Understanding Coordinate Reference Systems In Gis Projects And Layers

What are Coordinate Reference Systems and Why They Matter

A coordinate reference system (CRS) is a fundamental component of geographic information systems (GIS) that defines the coordinate system and map projection used to represent the locations and shapes of spatial features on the Earth’s surface. At its core, a CRS provides a reference framework for encoding coordinates on a map or spatial dataset, allowing GIS software to translate latitude and longitude locations into planar X,Y coordinates that can be visualized and analyzed.

The choice of CRS fundamentally impacts the visualization and analysis of spatial data in a GIS. Using an inappropriate CRS can cause positional distortions, misalignment of map layers, and inaccurate calculations and measurements. Selecting an appropriate CRS is therefore crucial for maintaining the integrity of spatial relationships and locations in a GIS project.

Defining coordinate reference systems

A CRS consists of three key components:

Table of Contents

A coordinate system that defines the origin, orientation, and grid units (e.g. meters, feet) used to encode real-world locations in X,Y coordinates
A map projection that translates the three-dimensional Earth with curving longitude and latitude lines into a two-dimensional planar surface
A datum that specifies the size and shape of the reference ellipsoid used to approximate the geoid and establish the local vertical and horizontal datums to which the project’s elevations and coordinates will refer

Common CRSs combine standardized components to create consistent systems for referencing locations across different maps and geospatial datasets. For example, the widely used WGS 84 CRS combines the WGS 84 ellipsoid, the World Geodetic System 1984 datum, and latitude/longitude coordinate system to create a shared geospatial framework.

Spatial data and map projections

The CRS used when collecting or encoding spatial data will determine how real-world features are positioned and represented geometrically within the coordinate grid of a map layer. Map projections transform the three-dimensional Earth into a two-dimensional planar surface by projecting locations from the curved surface of the Earth to locations on a flat grid. This mathematical transformation inevitably introduces some distortion of shapes, distances, directions, and areas as data is projected from a spherical Earth to a flat plane.

Choosing an appropriate projection is crucial because it determines what spatial properties and relationships are preserved accurately versus distorted. For example, conformal projections maintain accurate local angles and shapes while equal-area projections maintain proportional relationships between areas. Other projections optimize for equidistance, or minimize overall distortion within the map extent. The appropriate choice depends on the geographic extent as well as the spatial properties and relationships that are most important to preserve for analysis and visualization purposes.

The importance of selecting the right CRS

Selecting the appropriate CRS is important because it provides the reference framework for locating and analyzing spatial phenomena on the Earth’s surface within a GIS project. The CRS defines the coordinate system for encoding real-world locations into planar coordinates, establishes the projection used to render maps, and provides the geodetic datum ensuring accurate relationships between coordinate positions. If spatial data is captured or encoded using different CRSs, GIS layers will not align correctly and spatial analysis will yield invalid measurements and calculations.

Working with Different Coordinate Reference Systems

In many mapping projects, geospatial data may be compiled from multiple sources that use different CRSs. GIS software has capabilities for assigning, transforming, and aligning layers with different projections into a uniform project CRS.

Common CRSs used in GIS

Some of the most widely adopted CRSs include:

WGS 84 – A global latitude/longitude system used for GPS positioning, web mapping, and global exchange formats
NAD 83 – Adopted for many North American mapping systems compatible with WGS 84
UTM – Universal Transverse Mercator zones commonly used for more localized mapping
State plane systems – Tailored conformal projections for survey mapping within U.S. states

Setting the project CRS

GIS projects must define a singular project CRS that will be used as the reference coordinate system aligning all map layers within the map frame spatial extent. Layers added from external sources may use different CRSs but can be aligned by transforming layer geometries to the defined project CRS “on-the-fly”.

On-the-fly projection

GIS software can dynamically project vector and raster data sources “on-the-fly” from their native coordinate system into the project’s CRS to render map layers that are properly aligned. This allows combining data from different sources without needing to permanently transform the data to match the project CRS.

