DS7002 Spatial Data Analysis
Practical Exercises
1
Session 7 – Exploring and Mapping Social Landscape of London
(Basic Geostatistics and Thematic Mapping with QGIS and GeoDa)
Objectives: To develop skills of Geostatistics and Thematic Mapping through QGIS and
GeoDa functionalities.
Task 1: Exploring Health Data across London Boroughs
Problem solving: Initially reveal spatial pattern of public health in London
Functionality: Basic Geostatistics in GeoDa
Data set: Health variables by London Borough
In GeoDa
Open a new project in GeoDa: File -> New, Input the Shape file of
“london_life_polygon.shp”
Practice following statistical functionalities with health variables of ‘LIFE_MALE’ (male
life expectance), ‘LIFE_FEMALE’ (female life expectance), ‘P_SMOKE’ (percentage of
smoking population), ‘P_BINGE’ (percentage of binge drinking population),
P_HEALTHY (percentage of healthy population).
GeoDa -> Explore -> Histogram
-> Boxplot
-> Scatterplot
-> Bubble Chart
Practice following statistical functionalities with variables of ‘OBESE’ (obesity
population) and ‘Population’ (residential population)
GeoDa -> Map -> Rates-Calculated map -> Raw Rate
-> Excess Risk
With above functions, risk of obesity will be spatially illustrated in London,
which can support further risk analysis.
Problem solving: Initially explore spatial accessibly in London
Functionality: Basic spatial analysis tools in QGIS
Data set: Maps of London Boroughs, Motorway and Underground Stations
In QGIS
Add “london_boroughs.shp”, “motorway.shp” and “UndergroundStations.shp”
Practice following statistical functionalities:
QGIS -> Vector -> Analysis Tools -> Sum line lengths by polygon
-> Count points in polygon
DS7002 Spatial Data Analysis
Practical Exercises
2
With above functions, it is easy to find out figures related to local spatial
accessibility, such as length of Motorway and number of tube stations.
Task 2: Thematic Mapping of Crime Data across London Boroughs
Problem solving: Create thematic maps to show spatial pattern of crimes in London
Functionality: Mapping functions in GeoDa
Data set: Crime variables by London Borough
In GeoDa
On “london_life_polygon.shp”, practice following mapping functionalities with crime
variables of “BURGLARY” (counts of burglary per 1000 persons), “CRIME_DANAG”
(counts of crime damage per 1000 persons), “DRUG_OFFEN” (counts of drug offence
per 1000 persons), “VEHICLES” (counts of vehicles theft per 1000 persons),
“VIOLENCE” (counts of violence crime per 1000 persons).
GeoDa -> Map -> Quantile Map
-> Percentile Map
-> Box
-> Standard Deviation Map
-> Cartogram Map
With above functions, various thematic map can be created to demonstrate
spatial distribution of different types of crimes
In QGIS
On “london_life_polygon.shp”, practice following mapping functionalities with crime
variables of “CRIME_1000” (total counts of crime per 1000 persons) with your
preferred colour schemes:
QGIS -> Layer -> Properties -> Style
(right click of mouse -> Properties -> Style
-> Graduated)
QGIS and GeoDa have similar functions on thematic mapping. QGIS is more
flexible while GeoDa is more straightforward.
Please export rate and risk maps of obesity created in GeoDa from Task 1, export thematic
map of crime created in QGIS from Task 2 and put them into your portfolio.
GeoDa: right click of you mouse -> Save Image as
QGIS: Project -> Save as Images
Please have comments on difference between functionalities of Geostatiscs and
corresponding functionalities in conventional statistical packages.
In thematic maps, is there any difference in spatial pattern by different classifications and
colour schemes?