Spatial data accuracy standards

Data StandardsMedia standards(CD-ROM, tape… ISO physical and device format)Format standards(Data file components and structures; TIFF, IMG, Shapefiles…. .zip files)Spatial data accuracy standards(quality of the positional and attribute values stored in the data set)Documentation standards(how to describe spatial data's: origin/sources, transformations, manipulations,storage)

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Data StandardsMedia standards(CD-ROM, tape… ISO physical and device format)Format standards(Data file components and structures; TIFF, IMG, Shapefiles…. .zip files)Spatial data accuracy standards(quality of the positional and attribute values stored in the data set)Documentation standards(how to describe spatial data's: origin/sources, transformations,manipulations, storage)

Data AccuracyAccuracy measures how close an observation is tothe true valuePrecision refers to how repeatable a process ormeasurement may be (measure of predictable, consistency)

Data AccuracyHow close is the observation to the truth?Expressed asPercent (%)How often the value is wrong; “4% of the fields listed as rowcrops are perennial grasses”Expressed as a number or probability distribution of the sizeof an error“the average positional error is 12.4 meters for power polelocations, or more than 90 percent of the digitized geodeticmonuments are with 3.2 meters of their surveyed locations”

Data AccuracyPositional accuracy should be quantifiedProvide a physical measurement of theexpected accuracyMost often statistics used are•Mean Error•Error frequency threshold

Data AccuracyErrors due to:•How features are conceptualized•Methods of data collection and analysis•Field measurement error - instrument and observerprecision and bias, blunders•Sampling density - natural spatial variation•Interpolation error•Map derived data - map scale, digitizer precision, visualacuity, boredom factor•Data out of date Inadequate spatial data model

Sources of Erroralways contain some error- take steps to minimize errorsBellvue, Washington1936 1997

Data AccuracyMeasuring and DocumentingDepends on the problem (city property lines or state wide vegetation type)Remember “truth” may not be completely known•Must know the accuracy of our measure of the “truth”•It must be independent•It must have a higher order of measurement

Data AccuracyMeasuring and DocumentingFour main ways to measure spatial data accuracyPositional (geometric) Accuracy – Are coordinates correct?Attribute Accuracy – Are attributes correctLogical Consistency- Are there overshoots, open polygons,duplicate or missing labels, are roads in rivers, etc.Completeness – how current is the data, what was included,how are the objects identified and defined, what was theminimum mapping unit?(Understand and document these four within “Lineage” or what are the data sourcesand processing steps taken.)

NSSDA – National Standard for Spatial DataAccuracy defined in 1998Defines test statistic, methods, reporting of positionalaccuracyFive steps:•Select test points•Define independent control data set•Collect measurements from both sources•Calculate positional accuracy statistic•Report the accuracy statistic in a standardizedform included in the metadata

Welldistributedsamples

For each test pointFor all points

AccuracyAssessmentSummaryTableNote: RMSE is not the same as theaverage distance error not a typicaldistance error. It is a statistic that isuseful in determining probabilitythresholds for errorRMSE x 1.7308 = 95% threshold

No established standards for accuracy of Linear featuresOne common approach is to define a epsilon band(characterizing the uncertainty in line position)

Linear features (continued)(Another approach for straight lines:Using nodes and vertices to accessaccuracy)

Attribute errorBlundersInappropriate model - ordinal vs. continuousHow to characterize?•Sampling. Visit points, precisely measure attribute atlocation, and query database. (Need to accurately locate yourself)•Continuous variables, report mean, variance, etc., formeasurements and database values•For nominal variables, usually a proportion wrong. Can besummarized in a contingency table

Contingencyor ConfusionTable

Metadata(“Dataabout data”)Spatial_Reference_Information:Horizontal_Coordinate_System_Definition:Planar:Grid_Coordinate_System:Grid_Coordinate_System_Name: Universal Transverse MercatorUniversal_Transverse_Mercator:UTM_Zone_Number: 10-19Transverse_Mercator:Scale_Factor_at_Central_Meridian: .09996Longitude_of_Central_Meridian: -123 00 00Latitude_of_Projection_Origin: 0.0False_Easting: 500000False_Northing: 0.0Planar_Coordinate_Information:Planar_Coordinate_Encoding_Method: coordinate pairCoordinate_Representation:Abscissa_Resolution: 2.54Ordinate_Resolution: 2.54Planar_Distance_Units: metersGeodetic_Model:Horizontal_Datum_Name: North American Datum 1927Ellipsoid_Name: Clark 1866Semi-major_Axis: 6378206.4Denominator_of_Flattening_Ratio: 294.98Vertical_Coordinate_System_Definition:Altitude_System_Definition:Altitude_Datum_Name: National Geodetic Vertical Datum of 1929

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