RasterFrames enables you to
in a DataFrame
Features & Benefits
As part of Eclipse Foundation LocationTech and released under the Apache 2.0 License, we are proud to support the global community of developers using RasterFrames to build unique Earth-observing data application.
Whether you prefer Python, SQL, or Scala, RasterFrames connects you to the extensive machine learning ecosystem of Apache Spark.
RasterFrames transforms EO raster and vector data into the tabular rows-and-columns structure that humans favor for analysis.
From laptops to super computers, RasterFrames scales your solution to available hardware, locally or in the cloud.
Enables Machine Learning
AI models generally like tabular data. By generating DataFrames from raster data, RasterFrames enables data science practitioners to extract insights from this data.
Community of Practice
As part of a diverse and growing user base, RasterFrames users can connect with like-minded practitioners around the world.
RasterFrames Was Built For
Build an application to process imagery using RasterFrames directly. Get support, training, and direct access to the RasterFrames development team with professional support packages.
Use RasterFrames to analyze imagery data in Python notebooks. To get started in our hosted environment, learn more about EarthAI Notebook. To get help setting up your own stack, get training or development support from the RasterFrames Team through our professional support packages.
Build image processing workflows in a no-code environment using pre-built analytic components and templated workflows. Learn more about EarthAI Workflow.
As the developers of the open-source RasterFrames library, Astraea 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. See more about our consulting engagements here.