Final Flashcards
(44 cards)
1
Q
Continuous Data
A
- Exists at all points on Earth
- Example: temperature which is measured at particular points, every location on the planet has a temperature at any given time
- Represented well with isolines/contour lines
2
Q
Discrete Data
A
- Exists in specific locations and not in others
- Example: people, roads, hospitals, airports
- Represented well with symbols positioned to represent the location of the feature
3
Q
Spatial Data
A
- Has coordinates
- Has been georeferenced
4
Q
Non-spatial data
A
- No coordinates
- Also called attribute data
- Ex: a person’s height, mass, and age
5
Q
Quantitative Data
A
mathematical
6
Q
Qualitative data
A
- Based on things like interviews
- Can be quantified
- Really great for understanding context
7
Q
Nominal data (attribute data)
A
- Objects classified into groups which have names, not numeric values
- No ordering (high to low) implied
- Also called categorical
- Examples: gender, race, land use type
8
Q
Ordinal Data
A
- Observations assigned to discrete categories
- Categories are ranked and have some kind of order/hierarchical relationship
- Observations measured at the ordinal level typically should not be added, subtracted, multiplied, or divided
- Examples: opinion poll with “strongly agree” to “strongly disagree”
9
Q
Interval Data
A
- Moved into quantitative realm
- Classifies data on a linear scale, but not relative to a true zero point in time or space
- Example: temperature and time of day
10
Q
Ratio data
A
- Quantitative attribute that has a true origin
- Can be added, subtracted, divided or multiplied
- These attributes support analysis using statistical techniques
Examples: number of doctors per county or dollars spent per patient
11
Q
Raster Data Model
A
- Associated most with continuous data
- Represented by cells (pixels)
Largest share rule (usually used) vs. central point rule (would be used for quick and dirty)
12
Q
Vector data model
A
- Associated most with discrete data
- Represented by points lines, and polygons
13
Q
Gatekeepers of data
A
- Government agencies
- Private agencies
- Non-profit agencies
14
Q
Searching for data
A
- Must also find data at the appropriate scale for your particular research question
- Broader patterns mask important patterns that occur at a smaller scale. Broad patterns mask context
15
Q
Normalizing data
A
- Reduction of data to any kind of canonical form
- Process of organizing the fields and tables to minimize redundancy and dependency
- Guided by our research question in order to make data useful
16
Q
crude data
A
- Great for showing numbers of occurrences
- Not useful for analysis
- Does not consider confounding variable such as population size or age
- Not helpful for spatial analysis
- Would be useful if you are looking at quantity
17
Q
data classification
A
- The purpose of data classification is to render the data into a simpler form for analysis to delineate meaningful patterns
- The trade off is a loss of detailed information about the data
- The gain is in the information about the spatial relationships that may exist
- Data classification procedures are used in map production in order to ease user interpretation
- GIS has made it possible to evaluate different possible classifications
18
Q
natural breaks
A
- Good for data that can be arranged as a series of high to low (mortality rate)
- Several “clumps” or groups of data emerge
- The groupings are considered natural because the observer has imposed no categorization scheme
Map maker determines the number of natural break categories
19
Q
equal interval/quantile
A
- Relatively uniform distribution
- Ignores natural distribution of the data
- The chief advantage is that these methods can be used to show changes over time when the categories are kept constant
20
Q
standard deviation
A
- Based on the normal distribution of the data
- Most are standardized to set the mean to zero
- Maps are created using the standard deviation away from the central mean
- Not frequently used because data rarely fits the normal distribution
- Outliers can skew the mean
21
Q
design principles for cartography
A
- Visual contrast: how map features and page elements contrast with each other and their background
- Legibility: the ability to be seen and understood
- Figure ground: the spontaneous separation of the figure in the foreground from an amorphous background
- Hierarchical organization: visual separation of your map into layers of information
- Balance: organization of the map and other elements on the page
22
Q
GIS
A
Geographic Information System - combines computer science, mathematics, geography, climate, etc. to handle big questions such as the mosquito example.
23
Q
coordinate system
A
reference system used to represent the locations of geographic features, imagery, and observations within a common geographic framework.
24
Q
global coordinate system
A
ex: (Latitude, Longitude)
a. Keep in mind precision of coordinates…1 decimal place is 6.2 miles
25
projected coordinate system
```
map projection (a mathematical transformation that translates a 3D object onto a 2D plane) that takes the earth's spherical surface and projects it onto a two-dimensional Cartesian coordinate plane.
