Geofence Map Tool
Draw a circle, polygon, or rectangle zone — then export GeoJSON, WKT, KML, or coordinates for Radar, Samsara, PostGIS, or any geofencing platform.
Draw a Geofence in Under 60 Seconds
Geofence planning doesn't need to happen inside your app's SDK. Draw the boundary here first — where it sits, what shape it takes, what it should cover — then export the geometry to your production geofencing platform. This separates the planning step from the implementation step, which is usually how product and engineering teams collaborate.
- 1Go to the location. Search an address, postal code, or landmark, or tap “Use my location.” The map recenters so you can draw exactly where the zone belongs.
- 2Pick a shape. Circle for a symmetric zone (a store, a stadium), Polygon to trace an arbitrary boundary corner by corner, or Rectangle for a quick box. Circle sizes to know: 500 m for a single store, 2 km for a neighborhood, 10 km for a metro trigger.
- 3Draw and refine. Tap to place the circle centre or polygon vertices, then drag the edge, the centre pin, or any vertex to fine-tune. The area, perimeter, and centre coordinates update in real time on the map.
- 4Export. Download GeoJSON for mapping platforms and SDKs, WKT for PostGIS and spatial SQL, KML for Google Earth or QGIS, copy the raw coordinates to your clipboard, or grab a PNG for docs. Every format works for both circles and polygons.
All exports use the standard WGS84 coordinate datum, which is what every major geofencing platform expects. No coordinate conversion needed.
What Is a Geofence?
A geofence is a virtual boundary around a real-world location. When a mobile device (or any GPS-equipped asset) enters, exits, or dwells inside the boundary, software triggers an event — a push notification, a database update, a workflow step, an analytics log.
Circle geofences are the most common type. They're defined by a center point (latitude and longitude) and a radius measured in meters or kilometers. Polygon geofences — which trace an arbitrary shape — are supported by most major platforms but require more work to author.
Geofences are enforced in two ways. On-device geofences live inside a mobile SDK and trigger events locally when the device crosses the boundary. Server-side geofences query the user's reported location against a stored boundary on your backend. The first is more efficient for battery; the second is more flexible for complex logic.
Geofencing is widely used in retail proximity marketing, fleet management, workforce clock-in automation, asset tracking, and compliance zones.
How Geofencing Works Under the Hood
Three things happen when a geofence triggers an event: the device determines its location, the system compares that location to the boundary, and software executes a response.
Location sources. Most geofences rely on GPS when outdoors. Indoors or in dense urban areas (where GPS signal reflects off buildings), systems fall back to Wi-Fi positioning, cellular triangulation, or Bluetooth beacons for sub-meter accuracy. Accuracy ranges from under 5 meters in ideal GPS conditions to 50+ meters in urban canyons.
Trigger types. Platforms distinguish three event types:
- Entry: fires when the device crosses the boundary into the geofence.
- Exit: fires when it crosses the boundary going out.
- Dwell: fires when the device has stayed inside the boundary for a specified time (usually 1–30 minutes).
Dwell events are the quiet workhorse of geofencing. Retail attribution, workforce clock-in, and anti-fraud systems all depend on dwell rather than raw entry, because a drive-by crossing at 80 km/h is noise, not signal.
Battery impact. Circle geofences on iOS and Android run at the OS level, which means they're battery-efficient — the radio doesn't have to poll GPS constantly. Polygon geofences, custom triggers, and high-frequency proximity queries run at the application level and drain the battery faster.
Platform limits. iOS caps apps at 20 active geofences per app. Android allows 100 per app. Most production systems get around this with dynamic geofence loading — swapping active fences based on current location — but this adds complexity.
Geofence Types: Circle vs Polygon
Most geofences are circles. They're simple to author (one point, one distance), efficient to evaluate (is this GPS coordinate inside this radius?), and supported natively by every major SDK. They work well when the triggering zone is symmetric — a store location, a stadium, a workplace.
Polygon geofences trace an arbitrary shape. They're the right choice when the boundary follows a real-world feature: a city-center district, a shopping mall's actual footprint, a warehouse perimeter, a park. Polygons take more work to author (you draw each vertex) and cost more CPU to evaluate, but they eliminate the dead zones and false positives that circles produce in irregular spaces.
This tool draws all three: switch the shape selector to Circle for symmetric zones, Polygon to trace an arbitrary boundary vertex by vertex, or Rectangle for a quick axis-aligned box. Drag any vertex to reshape a polygon after you draw it, and export the result as GeoJSON, WKT, KML, or coordinates — all of which carry polygon geometry natively.
Practical rule: start with a circle. Roughly 80% of geofencing use cases are well-served by a well-placed circle. Reach for a polygon when the circle produces obvious false triggers at the boundary or misses obvious real-world zones — then draw it right here rather than jumping to a heavier GIS editor.
