Geographic vs Projected Coordinate Systems: Understanding the Difference

One of the most important decisions in any geospatial project is choosing between geographic and projected coordinate systems. Get it wrong, and your distance calculations might be off by kilometers, or your map could show Greenland larger than Africa. Let’s explore the differences and when to use each.

Geographic Coordinate Systems (GCS)

A Geographic Coordinate System uses angular units (degrees) to describe positions on Earth’s curved surface. Positions are defined by two angles measured from Earth’s center:

• Latitude: The angle north or south of the equator (−90° to +90°)
• Longitude: The angle east or west of the Prime Meridian (−180° to +180°)

Characteristics of Geographic Systems

Advantages:

• Universal applicability—works anywhere on Earth
• Direct representation of positions on Earth’s surface
• Ideal for storing raw location data
• GPS natively uses geographic coordinates (WGS84)

Limitations:

• One degree of longitude varies in distance (111 km at the equator, 0 km at the poles)
• Not suitable for direct distance or area calculations
• Difficult to visualize—degrees aren’t intuitive units

Common Geographic Coordinate Systems

System	EPSG	Description
WGS84	4326	Global standard, used by GPS
NAD83	4269	North American Datum
ETRS89	4258	European Terrestrial Reference System
GDA2020	7844	Geocentric Datum of Australia

Example: San Francisco in WGS84

Latitude: 37.7749°
Longitude: -122.4194°
EPSG: 4326

Projected Coordinate Systems (PCS)

A Projected Coordinate System uses a mathematical transformation to flatten Earth’s curved surface onto a 2D plane. Positions are defined by:

• Easting (X): Distance east from an origin point
• Northing (Y): Distance north from an origin point

The Projection Process

Think of projecting as wrapping a piece of paper around a globe, shining a light through it, and tracing the shadows. Different ways of wrapping create different projections:

1. Cylindrical: Paper wrapped as a cylinder (Mercator, UTM)
2. Conic: Paper formed as a cone (Albers, Lambert)
3. Planar/Azimuthal: Flat paper touching one point (Polar projections)

Characteristics of Projected Systems

Advantages:

• Linear units (meters, feet) enable accurate calculations
• Distance and area measurements are straightforward
• Better suited for local/regional mapping
• Easier to work with in CAD software

Limitations:

• All projections distort something: area, shape, distance, or direction
• Limited geographic extent—accuracy degrades away from the projection’s center
• Requires choosing the right projection for your area

Common Projected Coordinate Systems

System	EPSG Range	Best For
UTM	32601-32660 (N), 32701-32760 (S)	Large-scale mapping, military
State Plane	Various	US surveying, local government
Web Mercator	3857	Web maps (Google, OSM)
Lambert Conformal Conic	Various	Mid-latitude regional maps
Albers Equal Area	Various	Area-accurate continental maps

Example: San Francisco in UTM Zone 10N

Easting: 551,715 meters
Northing: 4,180,029 meters
EPSG: 32610

The Four Types of Projection Distortion

Every projection involves trade-offs. No flat map can perfectly represent our round Earth. Projections are designed to preserve specific properties:

1. Conformal (Shape-Preserving)

Examples: Mercator, UTM, State Plane

• Preserves local shapes and angles
• Useful for navigation (angles remain true)
• Distorts area, especially far from the standard parallel
• Greenland appears as large as Africa on Mercator maps

2. Equal-Area (Area-Preserving)

Examples: Albers, Mollweide, Gall-Peters

• Preserves relative areas
• Essential for density maps, land use analysis
• Distorts shapes—countries may look “squished” or stretched
• Africa shown correctly as 14 times larger than Greenland

3. Equidistant (Distance-Preserving)

Examples: Azimuthal Equidistant, Plate Carrée

• Preserves distances from one or two points
• Useful for radio/radar coverage maps
• Cannot preserve all distances simultaneously

4. Compromise

Examples: Robinson, Winkel Tripel

• Balances multiple types of distortion
• Nothing preserved perfectly, but nothing horribly distorted
• Often used for world maps in education and media

Deep Dive: Universal Transverse Mercator (UTM)

UTM deserves special attention as it’s one of the most widely used projected systems for large-scale mapping.

How UTM Works

UTM divides Earth into 60 vertical zones, each 6° of longitude wide, numbered 1-60 from west to east starting at 180°W. Each zone is further divided into northern and southern hemispheres.

