Spatial Data Accuracy: Precision vs. Accuracy, Standards and Need for Accuracy (Especially for GATE-Geospatial 2022)

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Discussions of location errors naturally lead to the topic of spatial data accuracy standards, which are based on the comparison between recorded locations of features and their locations on the ground or higher-accuracy data sources. As users of spatial data, we typically do not conduct the testing of location errors but rely on published standards in evaluating data accuracy. Spatial data accuracy standards have evolved as maps have changed from printed to digital format.

Difference between Precision and Accuracy

In mapped data, precision refers to placement whereas accuracy refers to classification.

Spatial Data Accuracy

Data accuracy should not be confused with data precision. Spatial data accuracy measures how close the recorded location of a spatial feature is to its ground location, whereas data precision measures how exactly the location is recorded. Distance may be measured with decimal digits or rounded off to the nearest meter or foot. Likewise, numbers can be stored in the computer as integers or floating points.

Floating-point numbers can be single precision with 7 significant digits or double precision with up 15 significant digits. The number of significant digits used in data recording expresses the precision of a recorded location.

Spatial Data Accuracy Standards

  • In the United States, the development of spatial data accuracy standard has gone through three phases. Revised and adopted in 1947, the U. S. National Map Accuracy Standard (NMAS) sets the accuracy standard for published maps such as topographic maps from the U. S. Geological Survey (USGS) (U. S. Bureau of the Budget 1947) . The standards for horizontal accuracy require that no more than 10 percent of the well-defined map points tested shall be more than 1/30 inch (0.085 centimeter) at scales larger than 1: 20,000, and 1/50 inch (0.051 centimeter) at scales of 1: 20,000 or smaller.
  • In 1990 the American Society for Photogrammetry and Remote Sensing (ASPRS) published accuracy standards for large-scale maps (American Society for Photogrammetry and Remote Sensing 1990) . The ASPRS defines the horizontal accuracy in terms of the root mean square (RMS) error, instead of fixed threshold values. The RMS error measures deviations between coordinates values on a map and coordinate values from an independent source of higher accuracy for identical points.

Understanding Aspects of Accuracy

GIS builders and users must understand:

  • Impact of data accuracy
  • Details of spatial data accuracy
  • Spatial data accuracy needs

Need for High Accuracy

  • Realistic, useable representation of data
  • For local government, facilities management, utility, and other applications
  • Large scale applications can be conducted
  • Maps and decision-making information reliable
  • Data can be aligned and easily integrated
  • Survey data and GIS data can be input directly
  • High accuracy data saves expense for many operations

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