This issue is presented by MapHub TOP OF THE STACK Two quick datasets for mobile phone and data coverage. This data has always been hard to get your hands on but (at least for the US) I came across these shapefiles (they appear to be vectorized rasters) for LTE coverage for data and voice for the big providers: T-Mobile, AT&T, […]
I spend a lot of time talking about scaling geospatial analysis—massive datasets, remote sensing archives, distributed computation—but sometimes the best way to start is right from your laptop. In this tutorial, we’ll set up a local Apache Spark environment using Apache Sedona, a powerful extension for scalable geospatial processing. We’ll connect to remote cloud-hosted data, […]
Geospatial data can be stored and analyzed using a variety of tools, databases, query engines, and frameworks. Choosing the right tool depends on the scale of your use case, from individual exploration on a laptop to enterprise-level deployments, and each technology has a point where its benefits taper off. The good news for you is […]
TOP OF THE STACK What we need to do with COGs COGs (Cloud-Optimized GeoTIFFs) are one of the most promising tools we have for making raster data truly cloud-native. They let you stream just the pieces you need, work remotely, and plug into modern geospatial systems without downloading giant files. But after working closely with […]
Spatial joins combine data based on location instead of a common key. In a spatial join, attributes from one dataset are attached to another by evaluating how their geometries relate in space. For example, you could join a list of customer coordinates to sales territories by finding which territory polygon contains each customer point. This […]
