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MEETING NOTES AND BACKGROUND MATERIALS

(Page Last Updated:  9/26/2013)

Existing Standard:  ASPRS Accuracy Standards for Large-Scale Maps, 1990
Existing Standard:  ASPRS Guidelines, Vertical Accuracy Reporting for Lidar Data, 2004 
FGDC Reporting Standard:  National Standard for Spatial Data Accuracy (NSSDA), 1998
Initial Draft Concept Outline for New Standard (Pecora 2011)

Summary of Comments to Date (To be published as available)

SUMMARY OF KEY ISSUES AND COMMENTS TO DATE

(Last Updated:  9/26/2013)

(This is not a comprehensive list of all issues discussed. The draft document provides detailed background information and discussion in support the assumptions made and final approaches selected therein. This discussion is only intended to provide background clarification for a few key issues that received significant discussion and debate in the course of developing the draft standard and for any additional comments that have not yet been addressed).

• Map scale, ground sample distance (GSD) and pixel size: Ground sample distance (or the distance on the ground represented by one pixel in the digital image) is used to establish accuracy thresholds for digital orthophotography. In the case of an orthophoto, the GSD, or pixel size, is a representation similar to the final published scale of the map and as such is an appropriate metric to use for establishing orthophoto accuracy thresholds. This is not true for planimetric data. In the case of planimetric data, there are numerous variables that affect the final accuracy. These include the quality of the aerotriangulation solution, the type of camera used, the method used for digitizing as well as the point spacing for collection used based on the intended final published scale of the map. As such, planimetric data accuracies cannot be directly characterized by the GSD of the source imagery. For this reason the intended map for digital viewing and/or hardcopy use was selected to characterize planimetric accuracies. The GSD that would be appropriate given current, large scale photogrammetric mapping cameras is provided for general reference only.

• NSSDA equations in relating RMSE to 95% confidence levels: The NSSDA equations that use RMSE to compute the error range at a 95% confidence level are only statistically correct under the very restrictive condition that the mean error equals zero. This condition rarely occurs. Further, the RMSE statistics are only valid for normally distributed data. However, in many common applications, empirical results indicate that if the mean error is small, and the data is normally distributed, the NSSDA equations can represent a reasonable approximation of the error range at a 95% confidence level. As the mean error increases, the approximation is less accurate and tends to overestimate the range of errors. This is not well documented in the NSSDA standard.  In addition, RMSE by itself does not fully characterize other aspects of the data set accuracies. As such, RMSE is applicable only for normally distributed data sets with all systematic errors removed.  Ensuring that the data set meets these requirements requires careful evaluation of the other statistical parameters. 

• Approach to Using RMSE in New Standard:  RMSE is used in the existing standard and is a long established, well understood and widely used parameter for estimating geospatial data accuracies for normally distributed data sets. Further, as a simple to use, single parameter threshold, RMSE appropriately characterizes the absolute accuracy of the data set (as opposed to the relative accuracy or precision about the mean). For these reasons, the new standard continues to use RMSE as the accuracy threshold for normally distributed data sets. 95% values that correlate to the NSSDA reporting standard are listed in the table as reference. Clarifying text was added to indicate the limitations of that relationship and to explain the necessity of evaluating other statistical parameters to ensure that the data set has had all systematic errors removed and meets conditions for normally distributed data. Further, for lidar accuracies in vegetated areas (which are known to be biased and not normally distributed), thresholds are based on the 95th percentile accuracies and do not use RMSE values. The current standard was intended to provide a simple to use and straight-forward threshold for the most common data sets. It does not preclude future modules or addendums that address the more complex case of data sets that do not meet these criteria.

• Modular Standard: Several comments to date have indicated that other modules may be needed. These include: Assessment of linear data; rigorous total propagated uncertainty (TPU) models for our products (as opposed to ground truthing against independent data sources); more detailed statistics that do not rely on the assumption of normally distributed data; and image quality factors (such as edge definition and other characteristics). The current standard is intended to be the base standard needed to replace the existing standard for Large Scale Maps and to meet the immediate need of better addressing current digital technologies. Additional modules should be pursued and can be added by subject matter experts in these fields as they are developed.
  

• Published data set vs. source data points: The standard is replacing the existing "map accuracy standard" and as such applies to values interpolated from the final data sets. The standard is not necessarily evaluating the system accuracy at discrete source points such as lidar returns or digitized points. Elevation accuracies are assessed as interpolated from a TIN generated from the final digital elevation model. Planimetric accuracies are measured at well-defined and readily identifiable features.
  

• Spot Elevations:  Higher accuracy spot elevation points are not specified by the new standard.  Spot elevations were primarily used on cartographic contour maps, published at a fixed map scale, to aid in the accurate interpolation of elevations at key locations between drawn or interpolated contours.  With current GIS, DTM and lidar technologies spot elevation points tied to a specific contour interval are less relevant.  The new standard uses a single accuracy threshold to specify the accuracy of elevations interpolated from the source terrain model and moves away from specifying accuracies in terms of contour intervals.
  

• More stringent that past standards:The new accuracy classes represent a more stringent standard than the existing 1990 standard as newer technologies can support the higher accuracies. The primary focus was on higher accuracies. Some comments indicated that additional classes may need to be added, or some of the higher classes may need to be relaxed to address applications where less stringent accuracies are required. How appropriate the selected thresholds are given typical applications and user needs is one of the primary things that will be evaluated and ammended as needed based on member feedback on the initial draft.