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The following notebook examples discuss how Wherobots enables organizations to: track land change over time, model exposure to environmental catastrophe, and prove compliance across large and remote footprints.

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How to use these solutions

Treat these notebooks as data engineering patterns as you evaluate Wherobots for your business or organization:

Baseline & Survey Imagery

Pull satellite and aerial imagery from STAC catalogs to establish a land baseline you can measure every later survey against.

Environmental Monitoring

Detect land-use change, deforestation, and habitat disruption across your footprint using RasterFlow computer vision models on satellite imagery.

Regulatory Compliance

Overlay operational boundaries with protected areas, water bodies, and jurisdictional zones to automate compliance checks through spatial joins.

Severe Weather Exposure

Correlate NOAA Severe Weather Data Inventory records with your operational footprint to model exposure to storms, hail, and tornado activity.

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Key Capabilities

Use RasterFlow to run change detection models on multi-temporal satellite imagery. Identify deforestation, land disturbance, and reclamation progress over time without manual inspection.

Change detection with RasterFlow

Compare imagery across dates and quantify what moved.
Estimate canopy height and vegetation density from aerial or satellite imagery to establish environmental baselines and measure recovery against them.

Estimating canopy height

Predict tree heights from aerial imagery to baseline vegetation.
Perform floodplain analysis, slope stability assessments, and proximity-to-hazard calculations by joining raster terrain data with vector asset inventories using WherobotsDB.

California coastal flood risk

Join hazard zones against parcel and asset records to quantify what is exposed.
Bring your own drone, aerial, or satellite GeoTIFFs into a RasterFlow mosaic and run your own PyTorch model over them to detect site-specific features such as tailings, wellheads, or haul roads.

Bring your own rasters

Mosaic your own GeoTIFFs into analysis-ready imagery.

Bring your own model

Run a custom PyTorch model over that imagery at scale.
Classify land cover types across large regions using ESA WorldCover or custom datasets, enabling informed decisions about where to operate and where to avoid.

Exploring ESA WorldCover

Classify land cover at 10 m resolution anywhere on earth.

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Wherobots Advantage

Get started with Wherobots

Try Wherobots with your own geospatial data in minutes.