Zone 10N: 126°W to 120°W, Northern Hemisphere
Zone 33S: 12°E to 18°E, Southern Hemisphere

UTM Zone Properties

• Central Meridian: Middle longitude of each zone
• False Easting: 500,000 meters added so all coordinates are positive
• False Northing: 10,000,000 meters added in southern hemisphere
• Scale Factor: 0.9996 at central meridian

Finding Your UTM Zone

Calculate your zone number from longitude:

Zone = floor((longitude + 180) / 6) + 1

Or use our Coordinate Converter to automatically determine the correct zone.

UTM Accuracy

UTM is most accurate along the central meridian and within 3° of it. Beyond that, distortion increases. For projects spanning multiple zones, consider:

• Processing each zone separately, then merging
• Using a different projection (like State Plane for local work)
• Using a geographic CRS for storage, projecting only for analysis

When to Use Each Type

Use Geographic Coordinates When:

Scenario	Reason
Storing raw GPS data	Native format, maximum precision
Global datasets	No zone boundaries to worry about
Data exchange	Universal, widely understood
Web APIs (GeoJSON, WMS)	Standard specification requirement
Long-term archival	Stable, not tied to specific region

Use Projected Coordinates When:

Scenario	Reason
Measuring distances	Linear units give correct results
Calculating areas	Equal-area projections preserve area
Engineering/construction	CAD tools expect linear coordinates
Local mapping	Better accuracy for limited areas
Buffer/proximity analysis	Distance operations need projected CRS

Practical Comparison: Distance Calculation

Let’s calculate the distance between two points to see why projections matter:

Points:

• San Francisco: 37.7749°, -122.4194°
• Los Angeles: 34.0522°, -118.2437°

Using Geographic Coordinates (Incorrect Method)

// DON'T DO THIS
const dx = -122.4194 - (-118.2437);  // -4.1757°
const dy = 37.7749 - 34.0522;         // 3.7227°
const distance = Math.sqrt(dx*dx + dy*dy);
// Result: ~5.58 "units" — meaningless!

Using Geographic Coordinates (Correct Method - Haversine)

// Haversine formula accounts for Earth's curvature
const R = 6371; // Earth's radius in km
// ... complex spherical trigonometry ...
// Result: ~559 km

Using UTM (Simple and Accurate)

// After converting to UTM Zone 10N
const sf = { e: 551715, n: 4180029 };
const la = { e: 385885, n: 3769206 };

const distance = Math.sqrt(
  (la.e - sf.e)**2 + (la.n - sf.n)**2
);
// Result: ~441,716 meters (441 km)

Note: The UTM result differs from Haversine because UTM introduces some distortion, and the points span a significant distance. For this scale, Haversine is more accurate. UTM excels for smaller areas within a single zone.

Conversion Between Systems

Converting between geographic and projected coordinates requires understanding:

1. Source CRS: The coordinate system your data is currently in
2. Target CRS: The system you need to convert to
3. Transformation method: The mathematical approach (some transformations have multiple methods with different accuracies)

Common Conversion Paths

GPS Coordinates (WGS84 / 4326)
        ↓
    Web Map Display (Web Mercator / 3857)
        ↓
    Analysis (UTM Zone or Local Projection)

Use our GeoJSON Converter to transform entire datasets, or the Point Converter for individual coordinates.

Best Practices

1. Store in Geographic, Display/Analyze in Projected

Keep original data in WGS84 for maximum flexibility. Transform to projected systems only when needed for calculations or display.

2. Document Your CRS

Always include the EPSG code or full CRS definition with your data:

{
  "type": "FeatureCollection",
  "crs": {
    "type": "name",
    "properties": { "name": "EPSG:4326" }
  },
  "features": [...]
}

3. Match CRS to Your Use Case

Task	Recommended CRS Type
Area calculation	Equal-area projection
Navigation	Conformal projection
Distance measurement	Equidistant or UTM
World overview	Compromise projection

4. Be Aware of Zone Boundaries

When working near UTM zone boundaries (every 6° of longitude), consider:

• Which zone contains most of your data
• Whether features cross zone boundaries
• Using a custom projection for cross-zone projects

Summary

Aspect	Geographic CRS	Projected CRS
Units	Degrees	Meters/Feet
Coverage	Global	Regional
Distortion	None (represents true shape)	Always some type
Use for	Storage, exchange	Analysis, measurement
Example	WGS84 (EPSG:4326)	UTM Zone 10N (EPSG:32610)

Understanding the distinction between geographic and projected coordinate systems is fundamental to working with geospatial data. Choose the right system for your task, document your choices, and always verify coordinates align when combining datasets from different sources.

Further Reading

• Introduction to Coordinate Systems
• Understanding Geographic Coordinate Systems
• Point Coordinate Converter
• GeoJSON Coordinate Converter