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

• phenofit combine merits of TIMESAT and phenopix
• A simple and stable growing season dividing methods was proposed
• Provide a practical snow elimination method, based on Whittaker
• 7 curve fitting methods and 4 phenology extraction methods
• We add parameters boundary for every curve fitting methods according to their ecological meaning.
• optimx is used to select best optimization method for different curve fitting methods.

Task lists

• Test the performance of phenofit in multiple growing season regions (e.g. the North China Plain);
• Uncertainty analysis of curve fitting and phenological metrics;
• shiny app has been moved to phenofit.shiny;
• Complete script automatic generating module in shinyapp;
• Rcpp improve double logistics optimization efficiency by 60%;
• Support spatial analysis;
• Support annual season in curve fitting;
• flexible fine fitting input ( original time-series or smoothed time-series by rough fitting).
• Asymmetric of Threshold method

Figure 1. The flowchart of phenology extraction in phenofit.

You can install phenofit from github with:

# install.packages("devtools")
devtools::install_github("kongdd/phenofit")

[1] 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. https://doi.org/10.1029/2020JG005636

[2] 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.

[3] Kong, D., (2020). R package: A state-of-the-art Vegetation Phenology extraction package, phenofit version 0.2.6, https://doi.org/10.5281/zenodo.3605560

[4] 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). Agric. For. Meteorol. 248, 408–417. https://doi.org/10.1016/j.agrformet.2017.10.026

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.