What is GeoJSON? How geographic data powers GIS workflows

Every map tells a story, but the data behind it determines how that story comes to life. Modern mapping applications rely on file formats that move cleanly between platforms and preserve both location and descriptive details.

GeoJSON is just that type of file. Its lightweight, open format combines geographic features with their associated attributes in one easy-to-use structure. This underlying simplicity has made GeoJSON a go-to for web mapping, APIs, and location-based services.

Let’s explore what GeoJSON is, including how it works and how teams can use it to manage spatial data in GIS workflows.

What is GeoJSON?

GeoJSON is an open format for working with geographic data. Built on the JSON structure, it provides a consistent way to store and exchange location information across tools and platforms. 

A GeoJSON file organizes geographic data into features, each corresponding to a real-world object or location. Every feature has coordinates — like latitude and longitude — that define its position, along with attributes that offer additional context.

One of GeoJSON’s biggest advantages is its readability. Because it uses a straightforward, text-based structure, people and machines can easily interpret the information without needing complex conversion tools. 

What is the difference between GeoJSON and Shapefile?

GeoJSON and Shapefile are two widely used formats for storing geographic data, but they serve different needs. GIS professionals use GeoJSON for modern web applications and data sharing, and Shapefiles for desktop analysis. 

How does GeoJSON work?

Each GeoJSON file stores geometry and attributes. Geometry defines a feature’s location and shape. Attributes describe what the feature represents. Instead of separating location data from supporting information, GeoJSON combines them. This way, it’s easier for mapping applications and GIS platforms to display and analyze geographic details. 

GeoJSON geometry types

GeoJSON uses distinct geometry types for different geographic features:

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• Point: Represents a single location using one coordinate pair. Common examples of point geometry include stores, landmarks, bus stops, and weather stations.
• LineString: Connects multiple coordinate pairs to create a line. LineString is frequently used to represent roads, hiking trails, and rivers.
• Polygon: Creates an enclosed area from connected coordinates. Polygons often appear for property boundaries, lakes, parks, and service areas.
• MultiPoint: Groups several points into one geometry. A retailer might store all brick-and-mortar locations in a region with a single MultiPoint feature.
• MultiLineString: Combines independent lines into one geometry. This works well for transit routes, utility networks, and river systems with multiple segments.
• MultiPolygon: Stores polygons together. A MultiPolygon could represent a national park with separate protected areas or a city map made up of several islands.
• GeometryCollection: Pairs different geometry types into a single object. One collection could include a building (Polygon), its entrance (Point), and an access road (LineString).

Because GeoJSON supports a range of geometry types, it can model everything from individual assets to large geographic regions within the same format.

Features and FeatureCollections

Features connect geometry with the information that describes them. The geometry defines where the feature is located, while GeoJSON properties store related details like the business name or operating hours. 

A FeatureCollection groups multiple features into one GeoJSON file, with each feature maintaining its own geometry and properties. Geographic locations and their associated attributes stay linked within these features, so organizations can move data across GIS platforms, web maps, and APIs without losing the relationship between them. Here’s a quick breakdown:

Coordinate system

GeoJSON uses the WGS84 coordinate system, which is the global standard behind GPS, online maps, and many GIS platforms. Each location is defined by a coordinate pair:

• Longitude: Identifies the east-west position.
• Latitude: Identifies the north-south position.

Together, these values pinpoint a location on Earth’s surface. Since GeoJSON relies on a common coordinate system, data displays consistently across web maps and location-based applications without requiring separate coordinate destinations for everyday workflows.

Practical GeoJSON use cases

Organizations turn to GeoJSON file extensions when they need a flexible format for analyzing geographic information. Its readable structure makes it easy to move spatial data between applications and sync location and business details.

Web mapping applications

One of the most common uses of GeoJSON is powering interactive web maps. Teams use this format to display geographic features like locations, boundaries, and routes in a way that’s highly intuitive and user-friendly. Examples include:

• Interactive maps showing stores, events, or points of interest.
• Public-facing applications that help customers find locations.
• Internal dashboards that combine maps with operational data.

Mapping tools, including Mapbox and Google Maps Platform, support GeoJSON to help developers add geographic information to online applications.

