Join us for a hands-on lab experience where you'll learn to leverage geospatial intelligence using Microsoft Planetary Computer Pro. In this session, you'll work with real-world data to analyze Phoenix school campuses, measuring land-surface temperature and vegetation coverage using satellite imagery and aerial photography. This practical lab will demonstrate how enterprise geospatial data can drive informed decision-making across various industries.
This lab is offered at the following times (PST):
- Wednesday, November 19 → 11:45 AM – 1:00 PM PST (Register)
- Thursday, November 20 → 9:00 AM – 10:15 AM PST (Register)
- Friday, November 21 → 9:00 AM – 10:15 AM PST (Register)
No prerequisites required! Just bring yourself to the lab session and we'll provide everything you need to get started.
By the end of this session, learners will be able to:
- Work with enterprise geospatial datasets through Microsoft Planetary Computer Pro
- Analyze satellite and aerial imagery to extract meaningful insights
- Compute vegetation indices (NDVI) and land-surface temperature from remote sensing data
- Scale geospatial analysis workflows using Azure Databricks
- Apply geospatial intelligence principles to real-world decision-making scenarios
- Microsoft Planetary Computer Pro
- Azure Databricks
- NAIP (National Agriculture Imagery Program) aerial imagery
- Landsat Collection 2 Level 2 thermal imagery
- Python geospatial libraries (GeoPandas, Rasterio, Xarray)
The Microsoft Learn MCP Server is a remote MCP Server that enables clients like GitHub Copilot and other AI agents to bring trusted and up-to-date information directly from Microsoft's official documentation. Get started by using the one-click button above for VSCode or access the mcp.json file included in this repo.
For more information, setup instructions for other dev clients, and to post comments and questions, visit our Learn MCP Server GitHub repo at https://github.com/MicrosoftDocs/MCP. Find other MCP Servers to connect your agent to at https://mcp.azure.com.
Note: When you use the Learn MCP Server, you agree with Microsoft Learn and Microsoft API Terms of Use.
| Resources | Links | Description |
|---|---|---|
| Microsoft Planetary Computer Pro Docs | What is Microsoft Planetary Computer Pro? | Enterprise geospatial data and analytics platform |
| Contact the Team | [email protected] | Questions about Microsoft Planetary Computer Pro? |
| Ignite 2025 Next Steps | https://aka.ms/Ignite25-Next-Steps | Links to all repos for Ignite 2025 Sessions |
| Learn at Ignite | https://aka.ms/LearnAtIgnite | Continue learning on Microsoft Learn |
 Prasad Komma 📢 |
At Ignite, a virtual environment with all prerequisites and required accounts is provided for this lab. To run this lab outside of Ignite, follow the setup instructions.
This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit Contributor License Agreements.
When you submit a pull request, a CLA bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., status check, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA.
This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact [email protected] with any additional questions or comments.
This project may contain trademarks or logos for projects, products, or services. Authorized use of Microsoft trademarks or logos is subject to and must follow Microsoft's Trademark & Brand Guidelines. Use of Microsoft trademarks or logos in modified versions of this project must not cause confusion or imply Microsoft sponsorship. Any use of third-party trademarks or logos are subject to those third-party's policies.