Predicting spring phenology in deciduous broadleaf forests: NEON phenology forecasting community challenge
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Related Links |
Related Dataset #1 : Daymet: Daily Surface Weather Data on a 1-km Grid for North America, Version 3 Related Dataset #2 : PhenoCam Dataset v2.0: Digital Camera Imagery from the PhenoCam Network, 2000-2018 Related Dataset #3 : USA National Phenology Network Extended Spring Index Gridded Data Products Related Dataset #4 : Submitted forecasts and analysis code for "Predicting spring phenology in deciduous broadleaf forests: NEON Phenology Forecasting Community Challenge" |
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Copyright author(s). This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
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Author |
Wheeler, Kathryn Dietze, M. C. LeBauer, D. Peters, J. A. |
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UCAR/NCAR - Library |
Publication Date | 2024-02-01T00:00:00 |
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geoscientificInformation |
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Metadata Date | 2025-07-10T20:04:25.350752 |
Metadata Record Identifier | edu.ucar.opensky::articles:26897 |
Metadata Language | eng; USA |
Suggested Citation | Wheeler, Kathryn, Dietze, M. C., LeBauer, D., Peters, J. A., Richardson, A. D., Ross, A. A., Thomas, R. Q., Zhu, K., Bhat, U., Munch, S., Buzbee, R. F., Chen, M., Goldstein, B., Guo, J., Hao, D., Jones, C., Kelly-Fair, M., Liu, H., Malmborg, C., Neupane, N., Pal, D., Shirey, V., Song, Y., Steen, M., Vance, E. A., Woelmer, W. M., Wynne, J. H., Zachmann, L.. (2024). Predicting spring phenology in deciduous broadleaf forests: NEON phenology forecasting community challenge. UCAR/NCAR - Library. https://n2t.org/ark:/85065/d7251npp. Accessed 03 August 2025. |
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