***Properties of map projection:
- Continuity
- Area
- Distance
- Direction
- Shape
Examples: cylindrical projection, conical projection, planar projection, UTM
```
26
datum
projected coordinated systems are determined by datum. Determines point of origin. Many datum have been developed over many years. Depends on how someone measures Earth (circumference). All coordinate systems reference back to a particular datum. Two types
27
local referencing datum
a. Examples: NAD27, NAD83
| b. Developed for a set local area
28
global ferencing datum
a. Example: WGS84
b. Approximates the size and shape of earth as a whole
c. Not good for a local scale
d. What your GPS uses
29
Universal Transverse Mercator
- Based on x,y coordinate system
- Easy to use
- Within one meter
- Simple to measure distance
- Mostly used for topographic mapping
- 60 zones, 6 degrees each
- Datum used WGS and occasionally NAD83
- Each zone is individually projected and therefore decreases distortion, but you can't use two zones together
- Good for small scale, local scale analysis
Uses Mercator Transverse projection
30
State Plane coordinate Ssytem
- Developed in 1930s before computers
- Professor thinks it's still useful for city/town
- State can have one or six zone, depending on size and shape of state
- x,y coordinate system therefore escape negative numbers
- Very accurate within each zone
- Not very useful because you can't use it for national level
- Each zone is projected independently
- Uses Lambert conic projection (e - w) or transverse mercator projection (n - s)
31
decennial census
The first decennial census was a "simple" count. It consisted of six questions and counted approximately 3.9 million people for purposes of apportioning the U.S. House of Representatives. As the 2010 census approaches, one million enumerators will assist the Census Bureau in counting more than 300 million of the nation's inhabitants. In addition to apportioning state representation, 2010 census data will be used to make decisions effecting legislation and spending on housing, highways, hospitals, schools, assistance programs, and scores of projects and programs that are vital to the health and welfare of the U.S. population and economy. Now only in short-form…last year of long-form distribution was 2000
32
American Community Survey
It regularly gathers information previously contained only in the long form of the decennial census, such as ancestry, educational attainment, income, language proficiency, migration, disability, employment, and housing characteristics. These data are used by many public-sector, private-sector, and not-for-profit stakeholders to allocate funding, track shifting demographics, plan for emergencies, and learn about local communities.
- Rolling survey
- 1, 3, and 5 year extracts
- Sample of 1 in 38 households
There have been controversial questions such as "does this house have a flush toilet" and "what was each person's total income in the past year"
33
Boundaries of legal entities are changed due to
legal actions including states, counties, minor civil divisions, incorporated places, congressional districts, and school districts
34
Boundaries of statistical entities are changed to
reflect population growth or decline, or because of revisions either to visible or legal features used as boundaries. Statistical entities include census tracts, metropolitan/micropolitan statistical areas, urban areas, census designated places.
35
blocks
- ~85 people
- Smallest unit for 100% data tabulation
- Cover the entire nation
- Nest within all other types of geographic areas
36
block groups
- ~600-3,000 people
- Smallest unit for tabulation of sample data
- Nest within Census Tracts
37
census tracts
- ~1,200 - 8,000 people
- Small, relatively permanent, consistent statistical subdivision of a county
- Defined nationwide for the first time in 2000
38
incorporated places
census entity
- Legally bounded entity
- Ex: town, village, borough
Some form of local governance
39
Census designated place
census entity
- Statistical entity
- Area with concentration of population, housing, and commercial structures identifiable by name; but not within an incorporated place
40
urban areas
- Represent densely developed territory
- Contain residential, commercial, and other nonresidential urban land use
- Begin with a dense core of at least 1,000 people
- Two types:
○ Urbanized areas of 50, 000 or more people
○ Urban clusters of 2,5000 up to 50,000
41
core based statistical areas
- Replaced metropolitan/micropolitan terms
42
boundary and annexation survey
annual census bureau thing to collect information about selected legally defined geographic areas. Statistical areas also experience boundary changes, but much less frequently as they are designed to have stable boundaries
43
finding census data
social explorer (visualizations, other info) and american factfinder
44
census boundaries
- Census Boundaries are not static
- Census Boundaries have not always gone down to small geographies – the entire country not “tracted” until 1990
- Options for dealing with changing boundaries:
○ Use a product that provides normalized (adjusted & weighted) data
○ Choose a stable level of geography for the comparison (township, state, possibly county)
- Questions asked on the censuses change
○ Decennial vs. Decennial
○ Decennial vs. ACS
- Make sure the variables between two censuses are the same
- For all census research: Understand the variables! Make sure the variable you choose is the correct one for your topic of inquiry
