Use of GIS, Spatial Analysis and Web-based
Mapping
United Nations Statistics Division
United Nations Sub-regional Workshop on Collection and Dissemination of Socio-economic Data from
Population and Housing Censuses
New Delhi, India, 28-30 May, 2012
Outline

UN Recommendations/Census Geography Programme

Why we use geospatial tools in censuses

Building a EA Geographic Database

Spatial Analysis

Web-based Mapping Services and Applications

Handbook on Geospatial Infrastructure in Support of
Census Activities
United Nations Sub-regional Workshop on Collection and Dissemination of Socio-economic Data from
Population and Housing Censuses
New Delhi, India, 28-30 May, 2012
UN Recommendations
 UN Principles and Recommendations for Population and Housing
Censuses, Rev.2, recommended the use of Geospatial technologies
for improving traditional methods of census mapping (adopted by
UNSC in 2007).
 Other recommendations derived from UN EGM on GIS and Census
Mapping emphasized:


the need for countries to consider the census geography programme as a
continuous process
the use of geospatial technologies and information is beneficial at all stages
of population and housing census process (GI improves the efficiency in
the preparatory, enumeration, processing and dissemination phases of the
census)
United Nations Sub-regional Workshop on Collection and Dissemination of Socio-economic Data from
Population and Housing Censuses
New Delhi, India, 28-30 May, 2012
Statistical Commission Decision on the Integration of
Statistical and Geospatial Information
Decision 41/110 (of the SC at its 41st session in 2010):

(b) Recognized the importance of the integration of geographic
and statistical information and the opportunities provided in that
context by the swift development of information technology, noting
that national statistical offices are playing an increasing role in such
integration, especially in the area of census management;

(c ) Called upon all national statistical offices to actively participate,
in partnership with relevant national authorities, in the further
development of national geographic information capacity in the
context of spatial data infrastructures, taking full advantage of
information technology and focusing special attention on the area of
improving statistical and geographic metadata compatibility;
United Nations Sub-regional Workshop on Collection and Dissemination of Socio-economic Data from
Population and Housing Censuses
New Delhi, India, 28-30 May, 2012
Census Cycle
United Nations Sub-regional Workshop on Collection and Dissemination of Socio-economic Data from
Population and Housing Censuses
New Delhi, India, 28-30 May, 2012
GIS with Census mapping at all stages
Pre-census
(Pre-enumeration)
Census
(Enumeration)
GPS
Photo/Video
Post-Census
(Post-enumeration)
GPS/PDA
GIS
Digital Mapping
GIS
GIS
Internet
(Map-Server)
Digital
Mapping
Satellite Imagery
EAs Units
Administrative and Reporting Units
United Nations Sub-regional Workshop on Collection and Dissemination of Socio-economic Data from
Population and Housing Censuses
New Delhi, India, 28-30 May, 2012
Administrative hierarchy
 Every country has its own specific administrative hierarchy
 Definition:
A system by which the country and each lower level set of
administrative units (except the lowest) are subdivided to
form the next lower level.
 Administrative areas for which census data will be reported
United Nations Sub-regional Workshop on Collection and Dissemination of Socio-economic Data from
Population and Housing Censuses
New Delhi, India, 28-30 May, 2012
Illustration of a nested admin.
Hierarchy
Provinces
 Relationships among all types
of administrative and
reporting unit boundaries are
defined.
Districts
 hierarchical levels may have
actual administrative roles
 Other units may have
statistical roles alone
Localities
Enumeration
areas
United Nations Sub-regional Workshop on Collection and Dissemination of Socio-economic Data from
Population and Housing Censuses
New Delhi, India, 28-30 May, 2012
Coding Scheme
 EA: a basic geographic feature
 Need for an identifier: linking the geographic feature to the
census data (attributes) recorded for them
 EAs and administrative units: coding scheme


A unique code assigned to each EA, used in data processing
Coding scheme: scalability, flexibility, intuitiveness, compatibility
 Example of a hierarchical coding scheme
1
2
province
0
3
4
district
0
1
2
locality
5
0
0
2
4
Enumeration area
United Nations Sub-regional Workshop on Collection and Dissemination of Socio-economic Data from
Population and Housing Censuses
New Delhi, India, 28-30 May, 2012
Geocode

Any alphanumeric or numeric-only value that will uniquely identify
one and only one geographical entity within the set of all similar
entities

Examples:







Mailing address
First and second level administrative areas with their name or number
Census statistical area numbers
Health district number
Watershed ID
Etc.
Geo-coding: not limited to address-matching (commercial use)
Source: US Census Bureau
United Nations Sub-regional Workshop on Collection and Dissemination of Socio-economic Data from
Population and Housing Censuses
New Delhi, India, 28-30 May, 2012
Why is GIS unique?

