1. Chapter 2: The Pitfalls and Potential of Spatial Data
(O’Sullivan and Unwin, 2003)

2. Bad News First: Spatial Autocorrelation
Data from locations near one another in space are more likely to be similar than data from locations remote from one another (positive, negative, zero)
Modifiable Areal Unit Problem (MAUP)
Ecological Fallacy
Scale
how an object type is represented is scale dependent
Nonuniformity
space is not uniform
spatial distribution of people is bound to have clusters and gaps (doesn’t conform to regular statistical methods)

3. Modifiable Areal Unit Problem
This is a problem of data aggregation and the impact that the level of aggregation has on the patterns and relationships observed
Usually, regression relationships are strengthened by aggregation

4. Ecological Fallacy High Correlation between crime and low-income areas
Commit EF if we conclude that low-income people commit crimes
Perhaps, low-income households don’t have good alarm systems; Or drug-addicts (regardless of income) live in these areas and commit crimes

5. Now for the Good News: Distance (dist. between spatial entities)
Spatial Analysis focuses on the distribution of data in space; spatial relationships are described using the following:
Distance (dist. between spatial entities)
Adjacency (spatial relationship between entities: adjacent or not adjacent)
Interaction (I ~ 1/D) – (the nearer things are, the more related they are)
Neighborhood- region of space within a certain distance of a particular entity

6. Proximity Polygons
The proximity polygon of an entity is that region of space that is closer to that entity than it is to any other.

7. Variogram Cloud
Helps explore the spatial dependence between attributes of objects; plot the differences in attribute values for pairs of entities against the difference in their location (dist. between entities).
A variogram cloud is a tool used to study spatial dependencies between attributes of objects.

8. Questions
What are the 5 major problems in the analysis of geographic information???
How are proximity polygons constructed for point objects??