In malinfischer/phenoTS: What the Package Does (One Line, Title Case)

knitr::opts_chunk$set(echo = FALSE)

Get started

## load and activate phenoTS package from github
devtools::install_github("malinfischer/phenoTS")
library(phenoTS)

## set directory where data files shall be saved
my_dir <- "C:/Users/.../my_folder"

## check available crops  and their abbreviations
dwd_crop_list()

download observation + meta data from DWD's ftp-server

# crop: Rotbuche (European beech), annual + immediate reporters
dwd_download(crops="FIC", start=1900, end=2019, _
             report="JMSM", dir_out=my_dir)

Data processing

## create directory to folder containing files to be processed
folder_dir <- paste0(my_dir, "/RBU") 

## process and join all files in folder
rbu_data <- dwd_process(folder_dir)

#result: processed tidyverse tibble

Note: includes several processing phenoTS functions:

• dwd_read
• dwd_add_phase_info
• dwd_add_station_info
• dwd_clean
• dwd_join_files

Data filtering

a. general filters: select one phase, define observation period, delete closed stations

# phase 4 (begin of foliation / Blattentfaltung Beginn) selected here
# = indicator for start of greening / spring
rbu_data <- dwd_filter(rbu_data, dwd_phase_id=4, _
             obs_start=1950, obs_end=2018, obs_min=25)

b. filter specific stations

# filter flexibly using dplyr package
rbu_data <- dplyr::filter(rbu_data,_
             stat_id%in%c(11162,11292,11295))

# save selected stations as shape file
dwd_stations_shp(rbu_data,my_dir)

Plotting time-series results

rbu_plot <- dwd_plot_ts(rbu_data)

knitr::include_graphics('example_scripts/result_plots/rbu_plot.png')

Plotting time-series results | two crops

rbu_fic_plot <- dwd_plot_2_ts(rbu_data,fic_data)

knitr::include_graphics('example_scripts/result_plots/rbu_fic_plot.png')

malinfischer/phenoTS documentation built on May 14, 2019, 12:56 a.m.