| download_phenocam {phenocamr} | R Documentation | 
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$",
  veg_type = NULL,
  frequency = "3",
  roi_id = NULL,
  outlier_detection = TRUE,
  smooth = TRUE,
  contract = FALSE,
  daymet = FALSE,
  trim_daymet = TRUE,
  trim = NULL,
  phenophase = FALSE,
  out_dir = tempdir(),
  internal = FALSE
)
Arguments
site | 
 the site name, as mentioned on the PhenoCam web page expressed as a regular expression ("harvard$" == 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   | 
contract | 
 contract 3-day data (logical, default is   | 
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 =   | 
phenophase | 
 logical, calculate transition dates (default =   | 
out_dir | 
 output directory where to store downloaded data (default = tempdir())  | 
internal | 
 allow for the data element to be returned to the workspace  | 
Value
Downloaded files in out_dir of requested time series products, as well as derived phenophase estimates based upon these time series.
Examples
## Not run: 
# 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"))
                  
## End(Not run)