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Spatio-Temporal Separating Analysis of NDVI Evolution and Driving Factors: A Case Study in Nanchang, China

Author

Listed:
  • Jiatong Li

    (School of Engineering, Tibet University, Lhasa 850000, China
    Joint Laboratory of Plateau Surface Remote Sensing, Tibet University, Lhasa 850000, China)

  • Hua Wu

    (School of Engineering, Tibet University, Lhasa 850000, China
    Joint Laboratory of Plateau Surface Remote Sensing, Tibet University, Lhasa 850000, China)

  • Jiaqi Zhu

    (School of Engineering, Tibet University, Lhasa 850000, China)

  • Yue Xu

    (School of Engineering, Tibet University, Lhasa 850000, China)

  • Qiyun Guo

    (School of Engineering, Tibet University, Lhasa 850000, China
    Joint Laboratory of Plateau Surface Remote Sensing, Tibet University, Lhasa 850000, China)

  • Huishan Li

    (Nanchang Meteorological Bureau, Nanchang 330000, China)

  • Xue Xie

    (School of Engineering, Tibet University, Lhasa 850000, China)

  • Sihang Liu

    (College of Horticulture and Landscape Architecture, Northeast Agricultural University, Harbin 150030, China)

Abstract

Investigating vegetation coverage and quantifying environmental changes offer critical insights for ecological protection, resource management, and policymaking. This study explores the spatial and temporal separation of evolutionary characteristics and driving factors of the NDVI in Nanchang City from 2000 to 2022, using methods such as the Hurst Exponent, the ReliefF feature selection algorithm, and geographical detectors. The results show the following observations: (1) Temporal analysis: the average NDVI in Nanchang City was 0.453, showing an overall upward trend, although the rate of increase gradually slowed over time. (2) Spatial analysis: vegetation in Nanchang City exhibited a pattern of sustained reverse development, with notable trends of “improvement around rivers and lakes” and “large-scale degradation of urban land”. (3) Feature selection: among the three algorithms tested, ReliefF proved most effective in analyzing temporal drivers of NDVI changes. Human factors were identified as the dominant drivers of NDVI variation, while meteorological factors were less significant. (4) Geographical driver analysis: The geographical detectors revealed that population density, nighttime lights, and land cover types were the primary drivers of vegetation change. Regions with a negative correlation between NDVI and human factors are mainly centered in the central area of Nanchang City and Jinxian County, whereas positive correlations were observed around rivers and lakes. This study delves into the changing patterns of vegetation cover in Nanchang City, offering scientific insights to guide the protection and management of the regional ecological environment, thereby promoting sustainable development.

Suggested Citation

  • Jiatong Li & Hua Wu & Jiaqi Zhu & Yue Xu & Qiyun Guo & Huishan Li & Xue Xie & Sihang Liu, 2024. "Spatio-Temporal Separating Analysis of NDVI Evolution and Driving Factors: A Case Study in Nanchang, China," Sustainability, MDPI, vol. 16(23), pages 1-23, November.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:23:p:10494-:d:1533099
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    References listed on IDEAS

    as
    1. Rina Wu & Jiquan Zhang & Yuhai Bao & Feng Zhang, 2016. "Geographical Detector Model for Influencing Factors of Industrial Sector Carbon Dioxide Emissions in Inner Mongolia, China," Sustainability, MDPI, vol. 8(2), pages 1-12, February.
    2. Yuxi Liu & Cheng Huang & Lvshui Zhang, 2023. "The Spatio-Temporal Patterns and Driving Forces of Land Use in the Context of Urbanization in China: Evidence from Nanchang City," IJERPH, MDPI, vol. 20(3), pages 1-17, January.
    3. Jian Wang & Junsan Zhao & Peng Zhou & Kangning Li & Zhaoxiang Cao & Haoran Zhang & Yang Han & Yuanyuan Luo & Xinru Yuan, 2023. "Study on the Spatial and Temporal Evolution of NDVI and Its Driving Mechanism Based on Geodetector and Hurst Indexes: A Case Study of the Tibet Autonomous Region," Sustainability, MDPI, vol. 15(7), pages 1-24, March.
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