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![Accuracy and Precision
"Accuracy - closeness of an estimated (e.g., measured or computed)
value to a standard or accepted [true] value of a particular
quantity.”
FGDC-STD-007.1-1998
Precision - in statistics, a measure of the
tendency of a set of random numbers to cluster about a number
determined by
the set.
FGDC-STD-007.1-1998](https://image.slidesharecdn.com/au2007itsnotcadtogisfinal-12737046890394-phpapp02/75/Au-2007-It-S-Not-Cad-To-Gis-Final-8-2048.jpg)
![Accuracy and Precision
"Accuracy - closeness of an estimated (e.g., measured or computed)
value to a standard or accepted [true] value of a particular
quantity.”
FGDC-STD-007.1-1998
Precision - in statistics, a measure of the
tendency of a set of random numbers to cluster about a number
determined by
the set.
FGDC-STD-007.1-1998](https://crownmelresort.com/image.slidesharecdn.com/au2007itsnotcadtogisfinal-12737046890394-phpapp02/75/Au-2007-It-S-Not-Cad-To-Gis-Final-8-2048.jpg)
Uploaded byRichard Chappell, GISP
Au 2007 It’S Not Cad To Gis Final
This document discusses issues related to managing data across design and facility management organizations. It aims to dispel myths about CAD and GIS data and identify technical and non-technical integration barriers. While data transfer between CAD and GIS formats is technically possible, the primary barriers are related to how the data is organized and used for different purposes throughout the design and facility management lifecycle. The document recommends focusing on common data requirements and developing standards around layering, symbols, geometry, and attributes to better integrate CAD design data into GIS for facility management.
Au 2007 It’S Not Cad To Gis Final
- 1. It’s not CADto GIS; It’s Design to As-Built Richard E Chappell APS (Arizona Pubic Service)
- 2. APS Background 1.3 Million Customers 5 Operating Divisions 1140 Feeders/Circuits North East Metro Region = 75 % of Customers, North West 15% of Service Territory South West One of the Fastest Metro Metro Growing Customer bases West South East in United States
- 3. Contents • Discuss issuesrelated to managing data across the facility management organization • Dispel myths • Identify technical issues • Identify non-technical issues • Discuss options
- 4. Intended Audience • Designedfor a mixed audience • Generally not technical • Some understanding of AutoCAD and GIS would be helpful
- 5. Ground Rules • Noreligious discussions – No discussion of whether GIS or CAD is better. – Many of us, for various reasons, need to work in an environment shared between CAD and GIS software
- 6. Critical Terminology • Error •Accuracy • Precision Photo Credit: http://www.mandypatinkin.net/PB/pb.html
- 7. Error Measurement is aninexact science. There is error inherent in all measurement. • Errors can exist due to mistakes • Errors can exist due to methods and tools
- 8. Accuracy and Precision "Accuracy- closeness of an estimated (e.g., measured or computed) value to a standard or accepted [true] value of a particular quantity.” FGDC-STD-007.1-1998 Precision - in statistics, a measure of the tendency of a set of random numbers to cluster about a number determined by the set. FGDC-STD-007.1-1998
- 9. Photo credit: NOAACollections http://celebrating200years.noaa.gov/distance_tools/theb1670.html
- 10. Photo Credit: Howto: http://www.westone.wa.gov.au/toolbox6/hort6/html/resources/visitor_centre/how_to/measure.htm
- 11. Target Model ofData Quality ACCURATE PRECISE ACCURATE & PRECISE –Accuracy is the quality of the tools and methods –Precision is how well the measurement is done
- 12. Data Sets atDifferent Levels of Precision
- 13. Different Levels ofPrecision
- 14. Some Myths toDispel • CAD is dumb data • GIS data is not accurate • CAD doesn’t use coordinate systems • Technology now allows us to capture 80% of CAD data for GIS • CAD uses x and y coordinates, and GIS uses Latitude and Longitude • CAD is a graphics program and GIS is a database program
- 15. CAD and GISBasics • Both consist of basic primitive elements – Points – Lines – Polygons – Attributes • Both store this information within a database
- 16. Points • Represent aposition or location • Consist of coordinates – X, Y and Z
- 17. Lines • Consist ofcoordinate pairs – a start point and end point
- 18. Polygons • Consist ofgroup of coordinate pairs – a boundary of lines
- 19. Complex Features Complex featuresare generally some construct of these primitives • Annotation is a form of point • Polylines are groups of lines
- 20. Attributes • Primitives willhave data elements attached – Some elements describe the object itself – Some are data describing what the object represents
- 21. So what isthe difference? There are 2 key differences between CAD and GIS that are critical • Data Structure Paradigm • Graphic Representation
- 22. Data Structure Paradigm •AutoCAD stores data in a free form object oriented database where the fields in each row are defined by the entity type • ArcGIS stores data in predefined data structures where the fields are defined in each data type
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- 26. AutoCAD Point DataSet with Attributes
