Contrasting biophysical impacts of vegetation growth and type transition greening on local temperature in Southwestern China

There is a noticeable greening trend observed in China over the first two decades of the 21st century attributed to both vegetation growth and type transition. However, the comparative impacts of these two greening on local climate and their associated biophysical mechanism have not been well appreciated, which is essential and beneficial for the development of regional ecological programs and climate mitigation. This study disentangles the influences of vegetation growth and type transitions on land surface temperature (LST) in southwestern China, employing a space-for-time approach utilizing satellite images from 2002−2022. Findings indicate that type transitions yield a more pronounced LST cooling, reaching 2‒3 times that of vegetation growth. Leaf area index (LAI) induced cooling is the highest in cropland to grassland transition, with a remarkable decrease of −0.058 ± 0.049 K, while the greatest cooling in vegetation growth is in grassland growth, achieving −0.031 ± 0.033 K. The highest LST sensitivity for type transitions is in Guangxi at −1.49 ± 0.52 K, whereas for vegetation growth is in Guizhou at −1.11 ± 0.28 K. Both types of greening exhibit cooling impacts predominantly driven by evapotranspiration, offsetting the albedo warming effect. Additionally, both albedo and LST sensitivities gradually decay with the increasing of greening degree to higher LAI saturation. This highlights both vegetation growth and type transitions contribute to local cooling with different intensity and effectiveness across vegetation types and regions. It is critical to consider their distinctions comprehensively and individually when formulating regional ecological programs and climate mitigation measures.

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Publication Details

Journal
Advances in Climate Change Research
Published
2025-11-06
DOI
https://doi.org/10.1016/j.accre.2025.10.010
Primary Topic
Remote Sensing in Agriculture
Type
article
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article

Contrasting biophysical impacts of vegetation growth and type transition greening on local temperature in Southwestern China

Ru Xu, Na Dong, Zhen Liu, Huabing Huang
Advances in Climate Change Research
Remote Sensing in Agriculture
article

Contrasting biophysical impacts of vegetation growth and type transition greening on local temperature in Southwestern China

Ru Xu, Na Dong, Zhen Liu, Huabing Huang
article en

Abstract

There is a noticeable greening trend observed in China over the first two decades of the 21st century attributed to both vegetation growth and type transition. However, the comparative impacts of these two greening on local climate and their associated biophysical mechanism have not been well appreciated, which is essential and beneficial for the development of regional ecological programs and climate mitigation. This study disentangles the influences of vegetation growth and type transitions on land surface temperature (LST) in southwestern China, employing a space-for-time approach utilizing satellite images from 2002−2022. Findings indicate that type transitions yield a more pronounced LST cooling, reaching 2‒3 times that of vegetation growth. Leaf area index (LAI) induced cooling is the highest in cropland to grassland transition, with a remarkable decrease of −0.058 ± 0.049 K, while the greatest cooling in vegetation growth is in grassland growth, achieving −0.031 ± 0.033 K. The highest LST sensitivity for type transitions is in Guangxi at −1.49 ± 0.52 K, whereas for vegetation growth is in Guizhou at −1.11 ± 0.28 K. Both types of greening exhibit cooling impacts predominantly driven by evapotranspiration, offsetting the albedo warming effect. Additionally, both albedo and LST sensitivities gradually decay with the increasing of greening degree to higher LAI saturation. This highlights both vegetation growth and type transitions contribute to local cooling with different intensity and effectiveness across vegetation types and regions. It is critical to consider their distinctions comprehensively and individually when formulating regional ecological programs and climate mitigation measures.

Advances in Climate Change ResearchVol. 17(1)
Sun Yat-sen University (CN), Chinese Academy of Sciences (CN), Hong Kong University of Science and Technology (HK), Ministry of Natural Resources (CN), Institute of Botany (CN)
Openalex Percentile: Top 68%
Remote Sensing in Agriculture
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