Shannon eveness index provides information on area composition and richness ranging from 0 to 1. It is calculated considering 9 Corine Land Cover classes of numeric matrices using a moving window algorithm of 5 pixels side and dividing this result by its maximum.
collection, landscape diversity, Shannon eveness index, ADO project, ADO, cct, N/A, 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 |
WGS-84 (3035:EPSG)
Grid
mapDigital
Imagery base maps earth cover
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$load_collection(id = "ADO_factor_landscape_diversity",
spatial_extent = list(west = 4.009019,
east = 17.508127,
south = 42.884855,
north = 50.318495),
temporal_extent = list("STARTTIME", "ENDTIME"))
result = p$save_result(data = data, format="netCDF")
# download results ----
# either directly (suitable for smaller requests)
compute_result(result,
format = "netCDF",
output_file = "ADO_factor_landscape_diversity.nc",
con = con)
# or start a batch job (suitable for larger requests)
job_id = create_job(graph = result,
title = "ADO_factor_landscape_diversity",
description = "ADO_factor_landscape_diversity",
format = "netCDF")
start_job(job = job_id)
result_list = list_results(job = job_id)
download_results(job = job_id, folder = ".")
#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_landscape_diversity",spatial_extent={'west':4.009019,'east':17.508127,'south':42.884855,'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_landscape_diversity.nc",format="netCDF")
# or start a batch job (suitable for larger requests, e.g. when .download() timeouts)
job = result.create_job(title = "ADO_factor_landscape_diversity",description = "ADO_factor_landscape_diversity",out_format = "netCDF")
jobId = job.job_id
job.start_job()
jobResults = job.get_results()
jobResults.download_files('.')
Name | Description | Link | Date published | Category |
---|---|---|---|---|
openEO for ADO project | Tutorial and snippets on how to use openEO in the ADO project | Link | Sept. 15, 2021 | OpenEO |
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 |
MOOC Cubes and Clouds | Free Online Course teaching the concepts of data cubes, cloud platforms and open science in geospatial and EO. | Link | March 8, 2024 | OpenEO, STAC |