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  3. Big Earth Hackathon Workshop: Google Earth Engine

Big Earth Hackathon Workshop: Google Earth Engine

lumaHosted on Luma

Fetched about 15 hours ago

Friday, October 2, 2026

to Friday, October 2, 2026

Data ScienceClimate Tech
Student only
This hackathon is only open to students. Double check the event page for more information as this may mean only those from a particular university/country are eligible.

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About this hackathon

This workshop provides a practical introduction to Google Earth Engine designed for members of the Stanford research and teaching community who are new to both satellite imagery and Earth observation data. The session emphasizes foundational concepts, hands-on exploration, and concrete examples that lower the barrier to working with large-scale geospatial data. Google Earth Engine is a cloud-based geospatial processing platform that combines a multi-petabyte catalog of satellite imagery and geospatial datasets with planetary-scale analysis capabilities. It enables users to explore environmental change, map patterns, and compute statistics across large spatial and temporal extents—without the need to download or locally store massive datasets. Instructor: Stace Maples. Note: This workshop is open to Stanford University affiliates only. The Earth Engine API allows users to write custom algorithms for processing raster and vector data directly in the cloud. This workshop is geared toward participants who want to understand how satellite imagery and related datasets are structured, accessed, and analyzed using Earth Engine. The session will be hands-on and will use the Earth Engine JavaScript Code Editor throughout. Workshop Structure: Part 1: A Tiny Introduction to Remote Sensing: An accessible introduction to satellite and Earth observation imagery, including fundamentals of the data model, spectral characteristics, spatial and temporal resolution. Part 2: Working in Google Earth Engine: Practical instruction on navigating the Earth Engine interface, accessing and filtering imagery collections, creating image composites, running analyses over image stacks, computing summary statistics, generating charts, exporting analysis results. Prerequisites: No prior experience with Google Earth Engine or JavaScript is required. However, familiarity with GIS or remote sensing concepts is helpful, prior programming experience is beneficial but not required, and a willingness to learn basic programming concepts is essential. Accessing Google Earth Engine: Many Stanford affiliates already have access to Google Earth Engine through the Stanford Geospatial Center’s collaboration with the Stanford Doerr School of Sustainability. Email maples@stanford.edu to request inclusion in the Stanford Geospatial Center’s organizational Earth Engine account. Access can only be provided to users with valid Stanford.edu credentials and a fully sponsored SUNet ID. Slides: The slides used in this workshop mirror those presented during the live session and can be opened in a separate window for reference, including embedded links. Sample Scripts: After receiving confirmation of your Earth Engine account, you may import the sample script repository used in this workshop. These scripts are designed to introduce the basic mechanics of working in Google Earth Engine and can be explored and modified at your own pace.

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