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- 28. What this means •The means that AutoCAD will store multiple data types in a single DWG, while ArcGIS will store multiple data types in separate files – Tables in Geodatabase – Sets of files for Shapes and other formats
- 29. Graphic Representation • InAutoCAD, the graphic representation is stored on the object as part of the individual object definition • In ArcGIS, all graphic representation is kept separate from the data
- 30. What this means •Sharing a DWG file provides an exact representation of the original graphic representation • Sharing a GIS data set will not provide an exact representation of the original graphic representation, without the ancillary support files Not good or bad – just different
- 31. Other Differences • Coordinatenumber data types – Floating point vs Long Integers • 32-bit – Single vs Double Precision • Some differences in primitives – Annotation – feature linked as well as annotation objects – Curves – curve data isn’t carried through some GIS data sets
- 32. Curves from aShapefile
- 33. What’s The Point Thephysical transfer of data is a minor technical issue • Most software vendors now provide excellent tools to transfer data back and forth • Most will allow direct editing of other data formats
- 34. Third-Party Options • Additonally,there are a number of third-party applications to further enable this interaction between systems – FME by Safe Software – GISConnect by Haestad Methods (Bentley) – Crossfire by EMS
- 35. So What’s theProblem?
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- 37. How it isseen in GIS
- 38. Integration Barriers • Theprimary barriers to integration are data organization and business issues rather than technical issues • The purposes of the data have a much larger impact than how the data is stored • Understanding those issues can remove the barriers
- 39. Purpose of theData • The purpose of the data can have a profound impact on the data • Across the facility management environment, there are a number of areas of the lifecycle, each with its own requirements
- 40. Commonality Across theWorkflow • Design and Facility Management are different activities that have unique requirements • Identify the common requirements and you identify the targets of integration • Then we can move to a real design to as-built data management process
- 41. Some of theIssues • Scale • Precision • Granularity • Generalization • Data Capture • Cartographic Issues
- 42. Scale • Different scaleshave different requirements • Generally, design scales will be much larger than GIS map scales – Design scales get in the 1”=20’-50’ range, where system maps get much smaller, as in 1”=100’-400’
- 43. 1”=5000’ Map Electrical System Map Itshows the road centerlines and the feeders
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- 46. Generalization • Reduce complexityby – Grouping of similar objects to simplify an image – Simplification of lines based on scale – Feature coalescence, selection and complexity reduction
- 47. Granularity • Granularity isthe grouping of dissimilar objects to represent a single feature • Items that aren’t important to the operation of the system may be dropped from facility maps
- 48. Precision and Accuracy •Higher accuracy is more expensive • Design requires a high degree of accuracy – Underground utilities • Most new construction work will include a site survey of 3rd order (or close) to identify the existing conditions • With a large land base, highly accurate data is likely too expensive to create and maintain
- 49. Cartographic Issues • Symbols – Blocks vs Fonts – Linetypes and masking • Appearance – White Space – “Slackuracy”
- 50. Putting It Together • Determine what data can move through the work flow • Understand how the pieces fit together • Be willing to re-evaluate your processes • Use the information to develop CAD standards that can make integration possible
- 51. Standards • Freeform natureof AutoCAD allows great flexibility • We can constrain CAD data to a similar organization as GIS through standards
- 52. Areas of Standardization • Layering • Symbols (Block) • Geometry • Attributes
- 53. Layers • In AutoCAD,layering is the most common method of segregating data • In ArcGIS, feature classes and subtypes define segregate the data • Match layers to feature classes and subtypes to segregate the data • Use similar object types within each layer – ie. Lines with lines, points with points
- 54. Point Symbols • Represent points in data set • ArcGIS uses a font in the map document to create the symbol • AutoCAD would use a block in the drawing • Identify Font-Block Mappings during conversion
- 55. Geometry • Maintain snappingthrough connected line features – use wipeouts to mask lines • Insure intersections are broken within a single data set • Use closed polygons to identify polygons
- 56. Attributes • Use attributesto label items rather than text labels • Use label blocks to attribute polygons and lines – after conversion, they can be spatially joined • One label block per element • Consider using external database links and maintaining an ID as an attribute
- 57. Conclusion By understanding theissues that really impact our processes, we can develop workflows that will allow us to take the most advantage of our data
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