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 […]
Geospatial Python has seen an explosion in adoption, with several key libraries surpassing 10 million downloads this year. As geospatial analysis becomes increasingly critical in data science, urban planning, environmental monitoring, and AI applications, understanding why these libraries are growing can provide insight into where the industry is heading. Here’s a breakdown of the most […]
Modern GIS is changing fast. If you’ve been working with QGIS, ArcGIS, or any other desktop GIS tool, you’ve probably hit some limitations—datasets getting too big, processing times slowing down, and collaboration becoming a challenge. The good news? The cloud offers a way forward. But how do you make that transition? How do you go […]
I want to set the scene that may seem odd at first, but it will help explain this post as we go along. Transport yourself back to a bustling school cafeteria at lunchtime. The room hums with chatter as students gather around their tables, each unpacking their lunch. Some have crisp apple slices and hearty […]
In a recent post (see below), I emphasized Python, SQL, and Cloud as core skills for GIS professionals today. Yes I still think these are critical skills but there is one thing I would fix about how I positioned that. Full post here However, some pointed out that I seemed to overlook the fundamentals: […]
