Relative Accuracy

Relative accuracy, also known as “swath-to-swath accuracy” or “interswath consistency” is the measurement of how well overlapping areas of data collection match each other. For LiDAR datasets, although offsets may occur in any direction, we measure this in the vertical only. Relative accuracy is influenced by many factors, many of which can be modeled and corrected for. Relative accuracy statistics are highly dependent on mission specific properties, such as trajectory quality, boresight quality and software/workflow employed, and are typically an indicator of those factors.

These factors have a significant impact on relative accuracy:

  • Systemic Calibration (Lever Arms & Boresight)

  • Trajectory Quality

  • Processing software and workflow

Measuring Relative Accuracy

Phoenix LiDAR evaluates the relative accuracy of datasets during testing using a ground surface based methodology.

  1. Ground surfaces are computed on a per-flightline level using a PTD algorithm in SpatialExplorer.

    1. Using ground classified points serves to eliminate above ground objects and other unreliable areas of the point cloud.

    2. Generally this classification is performed across the entire dataset, rather than user defined regions, to reduce complexity in the routine.

    3. Default values are used for the PTD algorithm.

  2. Then each surface is compared to all ground classified points from all overlapping flightlines.

    1. Elevation values are interpolated from a TIN surface in order to perform the comparison. The differences are recorded for each flightline surface.

  3. These differences are summarized by an average signed delta-z and an average unsigned magnitude per flightline.

  4. Finally a project-wide average magnitude is stated to characterize the entire dataset.

Industry References

Data providers should always reach an agreement with end users about data quality standards and reporting specifications.

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