APIs and data exchange

GeoJSON also helps systems exchange spatial data. APIs can transfer features and their attributes, allowing applications to share location details without separating the data that describes them. Examples include:

• Location-based services highlighting nearby places, routes, or recommendations.
• Mapping APIs that deliver geographic features to web and mobile apps.
• Geospatial applications that merge data from GIS layers and external databases.

GIS and spatial analysis

GIS professionals depend on GeoJSON files to organize and share spatial information across analysis workflows. Since each feature includes geometry and descriptive details, teams can evaluate locations while keeping important context attached. Examples include:

• Asset management for tracking infrastructure and equipment.
• Site selection for comparing potential locations and facilities.
• Spatial analysis workflows for identifying patterns and relationships.
• Geographic reporting that communicates insights through mapping.

Enterprise spatial intelligence workflows

For larger organizations, GeoJSON helps connect geographic data with planning and operations. Teams can move information between systems, combine location data with business data sets, and create maps to support collaboration. Examples include:

• Utility network management for pipelines, power grids, and service areas.
• Infrastructure planning for analyzing where to build roads and public projects.
• Retail location analytics that compare sites using customer, market, and location data.
• Environmental monitoring to reveal changes in land and natural resources.

Tools like Felt help enterprise teams incorporate GeoJSON into existing workflows by adding location-based information alongside business and infrastructure data. Teams can then create and share interactive maps that support collaboration and decision making.

Why is GeoJSON so widely used?

GeoJSON is a popular choice for working with geographic data because it’s lightweight, easy to understand, and reliable to use across web and cloud environments. By building on the familiar JSON structure, it gives developers and analysts a simple way to store, share, and work with spatial data in different environments. Benefits of GeoJSON include:

• Easy to read and edit: GeoJSON uses a human-readable structure to help teams inspect and update files more efficiently, without specialized software.
• Built for web mapping: GeoJSON fits naturally into web applications because browsers and APIs can process the format easily. It powers web maps and JavaScript applications for a number of trusted mapping platforms.
• Stores spatial and attribute data together: GeoJSON keeps a feature’s location data and descriptive details in the same structure. Shapefiles, on the other hand, store geometry and attributes in multiple files.
• Works across modern GIS workflows: GeoJSON helps organizations move geographic data among mapping platforms, cloud environments, and analytics tools. Its flexibility lets teams share data while preserving context.

Visualize and analyze GeoJSON data with Felt

GeoJSON is most valuable when teams move beyond simply viewing geographic data and use it for planning and operations. Fortunately, Felt is designed for these geospatial workflows. With native GeoJSON support, cloud-based visualization, and interactive maps and dashboards, Felt helps modern teams work with geographic data from collection to analysis. 

A typical workflow might start with importing GeoJSON into Felt, then pairing it with live data from cloud sources like Snowflake, BigQuery, Databricks, Redshift, Postgres, Amazon S3, Azure Blob Storage and Google Cloud Storage. Teams can apply consistent visualization across their maps and examine spatial relationships in detail. They can also share interactive maps and dashboards with key stakeholders.

Felt’s cloud-native architecture helps organizations manage geospatial workflows at scale, while shared workspaces, governance controls, and permissions encourage collaboration across teams. Enterprise users can directly connect to cloud data sources and even use Felt AI for faster exploration of spatial information.

Check out Felt’s pricing plans to find the right solution for building, analyzing, and sharing GeoJSON-powered maps at scale.

FAQ

What are the main challenges of GeoJSON?

GeoJSON works well with many mapping platforms but offers fewer advanced GIS capabilities than specialized data formats. It also has a limited range of coordinate systems for complex spatial analysis. For large-scale projects, organizations often combine GeoJSON with databases, cloud storage, and enterprise GIS platforms.

Can GeoJSON be integrated with cloud data platforms and warehouses?

Platforms like Felt connect with cloud data sources and support native GeoJSON ingestion, so you can visualize and analyze geographic data without manual exports or ETL processes. Felt AI also helps teams explore GeoJSON data sets and run spatial queries using natural language. 

How does GeoJSON compare to other geospatial data formats?

GeoJSON provides a lightweight, readable format for mapping and data exchange. Shapefile and GeoPackage offer broader GIS capabilities for larger data sets. Your workflow and data size can determine the right option for your use case.