Environmental Data Platform

UAV DataCubes detail

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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

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

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

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 = eurac)

# 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"
eurac = openeo.connect(euracHost).authenticate_oidc(client_id="openEO_PKCE")

# load collection - save result ----
data = eurac.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)
data.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('.')
Related docs
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EDP video tutorial Presentation of edp-platform and tutorial for data analysis and processing Link Sept. 15, 2021 OpenEO
Official OpenEO documentation and project site Official Documentation provided in the project web site for a deeper overview and introduction. Link June 10, 2021 OpenEO
OpenEO doc Documentation for OpenEO API Link June 9, 2021 OpenEO
Eurac - OpenEO openEO endpoint Link April 28, 2021 OpenEO