Geofencing Platforms Comparison
If you've planned your geofence here, your next step is implementing it in a production platform. Below is how the major geofencing platforms compare on the dimensions that matter for most teams.
| Platform | Type | Geofence Limit | Polygon Support |
|---|---|---|---|
| Radar.io | Standalone SaaS | Unlimited (paid plans) | Yes |
| Google Geofencing API | Mobile SDK (Android) | 100 per app | Circle only (native); polygon via server |
| Apple Core Location | Mobile SDK (iOS) | 20 per app | Circle only |
| PlotProjects | Marketing platform | Plan-based | Yes |
| Braze | Customer engagement | Plan-based | Yes |
| OneSignal | Push notifications | Paid tier | Limited |
Limits and features change frequently — verify each platform's current docs before committing.
Export Formats Explained
Draw the zone once, export it in whatever format your stack speaks. Every format below works for both circle and polygon zones and uses the WGS84 datum. Because neither WKT nor KML has a native circle primitive, circles are written as a fine polygon approximation in those two; GeoJSON keeps a circle as a centre point plus a radius property.
GeoJSON — the universal standard
The format nearly every modern mapping platform and SDK ingests directly: Mapbox, Leaflet, AWS Location Service, Radar, Turf.js, and geojson.io. Coordinates are stored as [longitude, latitude] pairs. If you only learn one format, learn this one — it is the closest thing geofencing has to a lingua franca.
WKT — databases & spatial SQL
Well-Known Text is what spatial databases understand. Paste the POLYGON((…)) string straight into a PostGIS geography column, a MySQL spatial field, or a BigQuery ST_GEOGFROMTEXT call. This is the format to use when your geofence check runs as a ST_Contains query in your backend.
KML — Google Earth, QGIS, ArcGIS
Keyhole Markup Language opens directly in Google Earth and every major desktop GIS. Use it to review a zone visually, drop it into a mapping deck, or hand it to a GIS team that works in QGIS or ArcGIS.
Copy coordinates — raw lat/lng
Puts the plain latitude/longitude list on your clipboard. For a circle you get the centre plus the radius in meters; for a polygon, one lat, lng pair per line. Paste it into a spreadsheet, a config file, or straight into an SDK's geofence constructor.
PNG — docs & mocks
A snapshot of the map with your zone drawn on it, for design mocks, tickets, and documentation. Not machine-readable — use one of the formats above when you need the actual geometry.
Common Geofence Sizes and Use Cases
| Radius | Area Covered | Typical Use | Business Scenarios |
|---|---|---|---|
| 100 m | 0.03 km² | Single storefront or venue | In-store proximity offers, loyalty check-ins, foot-traffic counting |
| 500 m | 0.78 km² | City block or shopping center | Mall-level retargeting, event venue entry triggers |
| 1 km | 3.14 km² | Small neighborhood | Competitor conquesting (e.g. targeting shoppers near a rival store), hyper-local delivery zones |
| 2 km | 12.6 km² | Urban district | Walkable commute zone campaigns, university campus coverage |
| 5 km | 78.5 km² | Small city or metro core | Ride-share driver deployment zones, local news alerts |
| 10 km | 314 km² | Urban metro area | Fleet dispatch zones, regional retail attribution |
| 25 km | 1,963 km² | Metropolitan region | Sales territory boundaries, weather alerts |
| 50 km | 7,854 km² | State-level coverage | Regional distribution, franchise territory enforcement |
Accuracy, Privacy, and Platform Limitations
Honest caveats for anyone implementing geofencing in production:
Accuracy isn't uniform. Outdoor GPS typically gets you within 5–10 meters. Urban canyons and dense cities can drift to 20–50 meters. Indoor accuracy without Wi-Fi positioning is unreliable — often 50 meters or worse. Plan your geofence boundary with the worst-case drift in mind, or you'll get false triggers at the edges.
Small geofences are noisy. Radii under 100 meters frequently produce false positives (users triggered who weren't actually in the zone) and false negatives (users missed who were). For critical use cases — compliance, payments, clock-in — use 200 meters minimum and supplement with secondary signals.
Privacy regulations apply. In the EU, geofencing that stores or transmits user location data falls under GDPR. In California, CCPA applies. In both jurisdictions, you need explicit consent, a data retention policy, and a way for users to opt out. Platform SDKs handle the mechanics, but the policy and consent UI are your responsibility.
Platform limits bite at scale. iOS allows 20 geofences per app — hard limit. Android allows 100. Production apps that need more use dynamic geofence loading: activate the 20 closest to the user, swap them as the user moves. This is non-trivial to implement.
Frequently Asked Questions
How do I create a geofence on the map?
How do I export a geofence as GeoJSON, WKT, or coordinates?
What's the difference between a geofence and a radius map?
Can I draw polygon geofences here, or only circles?
Which export format should I use for my platform?
How accurate is the planning here vs. what my platform will enforce?
Does this tool send my geofence data anywhere?
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