RasterFlow Overview
Learn about RasterFlow’s key features and capabilities
Get Started
Get started running RasterFlow in Wherobots.
Reference
Browse the RasterFlow API documentation
RasterFlow Datasets
Learn about built-in datasets and how to bring your own.
RasterFlow built-in models
RasterFlow includes curated, open-source models for common geospatial use cases.| Use Case | Capabilities | Example Application | Notebook |
|---|---|---|---|
| Agricultural Field Mapping | - Detect field boundaries from Sentinel-2 imagery - Segment crop fields across counties/regions - Convert raster predictions to vector geometries | Map all agricultural fields in Haskell County, Kansas using Sentinel-2 imagery and the Fields of the World model | Try it |
| Urban Infrastructure Detection | - Identify sidewalks, crosswalks, and pedestrian pathways - Generate detailed maps for urban planning - Analyze accessibility from high-resolution aerial imagery | Detect and map sidewalk networks in College Park, Maryland using 30cm NAIP imagery with the Tile2Net model | Try it |
| Canopy Height Estimation | - Predict tree canopy heights from aerial imagery - Monitor forest health and vegetation structure - Support conservation and urban forestry initiatives | Estimate tree heights across Nashua, NH using 60cm NAIP imagery with the Meta CHM v1 model | Try it |
| Rural Road Detection | - Identify roads, especially in rural environments - Map road networks to support routing and navigation - Detect road network changes to keep maps up to date | Detect roads in Maryland using 1m NAIP imagery with the ChesapeakeRSC model | Try it |
Running model inference
There are two options for running model inference in RasterFlow:- Run an end-to-end workflow that ingests the required imagery, generates a mosaic and runs the model using a pre-configured recipe. See build_and_predict_mosaic_recipe() for more details.
- Run model inference on an existing mosaic. See predict_mosaic() for more details.
Vectorization of model outputs
Convert raster predictions to vector geometries for further spatial analysis: Vectorization enables you to:- Join with other vector datasets (e.g., cadastral data, yield records)
- Calculate area statistics for each field
- Perform spatial queries in WherobotsDB
- Export to standard GIS formats for visualization
API reference
For detailed API documentation, see:- Client API Reference -
RasterflowClientmethods - Data Models Reference - Enums and configuration objects
- Model Registry Reference - Working with model registries
- Exceptions Reference - Error handling