Intro Flashcards
1
Q
What is Spatial Analysis?
A
- A set of tools (stats, math, software, hardware) to analyze (concepts, theories, techniques, models) spatial processes
- A subset of analytic techniques whose result depend on the spatial frame, or will change if the frame changes or if objects are repositioned within it.
- Reveals patterns that are otherwise invisible
2
Q
Aspatial data
A
Attribute, Pi (z)
- Value/info
3
Q
Spatial Data
A
Location and Attribute
- Pi (x,y,z)
- This is why matrices are often used
4
Q
What does it mean that Spatial Analysis has no locational invariance?
A
- Results change when locations of study objects change
- ‘Where’ matters
5
Q
What are the 4 main components of spatial analysis?
A
- Data manipulation
- Exploratory spatial data analysis and visualization
- Spatial statistical analysis
- Spatial modelling
6
Q
Data manipulation
A
- GIS, databases, processing, projecting
7
Q
Exploratory spatial data analysis and visualization
A
Showing and identifying interesting patterns
8
Q
Spatial statistical analysis
A
Investigating data to determine whether or not data can be represented in spatial model
9
Q
Spatial Modeling
A
Explaining interesting patterns and/or predict spatial outcomes
10
Q
Spatial Sampling
A
- Location as an experimental design problem
- Location as a given
11
Q
Location as an experimental design problem
A
- Spatial sampling = where to collect data
- Which villages
- Where to locate air quality monitoring stations
- Design sampling approach to fit surface
12
Q
Location as a given
A
- Most spatial data analyses have no choice in location
- No sampling in the usual sense
- data = attributes augmented with location information
- ex. census tract boundaries not under control of analyst
13
Q
Spatial Autocorrelation
A
- Why is something the way it is?
- There is an underlying process for why the surface is the way it is (not random as is ‘required’ for stats)
- Ex. Elevation has underlying trend in topography, tectonics, erosion
14
Q
What are the 4 major problems in spatial sampling?
A
- Maup
- Ecological fallacy
- Boundary/extent
- Scale
15
Q
What is critical when ‘the where’ is introduced?
A
- Spatial dependence, the relatedness of data in space
16
Q
MAUP
A
- Modifiable Areal Unit Problem
- Problem when data relates to discrete zones (most socioeconomic data)
- Densities in an area change/vary in space
- Grouping the data can have infinite possibilities and can greatly affect results (mean, etc.)
- Data is strongly dependent on groupings (tell different stories)
- Partly depends on underlying micro data and nature of zoning system
- Some can be justified (watersheds) but some change over time (neighbourhoods)
- Paly depends on underlying micro data and nature of zoning system
17
Q
Correlation relationship, R^2
A
- Does not imply causation
- Shows how strong the relationship is between the dependent and independent variables
- Can change/shift based on aggregation of groups
18
Q
Scale Problem
A
- Scale of spatial process and scale of spatial measurement
- Up/down scale and results change
- Use fractals (similar spatial pattern at increasing scales) to understand how to scale up/down
19
Q
Ecological Fallacy
A
- Inference on individual based on aggregated group data
- Results from belief that relationships observed fro groups hold for individuals
- Ex. use aggregated province to infer on municipalities, can greatly differ from provincial mean
- Ex. Countries with more fat in diet have higher rate of breast cancer, must mean women who eat fatty foods more likely to get cancer
20
Q
Boundary Problem
A
- Spatial processes are generally unbounded
- Artificial and arbitrary boundaries are often imposed for analysis purposes (grid points)
- Edge effects outside of boundary often impossible to control
- Does surface extend outside study area even though we have no observations?
- Potential fix: collect data outside of study area to help control edge effects
21
Q
Diffusion
A
- Who has it, who doesn’t
- Spreads slowly outwards
- Requires contact/adjacency
22
Q
Exchange and Transfer
A
- Commodities and income
- Adjacency
- Spill over effects
23
Q
Interaction
A
- Events at a location affect events at another
24
Q
Spatial organization can be exploited to?
A
- Design sampling plans
- Interpolate
- Fill in missing values in a database
- Classify
25
Main issues of Spatial Processes?
Representation of spatial dependence
26
Spatial Processes
- Diffusion
- Exchange and Transfer
- Interaction
27
Spatial Dependence
- Recall 1st law of geography
- Affects outcome of stat tests
- If present and not accounted for, the variance of correlation coefficient is underestimated
- Overlap on graphs
- Leads to redundancy, greater chance of outliers, chance of accepting null hypothesis when it is wrong
28
1st Law of Geography
Everything is related to everything else, but near things are more related than distant things
29
How do you tell if data is spatially dependent?
- Test for it!
| - Geary's C and Moran's I (Positive, Negative, None)
30
First order spatial autocorrelation
- Spatial variation occurs when observations across a study region vary from place to place due to changes in the underlying properties of the local environment
31
Second order spatial autocorrelation
Variation is due to interaction effects between observations
