1. Spatial Analysis & Dissemination of Census Data
United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis
Nairobi, Kenya, September, 2010

2. Spatial Analysis and Dissemination of Census Data
Outline
The Power of Maps
Introduction and Example
Dynamic Census Atlases
Overview & Example
Spatial Analysis Techniques
Overview & Examples
Digital Geographic Data for Dissemination
Overview & Cost and Benefits
Digital Data Dissemination Strategies and Users
Overview of Users
United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis
Nairobi, Kenya, September, 2010

3. Spatial Analysis Techniques
the main use of spatial analysis is for census products and services
Techniques include: buffering, linear interpolation, point pattern analysis, and cartograms, etc.
All offer functionality beyond standard thematic (choropleth) mapping, with many tools now available in both commercial and open-source software programs.
United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis
Nairobi, Kenya, September, 2010

4. Spatial Analysis Techniques
Some prevalent forms of spatial analysis especially useful for use with population data include:
Queries
Distance measurements
Transformations
Buffering
point-in-polygon analysis
Polygon overlay analysis
United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis
Nairobi, Kenya, September, 2010

5. Spatial Analysis: Query
select features by their attributes:
“find all districts with literacy rates < 60%”
select features by geographic relationships
“find all family planning clinics within this district”
combined attributes/geographic queries
“find all villages within 10km of a health facility that have high child mortality”
Query operations are based on the SQL (Structured Query Language) concept
United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis
Nairobi, Kenya, September, 2010

6. Nairobi, Kenya, 14-17 September, 2010
Examples:
What is at…?
Features that meet a set of criteria
United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis
Nairobi, Kenya, September, 2010

7. Modeling/Geoprocessing
modeling: identify or predict a process that has created or will create a certain spatial pattern
diffusion: how is the epidemic spreading in the province?
interaction: where do people migrate to?
what-if scenarios: if the dam is built, how many people will be displaced?
United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis
Nairobi, Kenya, September, 2010

8. Spatial relationships
Logical connections between spatial objects represented by points, lines and polygons
e.g.,
- point-in-polygon
- line-line
- polygon-polygon
Fundamental Questions addressed by GIS
What is in a particular place?
Find the position of some object
What is the area of, the distance from specific object?
Find patterns- by looking at the distribution of features on the map instead of just an individual feature
Combination of data layers
Point in polygon operation
Line in polygon operation
Polygon overlay
United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis
Nairobi, Kenya, September, 2010 8

9. Nairobi, Kenya, 14-17 September, 2010
Spatial Operations
“adjacent to”
“connected to”
“near to”
“intersects with”
“within”
“overlaps”
etc.
United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis
Nairobi, Kenya, September, 2010

10. Nairobi, Kenya, 14-17 September, 2010
“is nearest to”
Point/point
Which family planning clinic is closest to the village?
Point/line
Which road is nearest to the village
Same with other combinations of spatial features
United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis
Nairobi, Kenya, September, 2010

11. Spatial Analysis (cont.)
Buffer: find all settlements that are more than 10km from a health clinic
Point-in-polygon operations: identify for all villages into which vegetation zone they fall
Polygon overlay: combine administrative records with health district data
Network operations: find the shortest route from village to hospital
United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis
Nairobi, Kenya, September, 2010

12. Spatial Analysis Techniques
Queries:
Often this is the first step in an analysis, where one seeks to create a subset of units such as populated places with certain characteristics, allowing the user to check how typical an observation is against other observations
They use a GIS program to answer simple questions posed by the user, with no changes in the database and no new data produced.
An example of a query using geo-coded census data is, select all towns with a population greater than 1,000 persons. These towns can then have their attributes summarized, for instance, to measure their total fertility rates against smaller towns and villages, then map the results
The term exploratory data analysis refers to investigations of patterns and trends in data using such techniques as querying
Queries are considered the most basic type of analysis operation.
United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis
Nairobi, Kenya, September, 2010

13. Nairobi, Kenya, 14-17 September, 2010
Area delineation
E.g. Interactive determination of school districts with the same number of children in each school grade by aggregating census dissemination areas
United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis
Nairobi, Kenya, September, 2010

14. Spatial Analysis Techniques
Distance measurements
Easily done with all GIS programs, using the centroids (or center points) of cities, towns, and villages.
An analysis can be done to select villages located more than a kilometer from a school, clinic, or water source.
These can then be further analyzed using the attribute information for the populated places themselves.
United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis
Nairobi, Kenya, September, 2010

15. Spatial Analysis Techniques
Transformations
Methods of spatial analysis that use simple geometric, arithmetic or logical rules to create new datasets
Transformations can include operations that convert raster into vector data, or a stream of GPS coordinates into a route or a boundary
Of all the transformational techniques, buffering is the most well known and important
United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis
Nairobi, Kenya, September, 2010

