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Blog
15 posts on Computer Vision.
Utility Vegetation Management at Scale with Earth Intelligence
We mapped the trees tall enough to reach power lines in King County, WA and Shasta County, CA, using open NAIP imagery, Meta's canopy height model and Wherobots.
Yulin Naval Base in Satellite Imagery: AI-Assisted Vessel Counts
We ran six Vantor satellite images of Yulin Naval Base on Hainan through Wherobots RasterFlow and SAM3, then measured and checked every large detection.
How Wherobots builds with NVIDIA to let AI see the physical world
The world and what happens in it is digitized by petabytes of raw and derivative spatial datasets of various data types and scales, and the potential for applying AI to it is immense. But the AI models and agents we use every day need connectivity to tools that turn this data into usable insights and relationships. Wherobots gives AI the ability operate on and understand raw physical-world data, and NVIDIA GPUs are core to it. Architecturally here’s how this works at a high level.
RasterFlow is now available in Public Preview
RasterFlow makes planetary-scale earth intelligence workflows easy and costs predictable. We are excited to announce that RasterFlow is now in Public Preview, opening up the power of planetary scale Earth Intelligence to all Wherobots Professional Edition customers! RasterFlow let’s you solve complex monitoring challenges with vision-language models or tailored models for specific use cases, without […]
How well does SAM3 detect building footprints? We asked the Wherobots Spatial AI Coding Assistant
In a recent post, we showed how easy it is to use RasterFlow and Meta’s Segment Anything 3 Model (SAM3) to detect features in the physical world. A single end-to-end pipeline built a 133 GB NAIP mosaic of Marion County, Oregon, ran SAM3 against it with text prompts spanning eight classes, and produced approximately one […]
Change Detection Using AlphaEarth Foundations (Part 2)
Change detection with AlphaEarth Foundations measures how a place changes over time directly in embedding space, without hand-built spectral indices. This post scores temporal change using leave-one-out medoid distance and robust z-scoring per pixel, then runs it at scale on RasterFlow with a Colorado demonstration. The output flags where the landscape shifted and how strongly, ready to vectorize into geometries in WherobotsDB.
Detecting Objects From Text Prompts with RasterFlow and Segment Anything 3
Exploring the capabilities of Segment Anything 3 on high-resolution Earth observation data.
How We Delivered “Fields of The World” with RasterFlow: A Planetary-Scale GeoAI Pipeline
See how we used RasterFlow to run a 100TB+ global GeoAI pipeline, from feature mosaics to predictions and vectors, with reproducible workflows.
Raster Processing at Scale: The Out-of-Database Architecture Behind WherobotsDB
Learn how WherobotsDB's out-of-database architecture processes terabyte-scale satellite imagery, elevation models, and sensor data at scale, enabling zonal statistics, raster algebra, and planetary-scale AI inference without custom infrastructure.
Introducing RasterFlow: a planetary scale inference engine for Earth Intelligence
RasterFlow takes insights and embeddings from satellite and overhead imagery datasets into Apache Iceberg tables, with ease and efficiency at any scale.
Wherobots and Taylor Geospatial Engine Bring Fields-of-the-World Models to Production Scale
Agriculture depends on timely, reliable insight into what’s happening on the ground—what’s being planted, what’s being harvested, and how fields evolve over time. The Fields of The World (FTW) project was created to support exactly this mission, by building a fully open ecosystem of labeled data, software, standards and models to create a reliable global […]
Enabling Meta’s SAM 2 model for Geospatial AI on satellite imagery
Easily perform object detection and segmentation on terabyte scale satellite and aerial imagery, on-demand, prompted by text with Raster Inference.
