Environmental Data Platform

UAV DataCubes

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High resolution - hyperspectral maps as part of the data time series produced by MONALISA project. 16 Hyperspectral bands and Orthomosaic and Digital Surface models

collection, UAV, Multispectral, Suface models, UAV octocopter, Land use, Land cover

CC-BY-4.0

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


2019-09-04T00:00:00Z 2019-09-04T00:00:00Z

WGS-84 (32632: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$load_collection(id = "UAV_Transparent_Reflectance_20190904", 
                                             spatial_extent = list(west = 11.799453,
                                                                                 east = 11.803874,
                                                                                 south = 46.635872,
                                                                                 north = 46.637337),
                                             temporal_extent = list("2019-09-04T00:00:00Z", "2019-09-04T00:00:00Z"))
result = p$save_result(data = data, format="netCDF")

# download results ----
# either directly (suitable for smaller requests)
compute_result(result,
                             format = "netCDF",
                             output_file = "UAV_Transparent_Reflectance_20190904.nc", 
                             con = con)

# or start a batch job (suitable for larger requests)
job_id = create_job(graph = result,
                                   title = "UAV_Transparent_Reflectance_20190904",
                                   description = "UAV_Transparent_Reflectance_20190904",
                                   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("UAV_Transparent_Reflectance_20190904",spatial_extent={'west':11.799453,'east':11.803874,'south':46.635872,'north':46.637337},temporal_extent=["2019-09-04T00:00:00Z", "2019-09-04T00:00:00Z"])

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

# download results ----
# either directly (suitable for smaller requests, closes the connection after 2 minutes)
result.download("UAV_Transparent_Reflectance_20190904.nc",format="netCDF")

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

job = result.create_job(title = "UAV_Transparent_Reflectance_20190904",description = "UAV_Transparent_Reflectance_20190904",out_format = "netCDF")
jobId = job.job_id
job.start_job()

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