Skip to main content
  • Log in
  • Manage Cookies
projects.eclipse.org
Download
  • Projects
  • Working Groups
  • Members
  • Community
    • Marketplace
    • Events
    • Planet Eclipse
    • Newsletter
    • Videos
    • Blogs
  • Participate
    • Report a Bug
    • Forums
    • Mailing Lists
    • Wiki
    • IRC
    • Research
  • Eclipse IDE
    • Download
    • Learn More
    • Documentation
    • Getting Started / Support
    • How to Contribute
    • IDE and Tools
    • Newcomer Forum
  • More
      • Community

      • Marketplace
      • Events
      • Planet Eclipse
      • Newsletter
      • Videos
      • Blogs
      • Participate

      • Report a Bug
      • Forums
      • Mailing Lists
      • Wiki
      • IRC
      • Research
      • Eclipse IDE

      • Download
      • Learn More
      • Documentation
      • Getting Started / Support
      • How to Contribute
      • IDE and Tools
      • Newcomer Forum
    • Search

  1. Home
  2. Projects
  3. LocationTech
  4. LocationTech RasterFrames™
  5. Governance

LocationTech RasterFrames™

Primary tabs

  • Overview
  • Downloads
  • Who's Involved
  • Developer Resources
  • Governance(active tab)
  • Contact Us
Scope: 

LocationTech RasterFrames™ is a Scala library (with planned Python bindings) built on top of Apache Spark SQL and GeoTrellis. It also has dependencies on LocationTech's SFCurve, as well as a subset of GeoMesa. Its focus is to read and write against multiple imagery formats and stores, through the Spark SQL DataSource API, and make their contents available as columns of tiles with associated spatial metadata (such as indexes, keys, extents, projections, reference systems, etc). Conceptually, the contents of a RasterFrame is akin to the layers in a GIS application (e.g. QGIS), where each layer (or column in the data frame) represents a spectral band or other georectified, rasterized data product. Multiple RasterFrames may be spatially joined with each other, and their rows filtered, columns combined, statistically summarized, or have any number of additional map algebra-like operations applied to them. Furthermore, RasterFrames also includes interoperability with SparkML, allowing for classical machine learning algorithms to be applied to features derived from RasterFrame columns.

Reviews: 
NameDate
Creation Review2018-02-21

Project Links

  • Getting Started
  • Documentation
  • Proposal
Incubating - LocationTech RasterFrames™

Related Projects

Related Projects:

  • LocationTech
    • LocationTech GeoTrellis
    • LocationTech GeoMesa™

Project Hierarchy:

  • LocationTech
  • LocationTech RasterFrames™

Tags

Other Tags
  • Apache Spark
  • Machine Learning
  • Raster
  • DataFrame

Eclipse Foundation

  • About Us
  • Contact Us
  • Sponsor
  • Members
  • Governance
  • Code of Conduct
  • Logo and Artwork
  • Board of Directors
  • Careers

Legal

  • Privacy Policy
  • Terms of Use
  • Copyright Agent
  • Eclipse Public License
  • Legal Resources

Useful Links

  • Report a Bug
  • Documentation
  • How to Contribute
  • Mailing Lists
  • Forums
  • Marketplace

Other

  • IDE and Tools
  • Projects
  • Working Groups
  • Research@Eclipse
  • Report a Vulnerability
  • Service Status

Copyright © Eclipse Foundation. All Rights Reserved.

Back to the top