phenocamr (version 1.1.5)

download_phenocam: Downloads PhenoCam time series

Description

This is a wrapper around most of all the other functions. It downloads a time series and extract relevant phenological transition dates or phenophases.

Usage

download_phenocam(
  site = "harvard$",
  veg_type = NULL,
  frequency = "3",
  roi_id = NULL,
  outlier_detection = TRUE,
  smooth = TRUE,
  contract = FALSE,
  daymet = FALSE,
  trim_daymet = TRUE,
  trim = NULL,
  phenophase = FALSE,
  out_dir = tempdir(),
  internal = FALSE
)

Value

Downloaded files in out_dir of requested time series products, as well as derived phenophase estimates based upon these time series.

Arguments

site

the site name, as mentioned on the PhenoCam web page expressed as a regular expression ("harvard$" == exact match)

veg_type

vegetation type (DB, EN, ... default = ALL)

frequency

frequency of the time series product (1, 3, "roistats")

roi_id

the id of the ROI to download (default = ALL)

outlier_detection

TRUE or FALSE, detect outliers

smooth

smooth data (logical, default is TRUE)

contract

contract 3-day data (logical, default is TRUE)

daymet

TRUE or FALSE, merges the daymet data

trim_daymet

TRUE or FALSE, trims data to match PhenoCam data

trim

year (numeric) to which to constrain the output (default = NULL)

phenophase

logical, calculate transition dates (default = FALSE)

out_dir

output directory where to store downloaded data (default = tempdir())

internal

allow for the data element to be returned to the workspace

Examples

if (FALSE) {
# download the first ROI time series for the Harvard PhenoCam site
# at an aggregation frequency of 3-days.
download_phenocam(site = "harvard$",
                  veg_type = "DB",
                  roi_id = "1000",
                  frequency = "3")
 
# read phenocam data into phenocamr data structure                  
df <- read_phenocam(file.path(tempdir(),"harvard_DB_1000_3day.csv"))
                  
}