GEOG 892
Geospatial Applications of Unmanned Aerial Systems (UAS)

Vertical Accuracy Standards for Geospatial Data

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Some of the highlights of the new ASPRS Vertical Accuracy Standards for Geospatial Data are the following:

  1. Unlimited horizontal accuracy classes: The new standard was designed to fit any vertical accuracy requirement no matter what technology, current or future, is used. Table 5 represents the new ASPRS vertical accuracy classes.
    Table 5. See link in caption for text description
    Table 5 The new ASPRS vertical accuracy classes
    Click for a text description of Table 5.
    Table 5: Absolute Accuracy
    Vertical Accuracy Class RMSENon-Vegetated (cm) NVA at 95% Confidence Level (cm) VVA at 95th Percentile (cm)
    X-cm X 1.96*X 3.00*X
    Table 5: Relative Accuracy (where applicable)
    Vertical Accuracy Class RMSENon-Vegetated (cm) NVA at 95% Confidence Level (cm) VVA at 95th Percentile (cm)
    X-cm 0.60*X 0.80*X 1.60*X
  2. The standards introduce two vertical accuracy types, those are:
    1. Non-vegetated Vertical Accuracy (NVA) for any part of the project that is not covered by vegetation.
    2. Vegetated Vertical Accuracy (VVA) for the part of the project that is partly or fully covered by vegetation.
  3. The standards introduce relative accuracy for elevation data beside the absolute accuracy.
    Table 5 lists a new accuracy term, which is the relative accuracy. It is mainly addressing the Lidar-derived elevation data.
    Table 6 lists vertical accuracy examples for digital elevation data.
    Table 6. See link in caption for text description
    Table 6 Vertical accuracy examples for digital elevation data
    Click for a text description of Table 6.
    Table 6: Absolute Accuracy
    Vertical Accuracy Class RMSEz Non-Vegetated (cm) NVA at 95% Confidence Level (cm) VVA at 95th Percentile (cm)
    1-cm 1.0 2.0 3
    2.5-cm 2.5 4.9 7.5
    5-cm 5.0 9.8 15
    10-cm 10.0 19.6 30
    15-cm 15.0 29.4 45
    20-cm 20.0 39.2 60
    33.3-cm 33.3 65.3 100
    66.7-cm 66.7 130.7 200
    100-cm 100 196.0 300
    333.3-cm 333.3 653.3 1000
    Table 6: Relative Accuracy (where applicable)
    Vertical Accuracy Class Within-Swatch Hard Surface Repeatability (Max Diff) (cm) Swath-to-Swath Non-Veg Terrain (RMSD2)(cm) Swath-to-Swath Non-Veg Terrain (Max Diff) (cm)
    1-cm 0.6 0.8 1.6
    2.5-cm 1.5 2 4
    5-cm 3 4 8
    10-cm 6 8 16
    15-cm 9 12 24
    20-cm 12 16 32
    33.3-cm 20 26.7 53.3
    66.7-cm 40 53.3 106.7
    100-cm 60 80 160
    333.3-cm 200 266.7 533.3
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  4. The standards introduce horizontal accuracy requirements for elevation data
    1. Flor Photogrammetric elevation data: the horizontal accuracy equates to the horizontal accuracy class that would apply to planimetric data or digital orthoimagery produced from the same source imagery, using the same aerial triangulation/INS solution.
    2. For Lidar elevation data: use the following formula: Lidar Horizontal Error( RMSEr )= ((GNSS positional error )2 + ( (tan( IMU error )/0.55894170) x flying altitude)2 )1/2
      Table 7 lists some horizontal accuracy values for lidar data based on the previous equation.
      Table 7 Sample horizontal accuracy values for lidar data
      Altitude (m) Positional RMSEr (cm) Altitude (m) Positional RMSEr (cm)
      500 13.1 3000 41.6
      1000 17.5 3500 48.0
      1500 23.0 4000 54.5
      2000 29.0 4500 61.1
      2500 35.2 5000 67.6
  5. The Standards Introduce a Formal Accuracy Testing Statement:
    For the first time, the new standards provide users with formal data evaluation statements to be used by the data users and data producers. The following statement is an example of the accuracy statement of an elevation dataset when it is used by data users or their consultants upon completion of the data evaluation:
    “This dataset was tested to meet ASPRS Positional Accuracy Standards for Digital Geospatial Data (2014) for a 10-cm RMSEz Vertical Accuracy Class. Actual NVA accuracy was found to be RMSEz = 4.7-cm, equating to +/- 9.2 cm at 95% confidence level. Actual VVA accuracy was found to be +/- 14.1-cm at the 95th percentile.”

    The following statement is the one produced by the data providers or producers for the same elevation dataset assuming it is the contract call for vertical accuracy class of 10-cm:
    “This data set was produced to meet ASPRS Positional Accuracy Standards for Digital Geospatial Data (2014) for a 10-cm RMSEz Vertical Accuracy Class equating to NVA =+/- 19.6 cm at 95% confidence level and VVA =+/- 30 cm at the 95th percentile.”

Best Practices in Determining Product Accuracy*

  1. Check data should not be used in calibrating the tested products:
    • Totally independent check points
  2. Check data must be more accurate than tested data:
    • 3 times more accurate
  3. Check data must be well distributed around the project area:
  4. Check data must be a valid statistical sample:
    • Minimum of 20 check points for orthos
    • Minimum of 25 check points for elevation data

* according to the ASPRS Positional Accuracy Standards for Digital Geospatial Data