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A state-of-the-art remote sensing vegetation phenology extraction package: phenofit

Task lists


You can install phenofit from github with:

# install.packages("remotes")


Users can through the following options to improve the performance of phenofit in multiple growing season regions:


[1] Kong, D., McVicar, T. R., Xiao, M., Zhang, Y., Peña-Arancibia, J. L., Filippa, G., Xie, Y., Gu, X. (2022). phenofit: An R package for extracting vegetation phenology from time series remote sensing. Methods in Ecology and Evolution, 13, 1508-1527.

[2] Kong, D., Zhang, Y.*, Wang, D., Chen, J., & Gu, X*. (2020). Photoperiod Explains the Asynchronization Between Vegetation Carbon Phenology and Vegetation Greenness Phenology. Journal of Geophysical Research: Biogeosciences, 125(8), e2020JG005636.

[3] Kong, D., Zhang, Y.*, Gu, X., & Wang, D. (2019). A robust method for reconstructing global MODIS EVI time series on the Google Earth Engine. ISPRS Journal of Photogrammetry and Remote Sensing, 155, 13–24.

[4] Kong, D., (2020). R package: A state-of-the-art Vegetation Phenology extraction package, phenofit version 0.3.5,

[5] Zhang, Q.*, Kong, D.*, Shi, P., Singh, V.P., Sun, P., 2018. Vegetation phenology on the Qinghai-Tibetan Plateau and its response to climate change (1982–2013). Agricultural and Forest Meteorology. 248, 408–417.


Keep in mind that this repository is released under a GPL2 license, which permits commercial use but requires that the source code (of derivatives) is always open even if hosted as a web service.