Geospatial vs Geographic: Understanding Spatial Data in GIS

Anvita Shrivastava
12 minutes ago
3 min read

The words geospatial and geographic are often confused in GIS (Geographic Information Systems), yet they can refer to similar types of data; however, they do possess contradicting definitions. GIS Experts, GIS Developers, GIS Analysts, or anyone else who utilizes spatially related Data Needs to understand the distinction between the Two Types of Data.

This article will clarify many of the differences, similarities, and a few real-life Examples of each of the Two Concepts so that you may utilize the correct terminology when referencing each of the Two Terms and also better determine their Appropriate Use in your day-to-day GIS Projects.

What Is Spatial Data?

Before we get into geospatial versus geographic, let's begin by defining Spatial Data.

Spatial Data is basically any kind of data that describes the Position, Form, and Relationship of objects within Space. The data essentially helps to provide answers to questions such as:

What is its location?
How far/a distance from other objects?
What is nearby or intersected by?

Spatial Data can come in various formats, including:

Point Data - examples being Cities, Sensors
Line Data - examples being Roads, Rivers
Polygon/Area Data - examples being Countries, Parcels

Spatial Data can exist with or without a reference to the Earth.

What Is Geographic Data?

Geographic data refers specifically to data that has a geographic component as an explicit tie to Earth's geography.

Key Features of Geographic Data

Geographic Coordinates using Latitude and Longitude
Geographic Coordinate Systems (GCS) - Examples of GCS include WGS 84.
Representations of the Earth: Physical or Human Features

Examples of Geographic Data

GPS (latitude and longitude)
National Boundaries
Rivers, Mountains, Coastlines
Images Taken from Satellites
Administrative Boundary Lines

Any data with Earth-based coordinates is Geographic Data.

What Is Geospatial Data?

The term Geospatial Data encompasses many things; basically anything that has a geographic reference, most of which have been created, used, analyzed, or visualized with the help of GIS or GIS-related technologies.

The following are some examples of the major characteristics of Geospatial Data:

Geospatial Data is much broader than just geographic data.
Geospatial Data can be geographic, based on the Earth, or it can be abstract and not based on the Earth's geography.
The majority of Geospatial Data is managed and processed in a GIS, spatial database, or a web mapping application.

Many geospatial analyses and geospatial modeling are accomplished using Geospatial Data. Examples of Geospatial Data include:

Geographic and projected data.
Indoor mapping coordinates
3D terrain models
Raster grids and spatial index
Web mapping tiles

In short: All geographic data is geospatial, but not all geospatial data is geographic.

Geospatial vs Geographic: Key Differences

Aspect	Geographic	Geospatial
Scope	Earth-specific	Broader spatial context
Reference	Latitude & longitude	Coordinates, grids, indexes
Coordinate System	Geographic Coordinate System	Geographic or Projected
Usage	Mapping Earth features	GIS analysis, modeling, apps
Examples	GPS points, country borders	Web maps, spatial databases

Why the Distinction Matters in GIS

By understanding how geospatial data differs from geographic data, you will:

Select the best coordinate system for your use case.
Avoid errors in calculating distances and/or areas.
Build precise GIS Workflows.
Convey your message to GIS-focused developers and Professionals.
Enhance or improve your Spatial Database and Web Map.

For Example:

Your Global Datasets and GPS data will use Geographic Coordinates, while
Local Analysis and Measurement data will use Projected Geospatial Coordinates.

Geospatial Data in Modern Applications

Geospatial Data is utilized in several fields today:

Web Mapping (Leaflet, Mapbox, OpenLayers)
Navigation and GPS Systems
Environmental Modelling
Urban Planning
Remote Sensing / Satellite Imagery
Location-Based Services (LBS)

Accurately representing geospatial data requires an understanding of datums and coordinate systems to ensure reliable GIS solutions, as stated on GeoWGS84.com.