1. In a vector setting –Stored in a relational database for each geographic object A relational database is organized in a series of two-dimensional tables, each of which contains records for one data object. A ‘row’ of data for each point, line, or polygon Attribute data

2. Row = object Column = property Vector setting: attribute data:

3. Raster setting: attribute data In a raster setting –Stored as a grid of cells (each cell is given one number)

4. Cell (x,y) 12358 46839 35331 75439 22452 Cell value columns rows Raster attributes: cell values

5. Attribute data Three types of data: Nominal scale Ordinal level Interval and ratio levels

6. Attribute data types Nominal data – descriptors about the objects – numbers do not quantify an amount Examples: 1-school, 2-community center, 3-bench mark 1-Road, 2-boundary, 3-stream 1-Swamp, 2-desert, 3-forest 1-Apple tree, 2-peach tree

7. Ratio data: ratios make sense (3:1) for these data (which means that ‘0’ means ‘nothing’/‘none’/‘zilch’) mm of precipitation Resident population Elevation (contour lines: 30m, 40m, 50m, etc.) Average household income (of census tract) Age Ratio data

8. Interval scale: adding numbers are meaningful, but ratios aren’t Fahrenheit Celsius Note: 10 degrees cooler means the same thing at each temperature. But 20 degrees doesn’t mean twice as much as 10 degrees. Also, 0 degrees doesn’t mean ‘no degrees’.

9. Ordinal data Numbers identify an order only (no scale) Road size:, 1-forest path, 2-dirt road, 3- gravel road, 4-country road, 5-major highway 1-never, 2-sometimes, 3-often, 4-always 1-sober, 2-tipsy, 3-drunk, 4-smashed/pissed (British), 5-plastered 1-small, 2-medium, 3-large