Geographic Information Systems Data Quality

Practical issues Legal issues Theoretical issues 1. Necessity Practical issues Legal issues Theoretical issues                 

Necessity .. Accuracy - A measure of how closely data match the true value or descriptions Precision - A measure of how exactly data are measured and stored               

Necessity .. Error - The deviation between the measured value and the true value of a feature Uncertainty - A lack of confidence in the use of data due to incomplete knowledge                

Inherent errors Operational errors 2. Sources of Error Inherent errors Operational errors

2. (1) Inherent Errors Errors contained in source data, and they cannot be eliminated Map creation - Projection, generalization, etc. Map availability - Age of map, area coverage, map scale, map format, map accuracy, and map accessibility, etc.

Map Projection

Generalization http://polymer.bu.edu/java/java/coastline/coastlineapplet.html

Age of Map Northallerton circa 1999 Northallerton circa 1867 http://www.geog.leeds.ac.uk/courses/level2/geog2750/geog2750_13.ppt

SUFFOLK COUNTY PARCELS Area Coverage NASSAU COUNTY BASEMAP SUFFOLK COUNTY PARCELS Many data sets do not have a uniform coverage of information Arthur Lembo, Jr. Cornell University

Map Scale City of Sapporo, Japan 1:3Mil 1:500,000 1:25,000 1:10,000 http://www.geog.leeds.ac.uk/courses/level2/geog2750/geog2750_13.ppt

Map Format

Map Accuracy Standards 1:1,200 ± 3.33 feet 1:2,400 ± 6.67 feet 1:4,800 ± 13.33 feet 1:10,000 ± 27.78 feet 1:12,000 ± 33.33 feet 1:24,000 ± 40.00 feet 1:63,360 ± 105.60 feet 1:100,000 ± 166.67 feet http://www.colorado.edu/geography/gcraft/notes/error/error_f.html

Map Accessibility

2. (2) Operational Errors Errors introduced during data entry and manipulation Inherent errors may be enhanced by operational errors Data entry Data storage Data manipulation

Operational Errors .. Data entry Data storage - Numeric precision - Locational precision Data manipulation - Sampling/interpolation - Conversion - Overlay Output accuracy can only be as accurate as the least accurate individual layer – “GIGO”

Operational Errors .. Data entry

Data Entry Errors http://www.colorado.edu/geography/gcraft/notes/error/error_f.html

Sampling/Interpolation

Conversion - Raster to Vector Vector data converted to raster with 10’ grid cells Raster data converted back to vector, using 10’ grid cells Vector Data of Buildings Arthur Lembo, Jr. Cornell University

Overlay - Sliver In the following example, there are two polygons. When we overlay the two of them, the resulting polygon has not only the logical intersection between the two polygons, but also many small polygons that are probably due more to the fact that the representation of the polygon boundaries are slightly different. These smaller, or sliver polygons, represent spatial errors in the data. Arthur Lembo, Jr. Cornell University

3. Data Quality Assessment Data quality: "Fitness for use” Data quality assessment: "Truth in labeling” - It is data producer's responsibility to provide detailed information about the data - It is users' responsibility to make their judgment of "fitness for use"

Metadata Data about data Federal Geographic Data Committee (FGDC) - Content Standard for Digital Geospatial Metadata - U.S. National Committee for Digital Cartographic Data Standards (NCDCDS)

Components of Data Quality Positional accuracy Attribute accuracy Logical consistence Completeness Lineage

Closeness of coordinates to the true position Positional Accuracy Closeness of coordinates to the true position

Attribute Accuracy Closeness of attribute values to their true value Locational accuracy and attribute accuracy are closely related to each other - correct attributes but wrong locations - correct locations but wrong attributes

Logical Accuracy How well the relationships between data elements are maintained - geometry-attribute link consistency - topological consistency

Completeness The proportion of data available for the area of interest The level of classification for different categories of attributes

Attribute Completeness - High density - Residential - Low density Urban or build-up - Commer/indust Agricultural - Pasture - Row crop - Small grains Rangeland Forest land - Deciduous forest - Evergreen forest - mixed forest Water - Open water

Lineage Accuracy Data sources and the process steps used to produce the data - Data sources, methods of compilation, dates of data, map projection used, audit trails, etc

Readings Chapter 4