phenofit2

The second generation of phenofit cooperating with Julia.

  • 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

title

Figure 1. The flowchart of phenology extraction in phenofit.

Installation

You can install phenofit2 from github with:

# install.packages("devtools")
devtools::install_github("kongdd/phenofit2")

References


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

Acknowledgements

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.