For decades, GIS has lived in a world of its own. Specialized software. Obscure formats. A profession that, despite being critical to everything from climate modeling to logistics, has remained siloed from the rest of the data world. But that’s finally starting to change. In the latest episode of the Spatial Stack podcast, I sat […]
Most spatial workflows today are still running on a foundation of folders, flat files, and fragile scripts. You’ve probably worked with shapefiles stored in six different places, Python notebooks that quietly break when a column changes, and a dozen versions of the same dataset ending in _final_v2_edit.shp. I’ve been there. But spatial data has changed. […]
Look we can throw around a lot of terms about cloud-native and how geospatial is moving to the cloud, but none of this happens if it isn’t for cloud storage. Yes, this post is going to talk about storage. It’s one of the fundamentally more vanilla topics when discussion the cloud. When you boil it […]
The geospatial industry is evolving faster than ever: from AI-powered analytics to cloud-native infrastructures reshaping how we work with spatial data. That’s why I am excited to announce that the 2025 Geospatial Landscape is on the horizon. The response to this piece last year was amazing and I am excited to start work on the […]
If you’ve ever tried to run a spatial join on millions of features and watched your machine cry for help, it’s time to level up with Apache Sedona. In this new video, I walk through a complete hands-on tutorial for using Sedona in Python via JupyterLab. We’ll load spatial data, perform scalable spatial operations, and […]
