GV

GeezerVison

The World Wide Web, restored to 800 pixels of glory.

Home|About|Gaming cabinet|Archives|How it works|Starter sites

On this site

  • Sign in
  • ActionsCI/CD and automation
  • CodespacesCloud development environments
  • All Features
  • Documentation
  • Training
  • Certifications
  • Build with Copilot
  • Customize Copilot
  • Integrations
  • Trending repos
  • GitHub Sponsors
  • Developer articles
  • Enterprises

This view

  • Original page
  • New address

GeezerVison is showing github.com — GitHub - locationtech/rasterframes: Geospatial Raster support for Spark DataFrames

BranchesTags
Open more actions menu

Latest commit

 

History

1,595 Commits
1,595 Commits

Folders and files

NameName
Last commit message
Last commit date
.github
.github
 
 
bench
bench
 
 
core/src
core/src
 
 
datasource/src
datasource/src
 
 
docs
docs
 
 
experimental
experimental
 
 
project
project
 
 
pyrasterframes
pyrasterframes
 
 
python
python
 
 
rf-notebook
rf-notebook
 
 
.gitignore
.gitignore
 
 
.jvmopts
.jvmopts
 
 
.pre-commit-config.yaml
.pre-commit-config.yaml
 
 
.sbtrc
.sbtrc
 
 
.scalafmt.conf
.scalafmt.conf
 
 
.sdkmanrc
.sdkmanrc
 
 
CODE_OF_CONDUCT.md
CODE_OF_CONDUCT.md
 
 
CONTRIBUTING.md
CONTRIBUTING.md
 
 
LICENSE
LICENSE
 
 
Makefile
Makefile
 
 
NOTICE.md
NOTICE.md
 
 
README.md
README.md
 
 
RELEASE.md
RELEASE.md
 
 
build.sbt
build.sbt
 
 
icon.png
icon.png
 
 
poetry.lock
poetry.lock
 
 
pyproject.toml
pyproject.toml
 
 

Repository files navigation

®

Join the chat at https://gitter.im/locationtech/rasterframes

RasterFrames® brings together Earth-observation (EO) data access, cloud computing, and DataFrame-based data science. The recent explosion of EO data from public and private satellite operators presents both a huge opportunity as well as a challenge to the data analysis community. It is Big Data in the truest sense, and its footprint is rapidly getting bigger.

RasterFrames provides a DataFrame-centric view over arbitrary raster data, enabling spatiotemporal queries, map algebra raster operations, and compatibility with the ecosystem of Spark ML algorithms. By using DataFrames as the core cognitive and compute data model, it is able to deliver these features in a form that is both accessible to general analysts and scalable along with the rapidly growing data footprint.

Please see the Getting Started section of the Users' Manual to start using RasterFrames.

User Resources

  • RasterFrames Users' Manual
  • RasterFrames Jupyter Notebook Docker Image
  • Gitter Channel
  • Submit an Issue

Contributing

Community contributions are always welcome. To get started, please review our contribution guidelines, code of conduct, and reach out to us on gitter so the community can help you get started!

RasterFrames is part of the LocationTech Stack.

It is written in Scala, but with Python bindings. If you wish to contribute to the development of RasterFrames, or you wish to build it from scratch, you will need sbt. Then clone the repository from GitHub.

git clone https://github.com/locationtech/rasterframes.git
cd rasterframes

To publish to your local repository:

sbt publishLocal

You can run tests with

sbt test

and integration tests

sbt it:test

The documentation may be built with

sbt makeSite

Additional, Python sepcific build instruction may be found at pyrasterframes/src/main/python/README.md

Copyright and License

RasterFrames is released under the commercial-friendly Apache 2.0 License, copyright Astraea, Inc. 2017-2021.

Commercial Support

As the sponsors and developers of RasterFrames, Astraea, Inc. is uniquely positioned to expand its capabilities. If you need additional functionality or just some architectural guidance to get your project off to the right start, we can provide a full range of consulting and development services around RasterFrames. We can be reached at [email protected].

About

Geospatial Raster support for Spark DataFrames

rasterframes.io

Topics

earth-observationgeotrellisimage-processingmachine-learningscalasparkspark-mlsparksql

Resources

Readme
Apache-2.0 license

Code of conduct

Code of conduct

Contributing

Contributing
Activity
Custom properties

Stars

256 stars

Watchers

11 watching

Forks

47 forks
Report repository

Releases

Packages

Used by

Contributors

Languages

You are visitor 01402503 — GeezerVison does not store the pages you look up.
Best viewed with Netscape Navigator 4.7 or Internet Explorer 6 at 800×600. No cookies required.