call_MODIS.Rd
Get MODIS data by date and location
call_MODIS(
var,
product,
band,
site_info,
product_dates,
outdir = NULL,
run_parallel = FALSE,
ncores = NULL,
package_method = "MODISTools",
QC_filter = FALSE,
progress = FALSE
)
the simple name of the modis dataset variable (e.g. lai)
string value for MODIS product number
string value for which measurement to extract
Bety list of site info for parsing MODIS data: list(site_id, site_name, lat, lon, time_zone)
a character vector of the start and end date of the data in YYYYJJJ
where the output file will be stored. Default is NULL and in this case only values are returned. When path is provided values are returned and written to disk.
optional method to download data paralleize. Only works if more than 1 site is needed and there are >1 CPUs available.
number of cpus to use if run_parallel is set to TRUE. If you do not know the number of CPU's available, enter NULL.
string value to inform function of which package method to use to download modis data. Either "MODISTools" or "reticulate" (optional)
Converts QC values of band and keeps only data values that are excellent or good (as described by MODIS documentation), and removes all bad values. qc_band must be supplied for this parameter to work. Default is False. Only MODISTools option.
TRUE reports the download progress bar of the dataset, FALSE omits the download progress bar. Default is TRUE. Only MODISTools option.
Requires Python3 for reticulate method option. There are a number of required python libraries. sudo -H pip install numpy suds netCDF4 json depends on the MODISTools package version 1.1.0
if (FALSE) { # \dontrun{
site_info <- list(
site_id = 1,
site_name = "test",
lat = 44,
lon = 90,
time_zone = "UTC")
test_modistools <- call_MODIS(
var = "lai",
product = "MOD15A2H",
band = "Lai_500m",
site_info = site_info,
product_dates = c("2001150", "2001365"),
outdir = NULL,
run_parallel = TRUE,
ncores = NULL,
package_method = "MODISTools",
QC_filter = TRUE,
progress = FALSE)
} # }