Revealing global terrestrial vegetation dynamic across timescales based on long time series satellite observations

CUI Yilin; ZHOU Jie; JIANG Yiqiu; GUO Dongliang; ZOU Li

doi:10.11834/jrs.20265001

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Revealing global terrestrial vegetation dynamic across timescales based on long time series satellite observations
Vol. 30, Issue 5, Pages: 1357-1373(2026)
Received：09 January 2025，

Published：07 May 2026
DOI： 10.11834/jrs.20265001
稿件说明：

移动端阅览

崔祎霖，周杰，蒋奕秋，郭栋梁，邹丽.2026.基于长时序卫星观测的全球陆表植被多时间尺度动态特征分析.遥感学报，30（5）： 1357-1373 DOI： 10.11834/jrs.20265001.

Cui Y L， Zhou J， Jiang Y Q， Guo D L and Zou L. 2026. Revealing global terrestrial vegetation dynamic across timescales based on long time series satellite observations. National Remote Sensing Bulletin， 30（5）：1357-1373 DOI： 10.11834/jrs.20265001.

摘要

植被作为陆地生态系统的重要组成部分，对全球气候的变化具有深远影响。准确刻画植被动态特征对于把握和预测全球变暖背景下生态系统结构和功能的演变途径至关重要。本研究基于现有的长时序多源植被遥感产品，利用频谱分析方法实现对全球陆表植被时间尺度空间格局的表征，并在多时间尺度视角下分析植被动态趋势特征。结果表明：（1）全球陆地表面大部分区域（78.4%）的植被生长动态主要受年尺度主导。年内尺度主导的区域占16.1%，主要分布于热带地区。而年际尺度主导的区域占比最小（5.5%），主要位于半干旱灌木丛区。（2）植被年尺度振幅值和植被生长峰值存在显著相关关系的区域，主要分布在植被季节性生长变化特征较为显著的区域。年尺度相位值与时间域上遥感物候参数仅在全球28.19%的植被覆盖区域呈现显著正相关性（

0.1），其中植被峰值期与年尺度相位值相关性最好。（3）植被指数多个时间尺度（年际尺度、年尺度、年内尺度）上的振幅时间趋势呈现出大范围的增长趋势，与广泛关注的“全球植被绿化”现象（植被指数年均值呈现增长趋势）总体保持一致。但各个时间尺度上的趋势特征呈现出较大的空间差异性，3个时间尺度上的振幅时间动态仅解释了年均值动态特征的66%，凸显出“全球植被绿化现象”的时间尺度依赖性。总之，本文利用频谱分析方法实现对全球陆表植被动态特征的多时间尺度分析，可为全球陆表植被动态研究提供新的视角，对深化全球陆表植被绿化现象及其生态系统功能响应机制的科学认识具有重要意义。

Abstract

As an important part of the terrestrial ecosystem

vegetation exerts a profound influence on global climate variation. Accurately characterizing vegetation dynamics is crucial for capturing and predicting changes in ecosystem structure and function in the context of global warming. On the basis of existing long-time series and multisource vegetation remote sensing products

this study uses the spectrum analysis method to characterize the spatial pattern of global continental surface vegetation on timescales and analyzes the dynamic trend characteristics of vegetation from the perspective of multiple timescales.

Using long-term

multi-source remote sensing vegetation products

this study decomposes vegetation dynamics into three key timescales: interannual

annual

and intra-annual through by using spectral analysis. The amplitude obtained from Fourier analysis is used to characterize the spatial pattern of vegetation dynamics

and the phase value is used to evaluate the coupling relationship with phenological parameters. In addition

the temporal trend of vegetation indices is evaluated to explore its relationship with the observed “global greening” phenomenon.

(1) Vege

tation growth dynamics in most areas of the global land surface (78.4%) are largely dominated by the annual scale. The areas dominated by the intra-annual scale account for 16.1% and are mostly distributed in tropical areas. Areas dominated by the interannual scale constitute the smallest proportion (5.5%) and are mostly located in semiarid shrublands. (2) A significant correlation exists between the annual scale amplitude of vegetation and the peak value of vegetation growth. This correlation is mostly distributed in regions with more significant characteristics of vegetation seasonal growth. Only 28.19% of the global vegetation cover areas exhibited a significant positive correlation between the phase values at the annual scale and the phenological parameters in the time domain (

0.1). Among these

the correlation between the peak vegetation period and annual-scale phase values is the strongest. (3) The amplitude temporal trend of the vegetation index on multiple timescales (Low frequency

Middle frequency

High frequency) exhibits a large-scale growth trend

which is generally consistent with the phenomenon of “global vegetation greening” (i.e.

increasing annual mean vegetation index values). However

the trend characteristics exhibit considerable spatial heterogeneity across scales. Notably

amplitude dynamics at the three scales explain only 66% of the annual mean dynamic characteristics

highlighting the temporal scale dependence of the “global vegetation greening” phenomenon.

This study employs spectral analysis to conduct a multi-temporal scale analysis of global vegetation dynamics

offering a novel perspective for related research. The findings contribute significantly to a deeper scientific understanding of global vegetation greening and its response mechanisms within broader ecosystem functions.

关键词

Keywords

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