Best Practices For Displaying Coordinate Data To Avoid Misinterpretation

Understanding Coordinate Reference Systems

A coordinate reference system (CRS) defines how latitude, longitude, and height positions are displayed on a map or model of the Earth. Defining the CRS requires setting the map projection, which represents the 3D earth surface on a 2D plane, and the datum, which models the size and shape of the earth.

Defining Map Projections and Datums

Map projections geometrically transform the earth’s 3D shape into a 2D coordinate plane. Some preserve shape, some preserve area, some preserve distance and bearing. No projection maintains all properties. The datum defines the model of earth’s size, shape, and orientation in space. Hundreds exist to best fit regions. Choosing the appropriate projection and datum for displaying coordinate data reduces distortion and misrepresentation.

Common Coordinate Reference Systems

Widely used geographic coordinate reference systems (lat/long) include WGS84 and NAD83. Common projected systems (x/y) include UTM, State Plane, and Web Mercator. Data collected in different CRS may need transformation for accurate combined analysis and display.

Displaying Latitude and Longitude Values

When displaying geographic coordinates, the common formats are degrees-minutes-seconds (DMS) and decimal degrees. Precision and units must be considered to avoid misinterpretation.

Degrees, Minutes, Seconds Format

The DMS format represents latitude and longitude with component parts for degrees, minutes, and seconds. For example, 45°30’15″N. It allows variable precision but can cause confusion when degrees, minutes, or seconds are truncated or units omitted.

Decimal Degrees Format

The decimal degrees format represents latitude and longitude with a single numeric value, maintaining decimal places for precision. For example, 45.50417. This avoids truncation issues but the appropriate display precision must still be determined.

Setting Display Precision

The level of decimal precision depends on data accuracy and intended use. Low precision coordinates like 40°N, 105°W identify regional areas. Precision to thousandths or ten-thousandths of a degree provides accuracy for local areas and features. Consistently display precision and decimal places to avoid misalignments.

Handling Coordinate Transformations

Transforming coordinates between datum-based geographic coordinate systems or to/from plane-based projected systems requires specialized algorithms to maintain data integrity and accuracy.

Transforming Between Geographic and Projected Systems

Converting data from latitude/longitude to map coordinates requires projecting it based on defined parameters. The inverse projection transforms it back. This can introduce distortions so certain projections best represent specific areas. Consistently use appropriate projections.

Managing Datum Shifts

Since datums reference different earth models, transforming between them requires calculating offsets. Small shifts along all axes maintain integrity across the dataset. Identify source and target datums, choose proper transformation methods to prevent feature misalignment.

Best Practices

Following standards and guidelines when displaying coordinates reduces interpretation issues for analysis and decision-making.

Labeling Axes and Units

Always label map axes and coordinate readouts with system, units, and precision to provide essential reference information for proper data interpretation.

Choosing Appropriate Precision

Display coordinate precision suitable to data accuracy and intended use scale. Lower precision for regional analysis, higher precision for local mapping. Standardize across organisations and applications.

Using Decimal Degrees for Web Maps

Web maps and mobile applications typically display location data in decimal degrees, avoiding DMS complexity. This provides sufficient precision for general use with efficient processing.

Transforming Coordinates to Match Data Frame

Projected coordinates inherit their CRS from the overall map frame. Transform new layered data to match or misalignments occur. Identify CRS for each dataset and perform required datum and projection shifts.

Example Code

Development languages provide functions for managing coordinate data representations, precision, transformations, and projections.

Python – Setting Display Format for Decimal Degrees

import geopy.distance

lat = 45.5045
lon = -122.6743

print(f"{lat:.4f}, {lon:.4f}")
# Prints coordinate values to 4 decimal precision 

JavaScript – Converting DMS to Decimal Degrees

function convertDMSToDD(degrees, minutes, seconds, direction) {

  let dd = degrees + minutes / 60 + seconds / (60 * 60);

  if (direction == "S" || direction == "W") {
    dd = dd * -1;
  return dd;

let lat = convertDMSToDD(45, 30, 15, "N"); 
let lon = convertDMSToDD(122, 40, 35, "W");

SQL – Transforming Geometry Between Coordinate Systems

SET geom = ST_Transform(geom,4326) 
WHERE ST_SRID(geom) = 26915; 

The above transforms all geometries in data from projection SRID 26915 to geographic WGS84.

Troubleshooting Common Issues

Despite best practices, misalignment, overlap, and shift errors still occur. This section explains common causes and solutions.

Overlapping Features After Reprojecting

Projecting data into planar coordinates can cause feature overlaps due to spatial distortions introduced. Use appropriate projection minimizing distortion for target display or analysis area.

Shift in Feature Locations from Datum Differences

Datums reference different spheroid models of earth causing shifts in transformed coordinates. Calculate and apply datum transformations based on the specific datums and regions involved when projecting between geographic systems.

Truncating Coordinate Values Causes Misalignment

Consistently maintain precision and decimal places throughout a workflow to avoid truncating coordinate values. Display complete values with standardized formatting to align map data.

Leave a Reply

Your email address will not be published. Required fields are marked *