Urban areas from a zipped Shapefile
A Shapefile arrives as a folder of files that has to be zipped before it can be sent anywhere. MapCrafter reads the zip directly, pairing the .shp geometry with the .dbf attribute table and honouring the .prj projection if one is present.
Start an editable copy with this data and your current map styling.
What to look at
- All the parts of a Shapefile set are read from one zip: .shp, .dbf and .prj.
- DBF field names are truncated to ten characters by the format itself, which is why they look abbreviated.
- If a .prj declares a projected coordinate system the geometry is reprojected to WGS84 on import.
Source columns
These fields describe the example data. CSV and Excel use first-row headers; GIS formats store geometry and feature properties. Required geometry depends on the map type.
| Column | Type | Example |
|---|---|---|
| NAME | text | Munich service area |
| POP_SERVED | number | 1420000 |
| RADIUS_KM | number | 32 |
Rebuild it with your own data
- 1
Get your Shapefile file ready
The example fields are NAME, POP_SERVED, RADIUS_KM. For CSV or Excel, put headers in the first row. GIS files carry geometry and feature properties. Prepare any grid, catchment or route geometry before import.
- 2
Drop it into the studio
MapCrafter detects the geometry, counts the features, and shows the layers it found.
- 3
Style the imported layer
Pick which column drives colour, and which drives size or width where relevant.
- 4
Pick a basemap theme
Ivory is used here. 15 other basemaps are available, including official OpenFreeMap styles. Switch using Layers & basemap.
- 5
Share or export
Publish a link, embed the map, or export a PNG at print resolution.
Questions about this example
- What file format does this service areas use?
- This example illustrates Shapefile data. The live preview uses GeoJSON geometry. MapCrafter reads Shapefile directly, along with Excel, CSV, KML, KMZ, GPX, GeoJSON, TopoJSON and zipped Shapefile. No conversion step and no desktop software.
- What columns does the source data need?
- The file used here has 3 columns: NAME, POP_SERVED, RADIUS_KM. For tabular imports, supply coordinate columns, WKT or GeoJSON geometry, or address columns for an explicit geocoding step. Polygon and line files carry their geometry separately from these attributes.
- Can I use my own data with this map type?
- Yes. Open the studio, drop in your file, and MapCrafter detects the geometry and applies a starting style. Then style the layer and choose which property drives colour, size or width. The studio can render a point heatmap, but grids, routes and catchment polygons must be prepared before import.
- Can I export or share the finished map?
- Each map can be published to a short share link, embedded in another page with an iframe, or exported as a print-resolution PNG. The cleaned-up geometry can also be exported as GeoJSON. All of that is available on the free tier.
- Where does the data in this example come from?
- Catchment polygons generated around real German city coordinates with seeded radii; attributes are synthetic.
More catchment maps examples
Gallery (314)- CSVHospital catchment areasCatchment polygons drawn around facility points. Catchments are the most common polygon a non-GIS user needs, and generating them from a radius is faster and more reproducible than tracing boundaries by hand.
- GeoJSONDelivery zones with overlapsOverlapping zones drawn at partial opacity on a dark basemap. Where two zones overlap the fill deepens, which turns a coverage map into a map of contention without adding a single extra layer.
- KMLSchool catchments across TexasLarge rural catchments with a wide radius variation, imported from KML. At this scale a fixed radius would be wrong for both a city district and a rural county, so the radius is read from the data.
Last updated 2026-10-22