R/ee_download.R
ee_table_to_asset.Rd
Creates a task to export a FeatureCollection to an EE table asset.
This function is a wrapper around ee$batch$Export$table$toAsset(...)
.
ee_table_to_asset(
collection,
description = "myExportTableTask",
assetId = NULL,
overwrite = FALSE
)
The feature collection to be exported.
Human-readable name of the task.
The destination asset ID. **kwargs: Holds other keyword arguments that may have been deprecated.
Logical. If TRUE, the assetId will be overwritten if it exists.
An unstarted Task that exports the table to Earth Engine Asset.
Other vector export task creator:
ee_table_to_drive()
,
ee_table_to_gcs()
if (FALSE) {
library(rgee)
library(stars)
library(sf)
ee_users()
ee_Initialize()
# Define study area (local -> earth engine)
# Communal Reserve Amarakaeri - Peru
rlist <- list(xmin = -71.13, xmax = -70.95,ymin = -12.89, ymax = -12.73)
ROI <- c(rlist$xmin, rlist$ymin,
rlist$xmax, rlist$ymin,
rlist$xmax, rlist$ymax,
rlist$xmin, rlist$ymax,
rlist$xmin, rlist$ymin)
ee_ROI <- matrix(ROI, ncol = 2, byrow = TRUE) %>%
list() %>%
st_polygon() %>%
st_sfc() %>%
st_set_crs(4326) %>%
sf_as_ee()
amk_fc <- ee$FeatureCollection(
list(ee$Feature(ee_ROI, list(name = "Amarakaeri")))
)
assetid <- paste0(ee_get_assethome(), '/geom_Amarakaeri')
task_vector <- ee_table_to_asset(
collection = amk_fc,
overwrite = TRUE,
assetId = assetid
)
task_vector$start()
ee_monitoring(task_vector) # optional
ee_fc <- ee$FeatureCollection(assetid)
Map$centerObject(ee_fc)
Map$addLayer(ee_fc)
}