Transforming layer CRS

When layer alignment issues occur because of clashing CRSs, layers can be permanently transformed into the project coordinate system through geoprocessing tools. This defines new feature classes with geometries reprojected from the source to target CRS. However, transformation can degrade data accuracy so dynamic on-the-fly projection is preferred where possible.

Potential Issues and Debugging Tips

Various symptoms may indicate that spatial data layers have incompatible CRS definitions that need to be resolved.

Symptoms of CRS mismatches

Issues stemming from CRS mismatches include:

Map layers failing to align properly
Inaccurate distance, direction, and area calculations
Distorted feature and label positioning
Inability to select/query features across layers
Geoprocessing errors or unintended outputs

Tools for identifying layer CRS

GIS provides tools for reviewing and modifying the CRS definition for datasets and map layers to help diagnose conflicts:

Layer properties – Reports the assigned CRS for each map layer
Project properties – Defines the 2D and 3D project coordinate system
Project tool – Transforms or defines output CRS for analysis
Metadata – Reports original CRS and transformation history

Correcting misaligned layers

Typical steps for correcting layer alignment issues include:

Check project and individual layer CRS definitions in layer properties
Set all data sources to a shared project CRS
Use on-the-fly transformation override to test CRS alignment
Permanently transform layers to match if dynamic projection causes issues

Reprojecting data to match CRS

Occasionally, accurate analysis requires permanently transforming source data to match the project CRS using tools like:

Project tool – Creates projected output feature class
Feature Class to Feature Class – Creates copy of data in new CRS
Define Projection tool – Assigns coordinate system to dataset

Matching Map Layers to Real-World Locations

For meaningful spatial analysis, the CRS must accurately georeference map layers to precise real-world locations.

Georeferencing rasters

Georeferencing tools assign real-world coordinates to raster images based on control points overlaid on known locations:

Orthorectification – Corrects distortions in aerial imagery
Spatial adjustment- Matches raster control points to vector locations
Rubbersheeting – Stretches raster to match control points

Adjusting vector location accuracy

Survey-grade GNSS coordinates or aerial photogrammetry provide precision real-world locations for vector features. Location accuracy can be further refined by:

Snapping features to GPS-surveyed positions
Adjusting features to align with orthoimagery
Projecting data between datums using transformation methods

Custom coordinate systems

Specialized local grids can encode specific engineering structures or cadastres using a custom-defined coordinate system origin, orientation, units, and parameters.

Example Code for Common CRS Tasks

GIS platforms provide programming tools and code libraries for defining CRS parameters and executing projection tasks.

Setting default project CRS

Python example to define NAD 1983 UTM Zone 10N as the project CRS:

import arcpy
sr = arcpy.SpatialReference(26910) #UTM zone 10N 
arcpy.env.outputCoordinateSystem = sr  
arcpy.env.geographicTransformations = "NAD_1983_To_WGS_1984_5"

Transforming layer coordinate system

Project county layer from NAD 1927 State Plane to NAD 1983 UTM Zone 10N:

import arcpy

in_dataset = "counties_spcs.shp"
out_dataset = "counties_utm10.shp"
out_srs = arcpy.SpatialReference(26910) 

arcpy.Project_management(in_dataset, out_dataset, out_srs)

Creating custom coordinate systems

Define parameters for a custom State Plane zone:

import arcpy
sr = arcpy.SpatialReference(104129) # Existing SPCS zone 
sr.name = "My Custom State Plane"
sr.GCS.datumName = "D_Custom" 
sr.GCS.spheroidName = "Custom_Spheroid"
print(sr.exportToString()) # Export CRS WKT

Key Takeaways and Best Practices

Properly defining, assigning, and transforming coordinate reference systems is a key factor in maintaining the accuracy and integrity of GIS data.

Planning coordinate systems at project outset

Decide on an appropriate project CRS at the beginning matching the scale, location, and parameters of the mapping area and analytical needs.

Documenting CRS for all spatial data

Record layer coordinate reference system parameters and projection metadata in data descriptions andcatalogs.

Automating CRS assignments and transformations

Use scripts and models to parameterize and iterate CRS definitions and projection workflows for streamlined processing.