The Spatial Stack by Matt Forrest

From Spatial Stack

We have never had more data about our planet: petabytes of satellite imagery, aerial photos, and sensor readings collected daily. Yet, turning that massive volume of “noise” into a clear signal remains the fundamental challenge of the geospatial industry.

In this episode of the Spatial Stack, I sit down with the engineering and product minds from Wherobots: Ryan, Phil, and Len - to tear down the architecture required to handle Earth Observation data at a planetary scale. We move beyond the buzzwords to discuss the engineering “war stories” of building resilient inference pipelines.

We dive deep into why the industry is moving away from simple computer vision toward “Large Earth Models” that function like LLMs for the physical world. We also get into the weeds of the tech stack: the battle between Dask and Ray for distributed compute, why Cloud-Optimized GeoTIFFs (COGs) aren’t always the answer for inference, and how formats like Zarr are unlocking multidimensional analysis.