Justin Braaten is a Developer Relations Engineer at Google with 11 years of software engineering experience focused on geospatial tools and community-driven Earth observation workflows. Based in Walla Walla, Washington, he supports Google Earth Engine and the broader gee-community by building tutorials, tooling, and integrations that make complex spatial analysis more accessible. His open-source work includes authoring a time-series animation tutorial for MODIS NDVI in the earthengine-community repo and refactoring, testing, and extending the popular geemap Python package to improve mapping library compatibility. Justin blends full‑stack development, data science, and developer advocacy to turn research-grade geospatial processing into reproducible, user-friendly resources. He’s comfortable moving between JavaScript and Python and has a knack for improving code clarity and cross-service interoperability behind the scenes.
Tutorials and content created by Earth Engine users, for Earth Engine users
Role in this project:
Full-stack Developer
Contributions:141 reviews, 309 commits, 57 PRs in 3 years 6 months
Contributions summary:Justin's primary contribution centers around creating and refining a time-series animation tutorial within the Earth Engine Community repository. The initial commit introduced the tutorial, featuring JavaScript code for processing MODIS NDVI data and generating a GIF animation. Subsequent commits focused on improving code readability and maintainability through variable name changes and code formatting. The user demonstrated the ability to set up a project for data visualization.
A Python package for interactive geospatial analysis and visualization with Google Earth Engine.
Role in this project:
Data Scientist
Contributions:10 reviews, 14 PRs, 14 pushes in 5 years
Contributions summary:Justin primarily contributed to the development and testing of geospatial analysis and visualization tools within the geemap package. Their work included refactoring functions, adding tests for core functionalities, and updating existing features to enhance usability. They also focused on integrating and adapting various mapping libraries such as `xyzservices` and ensuring compatibility across different tile service providers, including custom and standard services.
pythonjupyter-notebookgoogle-earthdeck-glcolab
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