Earth Observation Data Cubes
Material type:
ArticleLanguage: English Publication details: MDPI - Multidisciplinary Digital Publishing Institute 2020Description: 1 electronic resource (302 p.)ISBN: - books978-3-03928-093-3
- 9783039280926
- 9783039280933
- 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
Open Access star Unrestricted online access
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
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