> ## Documentation Index
> Fetch the complete documentation index at: https://docs.wherobots.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Examples

> Find a notebook for loading data, spatial queries, raster processing, or statistics.

Choose an example by the result you want to produce. Each page includes the notebook code and instructions for running it in Wherobots Cloud.

## Start here

Work through these four notebooks in order to learn the core workflow.

1. **[Load and query spatial data](/tutorials/example-notebooks/part-1-loading-data)** — Combine NYC buildings with elevation data and map the results.
2. **[Read spatial files](/tutorials/example-notebooks/part-2-reading-spatial-files)** — Load GeoParquet, GeoJSON, CSV, and raster data.
3. **[Prepare data for faster queries](/tutorials/example-notebooks/part-3-accelerating-geospatial-datasets)** — Create managed tables and export GeoParquet with spatial metadata.
4. **[Join datasets by location](/tutorials/example-notebooks/part-4-spatial-joins)** — Count places within boundaries and find nearest neighbors.

## Find an example

<Tabs>
  <Tab title="Spatial SQL">
    | Outcome | Notebook |
    | - | - |
    | Count California parcels and property value exposure by FEMA flood zone and city. | [Coastal flood exposure](/tutorials/example-notebooks/california-coastal-flood-risk-analysis) |
    | Read spatial data and call geometry functions in Scala. | [Spatial analysis in Scala](/tutorials/example-notebooks/getting-started) |
    | Turn Overture buildings and roads into PMTiles for a map. | [Vector tile generation](/tutorials/example-notebooks/map-tile-generation) |
    | Filter TIGER railroads to Texas and generate a PMTiles archive. | [Railroad PMTiles](/tutorials/example-notebooks/pmtiles-railroad) |
  </Tab>

  <Tab title="Data sources">
    | Outcome | Notebook |
    | - | - |
    | Load GeoParquet, GeoJSON, Shapefiles, and GeoTIFF from S3. | [Spatial file formats](/tutorials/example-notebooks/loading-common-spatial-file-types) |
    | Load imagery catalog items from a STAC endpoint into a DataFrame. | [STAC reader](/tutorials/example-notebooks/stac-reader) |
    | Query and map Overture buildings, places, and transportation data. | [Overture Maps](/tutorials/example-notebooks/overture-maps) |
    | Filter NOAA hailstorm observations by date and location, then map them. | [NOAA storm data](/tutorials/example-notebooks/noaa-swdi) |
    | Read a Unity Catalog Delta table, add a distance feature, and write the results back. | [Unity Catalog ETL](/tutorials/example-notebooks/unity-catalog-delta-tables) |
  </Tab>

  <Tab title="Raster imagery">
    RasterFlow examples cover imagery preparation and model inference. See [RasterFlow requirements](/develop/rasterflow/index) before running them.

    | Outcome | Notebook |
    | - | - |
    | Build seasonal or custom-date Sentinel-2 mosaics. | [Sentinel-2 mosaics](/tutorials/example-notebooks/rasterflow-s2-mosaic) |
    | Build a mosaic from NAIP aerial imagery. | [NAIP mosaics](/tutorials/example-notebooks/rasterflow-naip-mosaic) |
    | Discover your raster inputs with STAC and build a mosaic from a tile index. | [Bring your own rasters](/tutorials/example-notebooks/rasterflow-bring-your-own-rasters-naip) |
    | Estimate canopy height from aerial imagery. | [Canopy height](/tutorials/example-notebooks/rasterflow-chm) |
    | Detect roads in aerial imagery and vectorize the predictions. | [Road detection](/tutorials/example-notebooks/rasterflow-chesapeake) |
    | Compare imagery from two dates to detect changes. | [Change detection](/tutorials/example-notebooks/rasterflow-changedetection) |
    | Detect crop fields in Sentinel-2 imagery and save field polygons. | [Field boundaries](/tutorials/example-notebooks/rasterflow-ftw) |
    | Detect sidewalks in aerial imagery and create network geometries. | [Sidewalk detection](/tutorials/example-notebooks/rasterflow-tile2net) |
    | Detect objects in aerial imagery using a text prompt. | [Text-prompted detection](/tutorials/example-notebooks/rasterflow-sam3) |
    | Export a PyTorch model and run it through RasterFlow. | [Bring your own model](/tutorials/example-notebooks/rasterflow-bring-your-own-model) |
    | Load ESA WorldCover tiles and visualize land cover. | [ESA WorldCover](/tutorials/example-notebooks/esa-worldcover) |
    | Summarize land cover around Overture building footprints in Texas. | [Zonal statistics](/tutorials/example-notebooks/zonal-stats-esaworldcover-texas) |
  </Tab>

  <Tab title="Statistics and routing">
    | Outcome | Notebook |
    | - | - |
    | Group nearby spatial points into density-based clusters. | [DBSCAN clustering](/tutorials/example-notebooks/clustering-dbscan) |
    | Identify spatial hotspots with Getis-Ord Gi\*. | [Hotspot detection](/tutorials/example-notebooks/getis-ord-gi*) |
    | Score spatial outliers using Local Outlier Factor. | [Outlier detection](/tutorials/example-notebooks/local-outlier-factor) |
    | Join each feature to its K nearest neighbors. | [Nearest-neighbor joins](/tutorials/example-notebooks/k-nearest-neighbor-join) |
    | Match vehicle GPS trajectories to OpenStreetMap roads. | [GPS map matching](/tutorials/example-notebooks/gps-map-matching) |
    | Calculate the area reachable within a driving time. | [Drive-time isochrones](/tutorials/example-notebooks/isochrones) |
  </Tab>
</Tabs>

For examples organized by a business question, [browse industry use cases](/tutorials/use-cases).


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