USA NPN National Phenology Network

Taking the Pulse of Our Planet

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Phenology Bibliography

Export 208 results:
Author Title Type [ Year(Asc)]
2018
V.Gougherty, Andrew, Stephen R Keller, Anton Kruger, Cathlyn D Stylinski, Andrew J Elmore, and Matthew C Fitzpatrick. Estimating Tree Phenology From High Frequency Tree Movement Data. Agricultural And Forest Meteorology no. Volume 263. Agricultural And Forest Meteorology (2018): 217-224. doi:10.1016/j.agrformet.2018.08.020.
Zhang, Xiaoyang, Lingling Liu, Yan Liu, Senthilnath Jayavelu, Jianmin Wang, Minkyu Moon, Geoffrey M Henebry, Mark A Friedl, and Crystal B Schaaf. Generation And Evaluation Of The Viirs Land Surface Phenology Product. Remote Sensing Of Environment no. Volume 216. Remote Sensing Of Environment (2018): 212-229. doi:10.1016/j.rse.2018.06.047.
Feldman, Richard E, Irma Žemaitė, and Abraham J Miller-Rushing. How Training Citizen Scientists Affects The Accuracy And Precision Of Phenological Data. International Journal Of Biometeorology. International Journal Of Biometeorology (2018): 1-15. doi:10.1007/s00484-018-1540-4.
Hufkens, Koen, D. Basler, T. Milliman, E. K Melaas, and Andrew D Richardson. An Integrated Phenology Modelling Framework In R. Methods In Ecology & Evolution. Methods In Ecology & Evolution (2018). doi:10.1111/2041-210X.12970.
Harrer, Laurie EF, and Taal Levi. The Primacy Of Bears As Seed Dispersers In Salmon-Bearing Ecosystems. Ecosphere no. 9(1). Ecosphere (2018). doi:e02076.10.1002/ecs2.2076.
Peng, Dailiang, Chaoyang Wu, Xiaoyang Zhang, Le Yu, Alfredo R Huete, Fumin Wang, Shezhou Luo, Xinjie Liu, and Helin Zhang. Scaling Up Spring Phenology Derived From Remote Sensing Images. Agricultural And Forest Meteorology no. 256-257. Agricultural And Forest Meteorology (2018). doi:10.1016/j.agrformet.2018.03.010.
Liang, Liang. A Spatially Explicit Modeling Analysis Of Adaptive Variation In Temperate Tree Phenology. Agricultural And Forest Meteorology no. 266-267. Agricultural And Forest Meteorology (2018): 73-86. doi:10.1016/j.agrformet.2018.12.004.
Carrillo, Carlos M, Toby Ault, and Daniel S Wilks. Spring Onset Predictability In The North American Multi‐Model Ensemble. Journal Of Geophysical Research - Atmospheres. Journal Of Geophysical Research - Atmospheres (2018). doi:10.1029/2018JD028597.
2017
Zurita-Milla, Raul, Romulo Goncalves, E. Izquierdo-Verdiguier, F.O. Ostermann, P. Soille, and P.G. Marchetti. Exploring Vegetation Phenology At Continental Scales : Linking Temperature-Based Indices And Land Surface Phenological Metrics. Proceedings Of The 2017 Conference On Big Data From Space (Bids '17), 28-30 November 2017, Toulouse, France. Proceedings Of The 2017 Conference On Big Data From Space (Bids '17), 28-30 November 2017, Toulouse, France. Toulouse, France: Ispra, 2017. https://research.utwente.nl/en/publications/exploring-vegetation-phenology-at-continental-scales-linking-temp.
Zhu, Likai, Jijun Meng, Feng Li, and Nanshan You. Predicting The Patterns Of Change In Spring Onset And False Springs In China During The Twenty-First Century. International Journal Of Biometeorology. International Journal Of Biometeorology (2017): 1-16. doi:10.1007/s00484-017-1456-4.

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