Environmental Data Platform

Factor presence of irrigation infrastructure

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Permanently irrigated agricultural land is based on the corine land cover 2018 (CLC) from Copernicus. It has been extracted the permanent irrigated class, which is the class 12 in the CLC raster. The output is a binary raster, whereas 1 corresponds for permanent irrigated land and 0 corresponds to not permanent irrigated land.

collection, permanent irrigated land, presence of irrigation infrastructure, ADO project, ADO, cct, N/A, Land use, Land cover

Access to data is based on a principle of full, open and free access as established by the Copernicus data and information policy Regulation (EU) No 1159/2013 of 12 July 2013.

Eurac Research - Institute for Earth Observation
bartolomeo.ventura@eurac.edu
Viale Druso, 1 / Drususallee 1, Eurac Research, Bolzano, Autonomous Province of Bolzano, 39100, Italy


WGS-84 (3035:EPSG)

Grid

mapDigital

Imagery base maps earth cover

Snippet code
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install.packages("openeo")
library(openeo)

# login ----
host = "https://openeo.eurac.edu"
con = connect(host = host)
login()

# check login ---
con$isConnected()
con$isLoggedIn()
describe_account()

# load collection - save result ----
p = processes()
data = p$load_collection(id = "ADO_factor_presence_of_irrigation_infrastructure", 
                                             spatial_extent = list(west = 4.008928,
                                                                                 east = 17.508127,
                                                                                 south = 42.885755,
                                                                                 north = 50.318495),
                                             temporal_extent = list("STARTTIME", "ENDTIME"))
result = p$save_result(data = data, format="netCDF")

# download results ----
# either directly (suitable for smaller requests)
compute_result(result,
                             format = "netCDF",
                             output_file = "ADO_factor_presence_of_irrigation_infrastructure.nc", 
                             con = con)

# or start a batch job (suitable for larger requests)
job_id = create_job(graph = result,
                                   title = "ADO_factor_presence_of_irrigation_infrastructure",
                                   description = "ADO_factor_presence_of_irrigation_infrastructure",
                                   format = "netCDF")
start_job(job = job_id)
result_list = list_results(job = job_id)
download_results(job = job_id, folder = ".")
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#pip install openeo
import openeo

# login ----
euracHost        = "https://openeo.eurac.edu"
conn = openeo.connect(euracHost).authenticate_oidc(client_id="openEO_PKCE")

# load collection - save result ----
data = conn.load_collection("ADO_factor_presence_of_irrigation_infrastructure",spatial_extent={'west':4.008928,'east':17.508127,'south':42.885755,'north':50.318495},temporal_extent=["STARTTIME", "ENDTIME"])

result = data.save_result(format="NetCDF")

# download results ----
# either directly (suitable for smaller requests, closes the connection after 2 minutes)
result.download("ADO_factor_presence_of_irrigation_infrastructure.nc",format="netCDF")

# or start a batch job (suitable for larger requests, e.g. when .download() timeouts)

job = result.create_job(title = "ADO_factor_presence_of_irrigation_infrastructure",description = "ADO_factor_presence_of_irrigation_infrastructure",out_format = "netCDF")
jobId = job.job_id
job.start_job()

jobResults = job.get_results()
jobResults.download_files('.')
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