Anthropogenic and natural influence on vegetation ecosystems from 1982 to 2023

Abstract Vegetation greening trends are a critical and direct indicator to reflect photosynthetic activity of plants at the ecosystem scale. The monitoring of vegetation greening is crucial for assessing ecosystem health, sustaining biodiversity, improving soil health, and providing direction for effective environmental management. However, long-term changes in greening trends are rarely reported due to radiometric inconsistencies among different satellite sensors. Here, we used 12 machine learning algorithms to perform pixel correction on 42 years of moderate resolution imaging spectroradiometer normalized difference vegetation index (NDVI) and GIMMS NDVI data. The models exhibited high accuracy (93%–97%), yielding a robust ensemble R 2 of 0.88 at the spatial scale. From 1982 to 2023, global NDVI had an increasing trend (0.0012), particularly in the high-latitude regions of the Northern Hemisphere (>60° N), with the rate of increase accelerating since 2000. Temperature and water conditions showed significant correlations with greening trends, exhibiting spatially asymmetric effects. In addition, frequent land cover changes promoted the growth of greening trends (∼23%), which is linked to enhanced structural plasticity of vegetation. This effect has become more pronounced since 2000, with 92% of such changes occurring during this period. Anthropogenic impact may play a role in driving greening trend reductions, rather than enhancements.

Authors

Publication Details

Journal
Environmental Research Letters
Published
2025-08-08
DOI
https://doi.org/10.1088/1748-9326/adf980
Citations
1
Primary Topic
Forest ecology and management
Type
article
Field-Weighted Citation Impact
2.31

Funders

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article

Anthropogenic and natural influence on vegetation ecosystems from 1982 to 2023

Huaqiang Li, Ke Liu, Ghulam Muhammad Ali, Matthew Tom Harrison et al.
1 citations
Environmental Research Letters
Forest ecology and management
2.31
article

Anthropogenic and natural influence on vegetation ecosystems from 1982 to 2023

Huaqiang Li, Ke Liu, Ghulam Muhammad Ali, Matthew Tom Harrison, Yonghong Hao, Teligeer Bao
article en
1 citations

Abstract

Abstract Vegetation greening trends are a critical and direct indicator to reflect photosynthetic activity of plants at the ecosystem scale. The monitoring of vegetation greening is crucial for assessing ecosystem health, sustaining biodiversity, improving soil health, and providing direction for effective environmental management. However, long-term changes in greening trends are rarely reported due to radiometric inconsistencies among different satellite sensors. Here, we used 12 machine learning algorithms to perform pixel correction on 42 years of moderate resolution imaging spectroradiometer normalized difference vegetation index (NDVI) and GIMMS NDVI data. The models exhibited high accuracy (93%–97%), yielding a robust ensemble R 2 of 0.88 at the spatial scale. From 1982 to 2023, global NDVI had an increasing trend (0.0012), particularly in the high-latitude regions of the Northern Hemisphere (>60° N), with the rate of increase accelerating since 2000. Temperature and water conditions showed significant correlations with greening trends, exhibiting spatially asymmetric effects. In addition, frequent land cover changes promoted the growth of greening trends (∼23%), which is linked to enhanced structural plasticity of vegetation. This effect has become more pronounced since 2000, with 92% of such changes occurring during this period. Anthropogenic impact may play a role in driving greening trend reductions, rather than enhancements.

Environmental Research LettersVol. 20(9)
National Natural Science Foundation of China
Openalex Percentile: Top 12%
Forest ecology and management
2.31
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