Publication Date:
2023-12-20
Description:
Satellite Earth observation (EO) data have already exceeded the petabyte scale and are increasingly freely and openly available from different data providers. This poses a number of issues in terms of volume (e.g., data volumes have increased 10
Keywords:
G1-922
;
Q1-390
;
knowledge base
;
metadata
;
Synthetic Aperture Radar
;
versioning
;
web services
;
web application
;
sustainable development goals
;
earth observations
;
FAIR principles
;
land cover classification
;
semantic enrichment
;
satellite imagery
;
imagery
;
analysis
;
information extraction
;
ARD
;
analysis ready data
;
swiss DC
;
data cube
;
Open Data Cube
;
UN 2030 Agenda for Sustainable Development
;
time-series
;
graph data
;
Digital Earth Australia
;
query store
;
open data cube
;
pyroSAR
;
R
;
earth oberservation
;
image cube
;
sentinel
;
open science
;
Sentinel
;
reproducibility
;
change
;
big EO data
;
earth observation
;
big Earth data
;
Earth Observations
;
Australia
;
geospatial standards
;
big earth data
;
visualization
;
UN System of Environmental Economic Accounting
;
interferometric coherence
;
dynamic data citation
;
intelligent semantic agents
;
data curation
;
snow cover
;
big data
;
Analysis Ready Data
;
climate change
;
topology based map algebra
;
data provenance
;
Sentinel-1
;
Sentinel-2
;
remote sensing
;
interoperability
;
image data cube
;
optical remote sensing
;
dual-polarimetric decomposition
;
GIS
;
Gran Paradiso National Park
;
data sharing
;
SAR
;
map algebra
;
Earth observation
;
Armenian DC
;
data cubes
;
Data Cube
;
data discovery
;
Earth observation data
;
persistent identifier
;
Landsat
;
GRASS GIS
;
subset
;
landsat
;
bic Book Industry Communication::R Earth sciences, geography, environment, planning::RG Geography
Language:
English
Format:
application/octet-stream
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