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Measuring Accuracy of Street Centerline Datasets Donald Cooke Founder, GDT CLEM2001 August 6-7, 2001.

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Presentation on theme: "Measuring Accuracy of Street Centerline Datasets Donald Cooke Founder, GDT CLEM2001 August 6-7, 2001."— Presentation transcript:

1 Measuring Accuracy of Street Centerline Datasets Donald Cooke Founder, GDT CLEM2001 August 6-7, 2001

2 Accuracy of Centerline Files History: NMAS History: GDT involvement NSSDA, July 1998 GDT procedure Results 3 meter accuracy

3 History, NMAS NMAS: National Map Accuracy Standard Promulgated in 1940’s Production Standard: “Build to this Spec.” Binary (pass-fail) standard Tied to scale/paper/”Gutenberg Disease” Did they ever test the quads? How?

4 History, GDT Involvement Geocoding accuracy

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6 Tampa, Florida, April 1997 Red: DGPS positions of addresses Black: Interpolated geocoded addresses Most of error budget comes from storing potential address ranges…….

7 History, GDT Involvement Geocoding accuracy GDT inherited spatial accuracy of TIGER Need to realign streets and improve accuracy Need to qualify sources for realignment Need to Q/C results of realignment operation

8 NSSDA NSSDA: “National Standard for Spatial Data Accuracy” July 1998; draft available well in advance

9 NSSDA Procedure “accuracy testing by an independent source of higher accuracy is the preferred test” Compile a test suite of coordinate measurements for well-defined points in the study area Extract corresponding points from the dataset being evaluated Statistically compare the two samples by computing RMSE and "accuracy" measures ("accuracy" = RMSE * 1.7308)

10 GDT Procedure Well-defined points: “T” or “Cross” intersections Park in center of intersection; average for 1 minute Post-processed code-phase differential ~30, and later ~45 points collected per sample Sample skewed to exclude major road intersections Sample sometimes adjusted to fall within DOQQ or 7.5 minute quad tile.

11 Sample point spacing; Deerfield Illinois

12 Results 56 areas surveyed; more in process TIGER: 16-100+ meter RMSE Dynamap aligned to DOQQ: 4-6 meter RMSE See some results...

13 Test AreaNumber TIGERDynamap of PointsRMSERMSE(meters) Sarasota, FL3926.54.3 Ann Arbor, MI2946.74.5 Deerfield, IL2927.04.2 Manchester, NH3625.54.6 Morristown, NJ4848.26.1 Greenfield, MA7021.36.0 Colma/Pacifica, CA5157.16.4 W Palm Beach, FL3844.23.0* Utility GIS Denver, CO3716.73.4 Dataset Warwick, RI3537.65.2 San Diego, CA3120.94.1

14 Check point # Error, Meters Absolute error for 29 check points, Ann Arbor, MI

15 Check point # Error, Meters Absolute error for 29 check points, Ann Arbor, MI RMSE: 46 meters RMSE of “good” pts: 20 meters; bad: 102 meters

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18 Results TIGER spatial errors are not normally distributed Large population from 1:100K DLGs Many from 1980 GBF/DIME files Some streets “cartooned” freehand Picking sample is crucial Cannot make a blanket statistical statement that describes TIGER spatial error

19 Results, continued 1:24,000 DLGs are spotty; South Carolina exp. Some (25%?) 7.5 minute quads don’t pass NMAS Impossible to test accuracy until recently 1 meter DOQs appear to be boringly reliable

20 Conclusions on NMAS vs NSSDA NSSDA is a workmanlike improvement No longer a binary test No longer tied to scale of analogue map Procedure extensible to testing GPS accuracy But still considers “map” to be a monolithic, one-time compilation to a single standard Need to carry accuracy metadata on each object

21 Census TIGER/2010 Accuracy 3-meter or better accuracy (=1.7 meter RMSE) Cannot achieve this from off-the-shelf DOQs Must use new imagery or drive DGPS Code-phase differential GPS is marginal for test suite We use carrier-phase for test points


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