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ORIGINAL RESEARCH article

Front. Environ. Sci.
Sec. Environmental Informatics and Remote Sensing
Volume 12 - 2024 | doi: 10.3389/fenvs.2024.1489267

Spatiotemporal Analysis of Phenological Metrics on the Qinghai-Tibet Plateau Based on Multiple Vegetation Indices

Provisionally accepted
Tao Chen Tao Chen 1Zhu Chen Zhu Chen 2*Guojing Xie Guojing Xie 2*
  • 1 Surveying and Mapping Data Archives of Guizhou Province, Guiyang, China
  • 2 Guizhou Tianditong Technology Co.,Ltd, Guiyang, China

The final, formatted version of the article will be published soon.

    As global climate change intensifies, understanding the response mechanisms and adaptive capacities of ecosystems to climate change has become a core focus in environmental science. The Qinghai-Tibet Plateau (QTP), a region highly sensitive to global climate change, shows vegetation phenological shifts that reflect the ecosystem's response to climate fluctuations. However, how phenological metrics extracted from different vegetation indices affect our understanding of these shifts in the region remains unclear. This study analyzes the start (SOS) and end (EOS) of the growing season on the QTP from 1982 to 2015 using GIMMS NDVI3g data. These metrics were compared with phenological data derived from GIMMS LAI3g and MODIS EVI2 data. The results indicate that phenological metrics derived from different vegetation indices (NDVI, LAI, and EVI2) are generally consistent in their spatiotemporal distribution and show significant correlations. However, regional differences and temporal inconsistencies were observed. This comparative analysis reveals the strengths and limitations of various vegetation indices in phenological metric extraction. The results offer crucial insights for enhancing the precision of phenological modeling and highlight the significance of choosing suitable vegetation indices in future studies on phenology.

    Keywords: vegetation indices, Phenological metrics, Spatiotemporal variation, Qinghai-Tibet Plateau, remote sensing

    Received: 31 Aug 2024; Accepted: 06 Nov 2024.

    Copyright: © 2024 Chen, Chen and Xie. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence:
    Zhu Chen, Guizhou Tianditong Technology Co.,Ltd, Guiyang, China
    Guojing Xie, Guizhou Tianditong Technology Co.,Ltd, Guiyang, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.