16. Spatial Analysis Techniques
Buffering (transformation)
Involves building a new data layer by identifying all areas that are within a certain specified distance of the original.
Buffering can be performed on points, lines and polygons and can be weighted by attribute values.
Buffering can be used to model travel time, for instance, by creating a “catchment area” around a particular feature such as a school or a clinic.
This provides a measure of accessibility that can be mapped across the extent of a country.
United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis
Nairobi, Kenya, September, 2010

17. “is near to”: Buffer Operations
Point buffer
Affected area around a Hospital
Catchment area of a water source
United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis
Nairobi, Kenya, September, 2010

18. “is near to”: Buffer Operations
Point buffer
Affected area around a polluting facility
Catchment area of a water source
United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis
Nairobi, Kenya, September, 2010

19. Nairobi, Kenya, 14-17 September, 2010
Buffer Operations
Line buffer
How many people live near the polluted river?
What is the area impacted by highway noise?
United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis
Nairobi, Kenya, September, 2010

20. Nairobi, Kenya, 14-17 September, 2010
Buffer Operations
Polygon buffer
Area around a reservoir where development should not be permitted
United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis
Nairobi, Kenya, September, 2010

21. Spatial Analysis Techniques
point-in-polygon analysis
Determines whether a point lies inside or outside a polygon.
Can be used to compare geo-coded village centroids lying inside and outside hazardous areas such as tropical storm tracks or earthquake zones.
Polygon overlay analysis
Involves comparison between the locations of two different polygonal data layers.
For example, the boundaries of two administrative districts could be compared to troubleshoot errors in the field enumeration process
United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis
Nairobi, Kenya, September, 2010

22. “ is within”: point in polygon
Which of the cholera cases are within the containment area
United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis
Nairobi, Kenya, September, 2010

23. Nairobi, Kenya, 14-17 September, 2010
Problem: We may have a set of point coordinates representing clusters from a demographic survey and we would like to combine the survey information with data from the census that is available by enumeration areas.
Solution:
“Point-in-Polygon” operation will identify for each point the EA area into which it falls and will attach the census data to the attribute record of that survey point.
United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis
Nairobi, Kenya, September, 2010

24. Nairobi, Kenya, 14-17 September, 2010
Spatial aggregation
Example of Spatial aggregation:
fusion of many provinces constituting an economic region
United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis
Nairobi, Kenya, September, 2010

25. Spatial Analysis Techniques
Spatial interpolation
A spatial analysis method designed to fill in values that lie between observations
A variety of methods including inverse-distance weighting and kriging are used to estimate the values of unsampled sites
based on Tobler’s first law that all nearby objects are more similar than distant objects
Kriging: interpolation technique for obtaining statistically unbiased estimates of spatial variation of known points such as surface elevations or yield measurements utilizing a set of control points
In kriging, the general properties of a surface are modeled to estimate the missing parts of the surface
United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis
Nairobi, Kenya, September, 2010

26. Spatial data transformation: interpolation
Example 1: Based on a set of station precipitation surface estimates, we can create a raster surface that shows rainfall in the entire region
13.5
20.1
26.0
27.2
12.7
15.9
24.5
26.1
United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis
Nairobi, Kenya, September, 2010

27. Nairobi, Kenya, 14-17 September, 2010
Example of linear interpolation creating contours
Illustration showing how contour lines of elevation can be derived through linear interpolation from a satellite image.
United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis
Nairobi, Kenya, September, 2010

28. Thiessen polygons illustrated
Spatial Analysis Techniques
Thiessen polygons
Have the unique property that each polygon contains only one input point (e.g. settlements), and any location within a polygon is closer to its associated point than to the point of any other polygon.
Thiessen polygons illustrated
United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis
Nairobi, Kenya, September, 2010

29. Nairobi, Kenya, 14-17 September, 2010
Areas of influence
Commuting distances: daily commuters flow
United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis
Nairobi, Kenya, September, 2010

30. Spatial Analysis Techniques
Cartograms
sometimes used to display census results
The areas of the original polygons are expanded or contracted based on their attribute values such as population size or voting habits
United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis
Nairobi, Kenya, September, 2010

31. Nairobi, Kenya, 14-17 September, 2010
Modelling: smoothing
Evolution of the population beetwen two censuses
United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis
Nairobi, Kenya, September, 2010

32. Nairobi, Kenya, 14-17 September, 2010
Location-allocation
Site selection
Optimal allocation
Multicriteria Analysis
United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis
Nairobi, Kenya, September, 2010

33. Nairobi, Kenya, 14-17 September, 2010
THANK YOU!
United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis
Nairobi, Kenya, September, 2010