The Complete Guide to GeoJSON: Format, Tools, and Best Practices

GeoJSON has become the de facto standard for representing geographic data on the web. It’s human-readable, widely supported, and perfect for web mapping applications.

What is GeoJSON?

GeoJSON is a JSON-based format for encoding geographic data structures. It can represent:

• Points (locations)
• Lines (paths, routes)
• Polygons (areas, boundaries)
• Collections of these geometries

Basic Structure

Every GeoJSON object has a type property. The most common structure is a FeatureCollection:

{
  "type": "FeatureCollection",
  "features": [
    {
      "type": "Feature",
      "geometry": {
        "type": "Point",
        "coordinates": [-122.4194, 37.7749]
      },
      "properties": {
        "name": "San Francisco",
        "population": 874961
      }
    }
  ]
}

Geometry Types

Point

A single location:

{
  "type": "Point",
  "coordinates": [-122.4194, 37.7749]
}

Coordinates are [longitude, latitude] (note: longitude comes first!).

LineString

A series of connected points:

{
  "type": "LineString",
  "coordinates": [
    [-122.4194, 37.7749],
    [-118.2437, 34.0522],
    [-117.1611, 32.7157]
  ]
}

Polygon

A closed area with an outer boundary and optional holes:

{
  "type": "Polygon",
  "coordinates": [
    [
      [-122.5, 37.8],
      [-122.3, 37.8],
      [-122.3, 37.7],
      [-122.5, 37.7],
      [-122.5, 37.8]
    ]
  ]
}

The first and last coordinates must be identical to close the polygon.

MultiPoint, MultiLineString, MultiPolygon

Collections of the basic types:

{
  "type": "MultiPolygon",
  "coordinates": [
    [[[...]]],
    [[[...]]]
  ]
}

GeometryCollection

Mixed geometry types:

{
  "type": "GeometryCollection",
  "geometries": [
    { "type": "Point", "coordinates": [0, 0] },
    { "type": "LineString", "coordinates": [[0, 0], [1, 1]] }
  ]
}

Features and Properties

Features wrap geometries and add properties:

{
  "type": "Feature",
  "id": "sf-1",
  "geometry": {
    "type": "Point",
    "coordinates": [-122.4194, 37.7749]
  },
  "properties": {
    "name": "San Francisco",
    "country": "USA",
    "timezone": "America/Los_Angeles",
    "population": 874961,
    "founded": 1776
  }
}

Properties can contain any valid JSON: strings, numbers, booleans, arrays, nested objects.

Coordinate Reference Systems

GeoJSON uses WGS84 (EPSG:4326) by default. Coordinates are:

• Longitude: -180 to 180
• Latitude: -90 to 90
• Altitude (optional): meters above WGS84 ellipsoid

{
  "type": "Point",
  "coordinates": [-122.4194, 37.7749, 100]
}

If your data is in a different CRS, convert it before creating GeoJSON. Our GeoJSON Converter can transform coordinates between systems.

Best Practices

1. Use Consistent Winding Order

For polygons, the outer ring should be counter-clockwise, holes clockwise. This follows the right-hand rule and ensures compatibility.

2. Keep Precision Reasonable

Six decimal places give ~10cm precision—more than enough for most applications:

// Good
[-122.419416, 37.774929]

// Excessive
[-122.41941642761231, 37.77492912847123]

3. Validate Your GeoJSON

Invalid GeoJSON causes silent failures. Common issues:

• Unclosed polygons
• Wrong coordinate order
• Invalid geometry types
• Missing required properties

Use our GeoJSON Viewer to validate and visualize your data.

4. Include Bounding Boxes for Large Files

Add a bbox property for faster spatial queries:

{
  "type": "FeatureCollection",
  "bbox": [-122.5, 37.7, -122.3, 37.9],
  "features": [...]
}

5. Use Feature IDs

IDs enable efficient updates and lookups:

{
  "type": "Feature",
  "id": "building-123",
  ...
}

Common Operations

Operation	Description
Parse	Convert JSON string to object
Validate	Check structure and geometry validity
Transform	Convert to different CRS
Simplify	Reduce coordinate count
Buffer	Create area around geometries
Merge	Combine multiple files

Tools and Libraries

JavaScript

• Turf.js: Comprehensive geospatial analysis
• Mapbox GL JS: Web map rendering
• Leaflet: Lightweight mapping

Python

• GeoPandas: Pandas for geospatial data
• Shapely: Geometry operations
• Fiona: File I/O

Online Tools

• GeoJSON Viewer - Visualize GeoJSON
• GeoJSON Converter - Transform coordinates
• GeoJSON to CSV - Export to spreadsheet

GeoJSON vs Other Formats

Format	Pros	Cons
GeoJSON	Human-readable, web-native	Large file sizes
Shapefile	Widely supported	Multiple files, 2GB limit
GeoPackage	SQLite-based, efficient	Less web support
KML	Google Earth support	XML verbosity
TopoJSON	Smaller files	Requires processing

Example: City Points

Here’s a complete example with multiple cities:

{
  "type": "FeatureCollection",
  "features": [
    {
      "type": "Feature",
      "geometry": {
        "type": "Point",
        "coordinates": [-0.1276, 51.5074]
      },
      "properties": {
        "name": "London",
        "country": "UK",
        "population": 8982000
      }
    },
    {
      "type": "Feature",
      "geometry": {
        "type": "Point",
        "coordinates": [2.3522, 48.8566]
      },
      "properties": {
        "name": "Paris",
        "country": "France",
        "population": 2161000
      }
    }
  ]
}

Try pasting this into our GeoJSON Viewer to see it on a map!

Conclusion

GeoJSON strikes an excellent balance between human readability and machine processability. By following these best practices, you’ll create interoperable geographic data that works across platforms and tools.