1. Mapping “what?” Instead of “where?”

2. Two types of geographic data: Horizontal location Vertical location Vegetation types Soil types Land cover Number of people LocationAttributes Attributes: characteristics of a place

3. Back to a previous topic … Reference maps Reference maps Emphasize location Emphasize location Thematic maps Thematic maps Emphasize patterns Emphasize patterns Leading candidate, by county Place names are attributes, but Location data is key Place names are attributes, but Location data is key Need location data, but attribute data is key Need location data, but attribute data is key

4. Mapping attributes Sources of attribute data Focus on census data

5. Examples of attributes: Vegetation types Soil types Land cover (forested, grass, asphalt, etc) Land use (wilderness, recreational, residential, commercial, etc.) Number of people People’s typical ages, incomes, etc! Temperature Precipitation How would you collect data for maps of these phenomena?

6. Sources of attribute data: Remote sensing: Land cover Vegetation types Soil types Precipitation Change over time, for any of these topics Aerial photography Satellite-based scanners

7. Ground surveys Count-based surveys More sources of attribute data: Vegetation, land cover Road type, land use Population (human) Population (animal)

8. Count-based Surveys: some definitions Census All members of a population Sampling Inferences about whole population based on some

9. Example: Decennial U.S. Census Why count? It’s in the Constitution M andate of Government Agencies US Census Bureau: “to be the preeminent collector and provider of timely, relevant, and quality data about the people and economy of the United States.”

10. 2000 Reapportionment

11. US Census … Issue 1 Challenges to getting a complete count: Time-consuming, laborious, costly Dishonest or uncompleted responses Homeless, transient populations, illegal immigrants

12. Challenges of a complete count Non-response follow-up enumerations (NRFU) = expensive Visit every house without a response Non-respondents usually urban, poor, minority Solution?

13. sample site Stratified sampling More efficient and accurate Widely used Example: survey of tree species in a forest Traditional sampling approach: “Random sample”

14. Stratified sampling The technique: Divide a region into homogeneous regions Assign sample sites to each stratum in proportion to what each area is thought to contribute low medium high biodiversity sample site “Stratified sample”

15. Complete Count v. Sampling Supreme Court ruling on use of sampling for census NRFU’s: WASHINGTON (CNN) – The U.S. Supreme Court on Monday ruled out the use of statistical sampling to adjust the 2000 census to make up for an expected undercount. The 5-4 ruling was a defeat for the Clinton administration, which had hoped statistical sampling would add population -- and subsequently House members -- to areas that traditionally vote Democratic. -AP, Jan 25, 1999

16. Issue 2: Reporting census data Aggregation: combining counts into spatial units Rather than recording precise location of individuals Less costly Preserves confidentiality 10 8 6 12 2 4 3

17. US census aggregation units States Counties Census Tracts – –Census Block Groups Census Blocks Challenge: changes Before 1990, census blocks and tracts only in some areas As population increases, units are divided

18. Challenge: Lost Detail Can aggregation lead to misrepresentation? 88 88 88 88 Accurate representation difficult to achieve Usually convenient regions are used

19. Conclusions on Count-based Surveys: Not “totally accurate” Reporting and map representation challenges Next Lecture…