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Download and return a SpatRaster object containing the requested dataset from ODS, cropped to an eLTER site boundary, which is obtained from the DEIMS-SDR API.


get_site_ODS(deimsid, dataset = "landcover")



A character. The DEIMS ID of the site from DEIMS-SDR website. DEIMS ID information here.


A character. The requested dataset. One of: "landcover", "clc2018", "osm_buildings", "natura2000", "ndvi_spring", "ndvi_summer", "ndvi_autumn", "ndvi_winter". Default is "landcover".


The function returns a SpatRaster object (from the terra package) of the requested dataset, cropped to the site boundaries The user should save the raster to disk, if necessary. i.e. writeRaster(ds_site, "site_dataset.tif")


Supported datasets from the ODS repository include: Landcover: Land-cover class according to the highest probability, generated by a spatiotemporal ensemble-ML model. 30 m. resolution CLC2018: Corine land cover rasterized to 100m spatial resolution and provided by Copernicus Land Monitoring Service. OSM buildings: Buildings according to OSM polygons and the Copernicus impervious build-up layer (2018), aggregated and rasterized first to 10m spatial resolution and after downsampled to 30m by spatial average. Natura2000: Protected areas rasterized from NATURA 2000 (A, B and C site categories) and OSM (IUCN Ia, IUCN Ib, IUCN 2, IUCN 3, IUCN 4, IUCN 5, IUCN 6 and others categories), first to 10m spatial resolution and after downsampled to 30m by spatial average. The overlap areas are indicated in a new category.

NDVI: NDVI time-series, derived from the Landsat quarterly temporal composites

All datasets are georeferenced to the EPSG:3035 coordinate reference system. and all except clc2018 have 30 meters resolution

The function output

NDVI for Eisenwurzen


Micha Silver, phD (2020) [email protected]

Alessandro Oggioni, phD (2020) [email protected]


 if (FALSE) {
# Landcover for Angelo Mosso
siteLandcover <- get_site_ODS(
  deimsid = "",
  dataset = "landcover"

# NDVI for Eisenwurzen
siteNDVI <- get_site_ODS(
  deimsid = "",
  dataset = "ndvi_summer"