Accounting for exact vegetation index recording date to enhance evaluation of time-lagged and accumulated climatic effects on global vegetation greenness

Considering time-lag and accumulation effects of climate is crucial for accurately evaluating vegetation dynamics under global climate change. Most studies investigate these mechanisms by examining the explanatory power of the overall climatic conditions of the same month of the day at which the vegetation index is recorded, or the preceding month(s). This approach, referred to as monthly climate approach, risks underestimating the importance of within-month vegetation index variations. This study introduces an alternative approach, the EVI-date climate approach, which considers climate data from a specified time period up to the EVI recording day. The explanatory power is investigated for temperature, precipitation, and solar radiation at a global scale. EVI-date climate generally shows stronger vegetation-climate relationships than monthly climate. The relative improvement in adjusted R<sup>2</sup> ranges from 2.86 % to 39.3 %, and it is especially significant at northern high latitude when the EVI typically varies greatly (May, June, September). Using EVI-date climate, the highest explanatory power for vegetation greenness is generally found with the overall conditions over the 30 or 60 days preceding EVI recording date for temperature and solar radiation, and the preceding 60-120 days for precipitation. Overall, using the optimal time spans of climatic conditions preceding EVI recording date improves the explanatory power by 16.3 %-22.3 % compared to the use of the preceding 30-days climate only. By better aligning climate variables with vegetation greenness, climate-vegetation interaction predictions can be improved, enhancing our insights into ecosystem changes driven by climate shifts and human impact.

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Publication Details

Journal
Environmental Research
Published
2025-03-17
DOI
https://doi.org/10.1016/j.envres.2025.121398
Citations
1
Primary Topic
Remote Sensing in Agriculture
Type
article
Field-Weighted Citation Impact
1.72

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article

Accounting for exact vegetation index recording date to enhance evaluation of time-lagged and accumulated climatic effects on global vegetation greenness

Xiangping Hu, Lan Zhang, Francesco Cherubini
1 citations
Environmental Research
Remote Sensing in Agriculture
1.72
article

Accounting for exact vegetation index recording date to enhance evaluation of time-lagged and accumulated climatic effects on global vegetation greenness

Xiangping Hu, Lan Zhang, Francesco Cherubini
article en
1 citations

Abstract

Considering time-lag and accumulation effects of climate is crucial for accurately evaluating vegetation dynamics under global climate change. Most studies investigate these mechanisms by examining the explanatory power of the overall climatic conditions of the same month of the day at which the vegetation index is recorded, or the preceding month(s). This approach, referred to as monthly climate approach, risks underestimating the importance of within-month vegetation index variations. This study introduces an alternative approach, the EVI-date climate approach, which considers climate data from a specified time period up to the EVI recording day. The explanatory power is investigated for temperature, precipitation, and solar radiation at a global scale. EVI-date climate generally shows stronger vegetation-climate relationships than monthly climate. The relative improvement in adjusted R<sup>2</sup> ranges from 2.86 % to 39.3 %, and it is especially significant at northern high latitude when the EVI typically varies greatly (May, June, September). Using EVI-date climate, the highest explanatory power for vegetation greenness is generally found with the overall conditions over the 30 or 60 days preceding EVI recording date for temperature and solar radiation, and the preceding 60-120 days for precipitation. Overall, using the optimal time spans of climatic conditions preceding EVI recording date improves the explanatory power by 16.3 %-22.3 % compared to the use of the preceding 30-days climate only. By better aligning climate variables with vegetation greenness, climate-vegetation interaction predictions can be improved, enhancing our insights into ecosystem changes driven by climate shifts and human impact.

Environmental ResearchVol. 275
Norwegian University of Science and Technology (NO)
China Scholarship Council, Norges Forskningsråd
Climate action
Openalex Percentile: Top 19%
Remote Sensing in Agriculture
1.72
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Accounting for exact vegetation index recording date to enhance evaluation of time-lagged and accumulated climatic effects on global vegetation greenness — Xiangping Hu, Lan Zhang, et al. · Environmental Research (2025) | TGRS Research Map | TGRS