics of Vegetation Coverage in Central and Western Inner Mongolia under the Background of Climate Change

XU Jiale1(), YANG Xingchuan1,*(), ZHAO Wenji1, YANG Zhiqiang1, ZHONG Yixue1, SHI Leyan1, MA Pengfei2   

  1. 1. College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, P. R. China
    2. State Environmental Protection Key Laboratory of Satellite Remote Sensing, Beijing 100094, P. R. China
  • Received:2024-04-22 Online:2024-07-18 Published:2024-09-04

摘要:

植被覆盖的动态演变能够有效地反映区域生态环境变化。为探究内蒙古中西部5个盟市植被覆盖度时空演变特征及对气候变化的响应,基于MODIS NDVI数据和同期气候因子(平均气温、累计降水、平均日照时数、平均相对湿度)数据,利用Theil-Sen Median趋势分析、MK检验、Hurst指数、偏相关分析等方法分析了内蒙古中西部5个盟市2000-2021年植被覆盖度和气候因子的时空变化特征及植被覆盖度对气候因子的响应。结果表明:2000-2021年,内蒙古中西部5个盟市的平均植被覆盖度为0.321,处于较低水平;22年间,植被覆盖度呈波动上升趋势,增长速度为0.4%。研究区植被覆盖度呈现东高西低的分布格局,低覆盖度面积为53.2%,中高覆盖度和高覆盖度约占总面积的10%。研究区植被覆盖度的平均Sen斜率为0.004,表明植被覆盖整体呈上升趋势;植被改善区域面积达89.1%,植被退化部分占比为10.6%。Hurst指数均值为0.423。结合Sen趋势,预测出未来覆盖度以稳步增长为主,其中48.4%的区域不会发生显著的植被改善或退化现象,30.6%的区域未来以植被改善为主。研究区平均气温、累计降水量呈上升趋势,而平均日照时数和平均相对湿度呈下降趋势。植被覆盖度与平均气温的关系以不显著相关为主,其中通过显著性检验(p<0.05)的正相关面积为14.7%;植被覆盖度与累计降水量的关系以正相关为主,正相关面积占比为98.1%;与平均日照时数和平均相对湿度的关系均以不显著相关为主。

关键词: 植被覆盖度, 时空格局, 气候变化, 相关分析, 趋势预测, 归一化植被指数

Abstract:

The dynamic evolution of vegetation cover can effectively reflect the changes in the regional ecological environment. To investigate the spatiotemporal characteristics of vegetation cover and its response to climate change in five leagues in central and western Inner Mongolia, we used MODIS NDVI data and concurrent climate factor data (average temperature, cumulative precipitation, average sunshine hours, average relative humidity), along with analytical techniques such as Theil-Sen Median trend analysis, Mann-Kendall test (MK), Hurst exponent, and partial correlation analysis to analyze the spatiotemporal variations of vegetation cover and climate factors from 2000 to 2021, as well as the response of vegetation cover to climate change. The results indicate that the average vegetation cover in the five leagues of central and western Inner Mongolia was 0.321 from 2000 to 2021, which was relatively low. During the 22-year period, the vegetation cover showed a fluctuating upward trend, with a growth rate of 0.4%. The distribution pattern of vegetation cover in the study area showed a higher cover in the east and lower cover in the west, with low-coverage areas accounting for 53.2% and moderate-to-high-coverage areas accounting for approximately 10% of the total area. The average Sen slope of the vegetation cover in the study area was 0.004 from 2000 to 2021, indicating an overall increasing trend in vegetation cover. Areas with improved vegetation cover accounted for 89.1% of the study area, whereas areas with degraded vegetation accounted for 10.6%. The mean Hurst exponent during the study period was 0.423. Combined with the Sen trend, a steady increase in future vegetation cover was predicted, with 48.4% of the region showing no significant vegetation improvement or degradation and 30.6% of the area dominated by vegetation improvement. The average temperature and cumulative precipitation exhibited increasing trends, whereas the average sunshine hours and average relative humidity exhibited decreasing trends from 2000 to 2021. Vegetation cover showed no significant correlation with the average temperature, with only 14.7% of the area showing a significant positive correlation (p<0.05). The vegetation cover and cumulative precipitation were positively correlated, with 98.1% of the area being positively correlated. However, the relationships between vegetation cover, sunshine hours, and relative humidity were dominated by non-significant correlations.

Key words: vegetation coverage, spatial and temporal pattern, climate change, correlation analysis, trend prediction, normalized difference vegetation index (NDVI)

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