Spatial Analysis & Dissemination of Census Data
United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis
Nairobi, Kenya, 14-17 September, 2010
Outline

Geographic Database

Spatial Analysis Techniques

Examples
United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis
Nairobi, Kenya, 14-17 September, 2010
Geographic Database
 Geographical features (Conceptual Model)



Components selection
Attributes
Structure
 Spatial Relationships (explicit -Topolgy)
United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis
Nairobi, Kenya, 14-17 September, 2010
Spatial relationships
 Logical connections between spatial objects represented
by points, lines and polygons
 e.g.,
- point-in-polygon
- line-line
- polygon-polygon
United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis
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, 14-17 September, 2010
Spatial Analysis Techniques
 the main use of spatial analysis is for census
products and services
 Techniques include: queries, distance
measurements, 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, 14-17 September, 2010
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, 14-17 September, 2010
Examples:
Id
What is
at…?
Features that
meet a set of
criteria
0012376027
Name
Population
Popdens
Num_H
H
Clinics
Limop
31838
37.5
8719
8
Population density
greater than 100
persons/sqkm?
United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis
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, 14-17 September, 2010
“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, 14-17 September, 2010
“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, 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, 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, 14-17 September, 2010
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, 14-17 September, 2010
“ 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, 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, 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, 14-17 September, 2010
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
12.7
26.0
27.2
15.9
24.5
26.1
United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis
Nairobi, Kenya, 14-17 September, 2010
Example of linear interpolation creating contours
United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis
Nairobi, Kenya, 14-17 September, 2010
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.

This method assumes that the
values of the unsampled data
are equivalent to those of the
sampled points.
Thiessen polygons illustrated
United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis
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, 14-17 September, 2010
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, 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, 14-17 September, 2010
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, 14-17 September, 2010
Location-allocation problems
 Site selection
 Optimal allocation
 Multicriteria Analysis
United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis
Nairobi, Kenya, 14-17 September, 2010
THANK YOU!
United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis
Nairobi, Kenya, 14-17 September, 2010