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RasterFlow runs computer vision and foundation models on satellite and aerial imagery at planetary scale.
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.
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.
AlphaEarth Embeddings, Zonal Statistics, and PCA
Aggregate AlphaEarth embeddings over Iowa fields and visualize them with PCA.
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.
How Agricultural Fields Change in AlphaEarth Foundations
Explore how Alpha Earth Embeddings reveal crop cycles and field change over time using RGB views, PCA, and embedding-distance analysis.
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.
Wherobots Raster Inference is GA with Support for Bring Your Own Model
We are excited to announce that Wherobots Raster Inference is now generally available! Raster Inference is a serverless, planetary-scale computer vision solution that extracts meaningful insights from aerial imagery (raster data) sources, such as satellites or drones, and puts these insights at the fingertips of data scientists and developers.
