Journal of Resources and Ecology ›› 2021, Vol. 12 ›› Issue (6): 729-742.DOI: 10.5814/j.issn.1674-764x.2021.06.002

• Ecosystem Assessment in Altay Region • Previous Articles     Next Articles

Spatiotemporal Pattern and Driving Force Analysis of Vegetation Variation in Altay Prefecture based on Google Earth Engine

HE Yuchuan1(), XIONG Junnan1, CHENG Weiming4,5,6,7, YE Chongchong1, HE Wen1, YONG Zhiwei1, TIAN Jie1   

  1. 1. School of Civil Engineering and Geomatics, Southwest Petroleum University, Chengdu 610500, China
    2. School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190, China
    3. Altay Regional Committee of the Communist Youth League, Altay, Xinjiang 836500, China
    4. State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    5. University of Chinese Academy of Sciences, Beijing 100049, China
    6. Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China
    7. Collaborative Innovation Center of South China Sea Studies, Nanjing 210093, China
  • Received:2021-04-01 Accepted:2021-05-30 Online:2021-11-30 Published:2022-01-30
  • About author:HE Yuchuan, E-mail:
  • Supported by:
    The Science and Technology Project of Xizang Autonomous Region(XZ201901-GA-07);The Key Research and Development Project of Sichuan Science and Technology Department(2021YFQ0042);The Science and Technology Bureau of Altay Region in Yili Kazak Autonomous Prefecture(Y99M4600AL)


Quantitative evaluation and driving mechanism analysis of vegetation dynamics are essential for promoting regional sustainable development. In the past 20 years, the ecological environment in Altay Prefecture has changed significantly due to global warming. Meanwhile, with increasing human activities, the spatiotemporal pattern and driving forces of vegetation variation in the area are uncertain and difficult to accurately assess. Hence, we quantified the vegetation growth by using the Normalized Difference Vegetation Index (NDVI) on the Google Earth Engine (GEE). Then, the spatiotemporal patterns of vegetation from 2000 to 2019 were analyzed at the pixel scale. Finally, significance threshold segmentation was performed using meteorological data based on the correlation analysis results, and the contributions of climate change and human activities to vegetation variation were quantified. The results demonstrated that the vegetation coverage in Altay Prefecture is mainly concentrated in the north. The vegetation areas representing significant restoration and degradation from 2000 to 2019 accounted for 24.08% and 1.24% of Altay Prefecture, respectively. Moreover, spatial correlation analysis showed that the areas with significant correlations between NDVI and temperature, precipitation and sunlight hours accounted for 3.3%, 6.9% and 20.3% of Altay Prefecture, respectively. In the significant restoration area, 18.94% was dominated by multiple factors, while 3.4% was dominated by human activities, and 1.74% was dominated by climate change. Within the significant degradation area, abnormal degradation and climate change controlled 1.07% and 0.17%, respectively. This study revealed the dynamic changes of vegetation and their driving mechanisms in Altay Prefecture, and can provide scientific support for further research on life community mechanism theory and key remediation technology of mountain-water-forest-farmland-lake-grass in Altay Prefecture.

Key words: vegetation variation, climate change, human activities, driving mechanism, Google Earth Engine, Altay Prefecture