Choosing The Right Coordinate System For Your Gis Application

Understanding Map Projections and Coordinate Systems

A coordinate system allows us to assign real-world coordinates to locations on a map. It is crucial for accurately displaying, analyzing, and integrating spatial data in a GIS application. At its core, a coordinate system consists of a map projection and a datum. The map projection translates the earth’s complex, curved surface into a flat map plane. Common projections include Mercator, Robinson, and Albers Equal Area. The datum anchors the projection to a model of the earth’s shape and defines the origin and orientation of the coordinate grid.

Understanding the differences between geographic and projected coordinate systems is key. Geographic coordinate systems (GCS) use latitude and longitude in angular units like degrees. They are global systems that can locate any point on earth. Projected systems measure in linear units like meters. They distort distances and areas but accurately represent local shapes and measurements. Most GIS analysis requires a projected coordinate system tailored to the study area.

Key Criteria for Selecting a Coordinate System

Choosing an appropriate coordinate system depends mainly on three factors: the location and extent of the study area, the required accuracy of measurements and analysis, and the coordinate systems used by the input data sources.

Area of Interest

The coordinate system should minimize distortion over the coverage area. Local and regional coordinate systems best preserve shapes, distances, directions, and areas for specific zones like countries, states, or counties. Global systems like latitude/longitude are only accurate for displaying data spanning the whole earth.

Required Accuracy

Projected systems tailor minimal distortion criteria like conformality, equal-area, or true direction to particular uses. Mapping natural landscapes may prioritize equal-area, while transportation analysis demands conformal systems that maintain accurate angles and a consistent local scale. Determine accuracy needs before selecting a datum and projection.

Data Sources

Evaluate the coordinate systems used by existing GIS data inputs. Reprojecting datasets introduces cumulative error and distortions by altering cell alignment. Converting data on-the-fly allows each layer to retain its native coordinate system during processing and display. But for analysis, having all inputs in one optimized projected system improves accuracy by minimizing transformations.

Common Coordinate Systems

Several standardized systems see widespread use across fields from surveying to GPS navigation. Understanding the most common options helps in evaluating systems for a particular GIS application.

Geographic Coordinate Systems


The World Geodetic System 1984 (WGS84) forms the standard geographic framework for GPS, mapping software, and online tile services. Its latitude/longitude degrees locate any global point while minimizing distortion across the datasets integrated within GPS technology and web mapping engines. Over 200 countries directly link their coordinate systems to the WGS84 datum.


The North American Datum 1983 (NAD83) provides an optimized geographic system for maps joining data across North America. Based on an improved model of the earth’s shape over North America, it delivers the most accuracy in Canada, the US, Mexico, Central America, and the Caribbean while integrally linking to global datasets through its connection to the WGS84 datum.

Projected Coordinate Systems

Specialized projected systems standardize measurements and minimize distortion within defined zones, unlike global geographic coordinates.


The Universal Transverse Mercator (UTM) projection divides the earth into 60 vertical zone strips, each spanning six degrees of longitude. Each UTM zone presents a conformal projection with constant scale along zones of true northing coordinates to preserve shapes and angles. Reducing distortion within these narrow zones makes UTM ideal for regions like countries or states.

State Plane

State Plane systems tailor projections, datums, and coordinate grids to the specific shape of individual U.S. states to maximize accuracy across each state. These highly-customized zones fuse multiple projection criteria to optimize for terrain details. Accuracy is improved for both states and when states join into regional systems like the New England, Great Lakes, Gulf Coast zones.

On-the-fly Projection

Displaying multiple GIS layers with different native projections often employs on-the-fly projection. Rather than altering the source data, this dynamically converts information to the target coordinate system during processing and rendering without saving altered datasets. This avoids cumulative error from reprojecting source data. But true coordinate-based analysis still requires a common system for inputs.

Setting the Coordinate System in GIS Software

Defining an appropriate coordinate system is a key first step in developing a robust GIS application. The code samples below demonstrate assigning project coordinate systems optimized for a county-level analysis area in two popular GIS platforms.

Code example for setting coordinate system in ArcGIS

# Import relevant coordinate system
import arcpy.SpatialReference as sr
srOhioSouth = sr.SpatialReference(102113) #Ohio South State Plane projection

#Define projection environment settings
arcpy.env.outputCoordinateSystem = srOhioSouth
arcpy.env.geographicTransformations = “NAD_1983_To_WGS_1984_5”

Code example for setting coordinate system in QGIS

# Lookup and assign coordinate reference system from EPSG registry
canvas_crs = QgsCoordinateReferenceSystem()
canvas_crs.createFromSrid(32121) #UTM Zone 17N


Dealing with Data in Different Coordinate Systems

In practice, geospatial datasets utilize a wide variety of tailored coordinate systems. Combining these inputs requires properly handling these differences to avoid positional distortions.

Identifying Mismatched Coordinate Systems

GIS software reports the native projection metadata for each layer including EPSG IDs identifying the coordinate system. Manual inspection reveals mismatches. Warning symbols flag layers not aligned with the project’s defined coordinate framework. Identifying mismatches prompts appropriate transformation steps.

Transformations and Conversions

Conversion permanently alters a dataset’s cell alignment from one coordinate grid to another. Transformation dynamically displays data from its native system into the target projection defined for the overall GIS application without modifying the original data source. For analysis, conversion into a common tailored projection often improves accuracy over relying solely on on-the-fly transformations during processing.

Best Practices for Coordinate System Selection

Following guiding principles helps ensure your GIS coordinate framework optimizes the display, analysis, and accuracy of geospatial data:

– Evaluate distortion and accuracy needs for the intended analytical uses over your study region
– Prioritize standardized coordinate systems fitting the coverage area
– Select localized projected systems over global geographic coordinates for spatial analysis
– Use specialized zonal systems tailored for countries, states, or grid zones like UTM
– Minimize reprojection of source datasets to avoid cumulative cell shift distortions
– Define one optimized projected system for analysis rather than relying on transformations
– Handle necessary transformations and conversions carefully according to GIS best practices

The coordinate system provides essential precision and standardization for integrating and analyzing location-based data. A projected framework customized to your study area and analytical needs will boost the accuracy and robustness of GIS applications. Evaluating your requirements, data sources, and options before selecting an appropriate system sets up GIS projects for success.

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