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Analysis of Spatiotemporal Variation Characteristics and Influencing Factors of Grassland Vegetation Coverage in the Qinghai–Tibet Plateau from 2000 to 2023 Based on MODIS Data

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  • Xiankun Shi

    (Xining Natural Resources Comprehensive Survey Center, China Geological Survey, Xining 810021, China
    Key Laboratory of Coupling Process and Effect of Natural Resources Elements, Beijing 100055, China
    School of Surveying and Geoinformation Engineering, East China University of Technology, Nanchang 330013, China)

  • Dong Yang

    (School of Grassland Science, Beijing Forestry University, Beijing 100083, China)

  • Shijian Zhou

    (School of Software, Nanchang Campus, Nanchang Hangkong University, Nanchang 330063, China)

  • Hongwei Li

    (Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China)

  • Siting Zeng

    (School of Surveying and Geoinformation Engineering, East China University of Technology, Nanchang 330013, China)

  • Chen Yin

    (Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China)

  • Mingxin Yang

    (Xining Natural Resources Comprehensive Survey Center, China Geological Survey, Xining 810021, China
    Key Laboratory of Coupling Process and Effect of Natural Resources Elements, Beijing 100055, China
    School of Grassland Science, Beijing Forestry University, Beijing 100083, China)

Abstract

Changes in grassland fractional vegetation coverage (FVC) are important indicators of global climate change. Due to the unique characteristics of the Tibetan Plateau ecosystem, variations in grassland coverage are crucial to its ecological stability. This study utilizes the Google Earth Engine (GEE) platform to retrieve long-term MODIS data and analyzes the spatiotemporal distribution of grassland FVC across the Qinghai–Tibet Plateau (QTP) over 24 years (2000–2023). The grassland growth index (GI) is used to evaluate the annual grassland growth at the pixel level. GI is an important indicator for measuring grassland growth status, which can effectively measure the changes in grassland growth in each year relative to the base year. FVC trends are monitored using Sen-Mann-Kendall slope estimation, the coefficient of variation, and the Hurst exponent. Geographic detectors and partial correlation analysis are then applied to explore the contribution rates of key driving factors to FVC. The results show: (1) From 2000 to 2023, FVC exhibited an overall upward trend, with an annual growth rate of 0.0881%. The distribution of FVC on the QTP follows a pattern of higher values in the east and lower values in the west; (2) Over the past 24 years, 54.05% of the total grassland area has shown a significant increase, 23.88% has remained stable, and only a small portion has shown a significant decrease. The overall trend is expected to continue with minimal variability, covering 82.36% of the total grassland area. The overall grassland GI suggests a balanced state of growth; (3) precipitation (Pre) and soil moisture (SM) are the main single factors affecting FVC changes in grasslands on the Tibetan Plateau (q = 0.59 and 0.46). In the interaction detection, in addition to the highest interaction between Pre and other factors, the interaction between SM and other factors also showed a significant impact on the changes in FVC of the QTP grassland; partial correlation analysis of hydrothermal factors and FVC of the QTP grassland. It shows that precipitation has a stronger correlation with QTP grassland FVC changes than temperature. This study has enhanced our understanding of grassland vegetation change and its driving factors on the QTP and quantitatively described the relationship between vegetation change and driving factors, which is of great significance for maintaining the sustainable development of grassland ecosystems.

Suggested Citation

  • Xiankun Shi & Dong Yang & Shijian Zhou & Hongwei Li & Siting Zeng & Chen Yin & Mingxin Yang, 2024. "Analysis of Spatiotemporal Variation Characteristics and Influencing Factors of Grassland Vegetation Coverage in the Qinghai–Tibet Plateau from 2000 to 2023 Based on MODIS Data," Land, MDPI, vol. 13(12), pages 1-21, December.
  • Handle: RePEc:gam:jlands:v:13:y:2024:i:12:p:2127-:d:1539004
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    References listed on IDEAS

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    1. Xiaoyu Deng & Liangxu Wu & Chengjin He & Huaiyong Shao, 2022. "Study on Spatiotemporal Variation Pattern of Vegetation Coverage on Qinghai–Tibet Plateau and the Analysis of Its Climate Driving Factors," IJERPH, MDPI, vol. 19(14), pages 1-17, July.
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