ODC Applications
Accessing the data in your Data Cube
The ODC core serves as a layer between satellite data providers and applications. A set of open source tools exist to help scientists conduct research using data managed by the ODC. Popular tools used within the community that utilizes the ODC Core as its basis include:
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Command Line Tools: A tool used by programmers/developers to interface with the ODC.
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Open Data Cube Explorer: A visual and interactive web application that lets users explore their inventory of available data.
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Open Data Cube Stats: An optimized means of defining and executing advanced analysis on ODC system. This tool is oriented towards scientists.
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Web User Interface (UI): A web application that allows developers to interactively showcase and visualize the output of algorithms.
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Jupyter Notebooks: Research documents centered around techniques in EO sciences. A notebook contains executable code detailing examples of how the data cube is used in a research setting, and therefore is an invaluable reference material for new users.
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Open Geospatial Consortium (OGC) Web Services: Adapters that can connect non-ODC applications to the ODC.

Satellite Data Providers


Command Line Tools

Web Services

ODC Explorer
Stats
Tool
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Web UI

Notebooks
Links to the GitHub repository
ODC ALGORITHMS & APPLICATIONS
The ODC supports a broad range of applications including land, water, cloud, and time series analysis:
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Mosaic Creation - A mosaic is a composite image created by combining the most appropriate pixels from a collection of source images. A common use case is to create cloud-free images for applications that are not time-dependent. There are a number of approaches.
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Spectral Products - Spectral Index algorithms calculate the relative magnitudes of wavelength components. The particular wavelength components used determine the product calculated.Common Spectral Indices include NDVI, NDBI, NDWI, and products such as Fractional Cover.
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Water Mapping - Water Observations from Space (WOfS) - WOfS is an automated water mapping algorithm created by Geoscience Australia. Surface water is detected in satellite images and for each location the number of occurrences is summed through time. The result is a percentage value of the number of times water was observed at the location.
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Land Classification and Land Change
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Cloud Statistics - Cloud statistics are valuable information for performing analyses. For example, if there are extensive clouds during a season, it may significantly impact mosaic products or index values. Users may also want a way to find dates when there are few clouds, so that they may assess land features.
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Time Series Analysis
Try the ODC Web UI on Amazon Web Services
ODC JUPYTER NOTEBOOKS
The ODC Ecosystem is growing, the following ODC Jupyter Notebook applications are available (see table below). Supporting material and guides for these notebooks can be found in our newly released Data Cube Application Library (DCAL) can be found here>>.
Visit our Data Cube
Application Library
ODC Algorithm Registry
QUESTIONS?
If you are having questions, or want to contribute, please feel free to reach us through our support channels:
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Github: https://github.com/opendatacube
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GIS Stack Exchange: https://gis.stackexchange.com/questions/tagged/open-data-cube
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Email: Mail us at info@opendatacube.org