Articles | Volume 22, issue 11
https://doi.org/10.5194/bg-22-2637-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-22-2637-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Duration of vegetation green-up response to snowmelt on the Tibetan Plateau
Jingwen Ni
Key Laboratory of Geographic Information Science, Ministry of Education, East China Normal University, Shanghai 200241, China
School of Geographic Sciences, East China Normal University, Shanghai 200241, China
Key Laboratory of Spatial-temporal Big Data Analysis and Application of Natural Resources in Megacities, Ministry of Natural Resources, Shanghai 200241, China
Jin Chen
State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, China
Yao Tang
Key Laboratory of Geographic Information Science, Ministry of Education, East China Normal University, Shanghai 200241, China
School of Geographic Sciences, East China Normal University, Shanghai 200241, China
Key Laboratory of Spatial-temporal Big Data Analysis and Application of Natural Resources in Megacities, Ministry of Natural Resources, Shanghai 200241, China
Jingyi Xu
Key Laboratory of Geographic Information Science, Ministry of Education, East China Normal University, Shanghai 200241, China
School of Geographic Sciences, East China Normal University, Shanghai 200241, China
Key Laboratory of Spatial-temporal Big Data Analysis and Application of Natural Resources in Megacities, Ministry of Natural Resources, Shanghai 200241, China
Zhejiang Tiantong Forest Ecosystem National Observation and Research Station, School of Ecological and Environmental Sciences, East China Normal University, Shanghai 200241, China
Jiahui Xu
Key Laboratory of Geographic Information Science, Ministry of Education, East China Normal University, Shanghai 200241, China
School of Geographic Sciences, East China Normal University, Shanghai 200241, China
Key Laboratory of Spatial-temporal Big Data Analysis and Application of Natural Resources in Megacities, Ministry of Natural Resources, Shanghai 200241, China
Linxin Dong
Key Laboratory of Geographic Information Science, Ministry of Education, East China Normal University, Shanghai 200241, China
School of Geographic Sciences, East China Normal University, Shanghai 200241, China
Key Laboratory of Spatial-temporal Big Data Analysis and Application of Natural Resources in Megacities, Ministry of Natural Resources, Shanghai 200241, China
Qingyu Gu
Key Laboratory of Geographic Information Science, Ministry of Education, East China Normal University, Shanghai 200241, China
School of Geographic Sciences, East China Normal University, Shanghai 200241, China
Key Laboratory of Spatial-temporal Big Data Analysis and Application of Natural Resources in Megacities, Ministry of Natural Resources, Shanghai 200241, China
Bailang Yu
Key Laboratory of Geographic Information Science, Ministry of Education, East China Normal University, Shanghai 200241, China
School of Geographic Sciences, East China Normal University, Shanghai 200241, China
Key Laboratory of Spatial-temporal Big Data Analysis and Application of Natural Resources in Megacities, Ministry of Natural Resources, Shanghai 200241, China
Jianping Wu
Key Laboratory of Geographic Information Science, Ministry of Education, East China Normal University, Shanghai 200241, China
School of Geographic Sciences, East China Normal University, Shanghai 200241, China
Key Laboratory of Spatial-temporal Big Data Analysis and Application of Natural Resources in Megacities, Ministry of Natural Resources, Shanghai 200241, China
Yan Huang
CORRESPONDING AUTHOR
Key Laboratory of Geographic Information Science, Ministry of Education, East China Normal University, Shanghai 200241, China
School of Geographic Sciences, East China Normal University, Shanghai 200241, China
Key Laboratory of Spatial-temporal Big Data Analysis and Application of Natural Resources in Megacities, Ministry of Natural Resources, Shanghai 200241, China
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An extended time series (2000–2018) of NPP-VIIRS-like nighttime light (NTL) data was proposed through a cross-sensor calibration from DMSP-OLS NTL data (2000–2012) and NPP-VIIRS NTL data (2013–2018). Compared with the annual composited NPP-VIIRS NTL data, our extended NPP-VIIRS-like NTL data have a high accuracy and also show a good spatial pattern and temporal consistency. It could be a useful proxy to monitor the dynamics of urbanization for a longer time period compared to existing NTL data.
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Short summary
The effect of snowmelt on vegetation is not immediate but has a mean response lag of 38.5 d. As precipitation and snowmelt increase, the response time shortens. More complex than these factors, temperature shortens the response time in colder regions while lengthening it in warmer areas. Furthermore, vegetation in arid regions is more dependent on water than heat, and low-vegetation areas rely more on sub-snow habitats than external climatic factors.
The effect of snowmelt on vegetation is not immediate but has a mean response lag of 38.5 d. As...
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