Can combine spatial and non-spatial data from different datasets in a
spatial analysis operation in order to answer questions such as:

What is there…
Identification

Where is…
Location

What has changed since…
Trends

What relationships exist between…
Patterns

What is the best route between…
Optimal path

What if…
Model
Source: US Census Bureau
United Nations Sub-regional Workshop on Collection and Dissemination of Socio-economic Data from
Population and Housing Censuses
New Delhi, India, 28-30 May, 2012
A GIS Works on Geocoded Data
Statistical Data
Geocodes
GIS
Maps, tables,
Geographical Data
reports
United Nations Sub-regional Workshop on Collection and Dissemination of Socio-economic Data from
Population and Housing Censuses
New Delhi, India, 28-30 May, 2012
Complete EA map with all components overlaid
on one map display
61
27
57
65
40
43
28
349
42
60
41
19
63
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350
20
21
64
9
8
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2
14
20
29
28
eet
Bonne Str
Robinson
Street
32
31
41
33
79
44
eet
Tissot Str
47
50
46
86
54
4
52
54
9
Cartania
Chartes
Maptown
7
12
53
22
377
16
11
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9
25
378
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8
27
32
34
10
21
Enumeration Area Map
Province:
District:
Locality:
EA-Code:
13
23
Bessel Street
3
2
14
84
85
15
52
51
1
2
24
51
45
58
27
83
Grinten Street
50
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28
1
88
39
Street
48
77
78
Miller
42
59
29
Imhof Drive
43
76
Mollweide Street
40
34
374
21
20
19
82
81
80
87
41
30
18
Cassini Drive
37
42
Goode
33
68
69
70
38
31
32
13
362
71
43
27
28
29
12
36
361
23
30
21
22
22
Street
20
23
26
25
74
73
35
24
67
10
3
4
72
Cassini Drive
21
19
15
16
75
11
2
ive
44
17
63
Dr
51
3
64
5
Gall Street
18
Lambert Avenue
enue
tor Av
Merca
43
65
19
13
et
38
45
12
kij Street
Krassows
re
Snyder St
37
66
57
Tobler Street
42
62
Street
56
59
10
11
6
eet
e Str
Clark
7
1
Street
Ortelius
Ptolemy
5
4
61
60
1
41
42
43
44
33
34
55
31
358
32
Eckert Drive
6
Main components are:
Street network,
Buildings
EA boundaries layer
Annotation,
Symbols,
Labels
Building numbers
Neatlines
Legend
45
31
35
22
62
33
Symbols
14
032
0221
00361
District
358
EA-Code
Locality
EA
N
17
Building
number
Hospital
Church
School
Approximate scale
0
50
100
200m
Census 2000
National Statistical Office - July 1998
United Nations Sub-regional Workshop on Collection and Dissemination of Socio-economic Data from
Population and Housing Censuses
New Delhi, India, 28-30 May, 2012
Components of a Hypothetical
Buildings
Street Network urban EA map
Boundaries
Street
Network
Boundaries
Annotation
and symbols
Buildings
Anno
350
349
358
358
362
361
374
374
378
377
Building
numbers
Boundaries
61
27
57
35
22
65
62
40
Neatlines and
Annotation
and legend
symbols
Boundaries
31
32
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41
42
20
21
42
43
44
41
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34
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350
349
6
61
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349
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350
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58
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6
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5
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7
1
62
31
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5
66
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7
1
62
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65
3
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31
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2
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358
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69
43
3
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22
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1
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1
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3
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378
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377
Building numbers
61
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65
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35
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62
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60
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7
358
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9
26
25
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2
3
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32
52
34
9
10
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378
Enumeration
Province:
District:
Locality:
EA-Code:
Church
Building
number
17
School
Building numbers
41
42
43
44
Census
2000
61
27
1
57
65
35
22
62
Neatlines and legend
45
National Statistical Office July 1998
6
61
60
27
16
Hospital
EA
8
53
45
377
EA-Code
10
Neatlines and legend
33
34
55
47
11
44
54
50
23
Locality
64
58
59
District
54
Approximate scale
31
32
63
28
13
15
52
51
Symbols
14
032
0221
00361
N
19
43
Cartania
Chartes
Maptown
49
51
50
58
1
Enumeration Area Map
Province:
District:
Locality:
EA-Code:
27
48
374
16
4
9
14
84
85
24
27
26
25
22
51
87
86
40
12
42
52
27
2
83
39
41
374
53
58
54
88
10
8
28
1
38
33
30
34
9
54
59
361
32
31
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77
78
43
42
33
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24
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32
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80
36
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82
79
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361
2
14
33
30
362
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70
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30
32
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43
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35
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87
42
41
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16
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32
31
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69
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3
37
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67
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Ne
31
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59
Building numbers
Annotation
and symbols
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69
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82
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10
New Delhi, India, 28-30 May, 2012
65
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3
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42
43
44
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68
12
N
Approxima
31
19
United Nations Sub-regional Workshop on Collection and Dissemination of Socio-economic Data from
Population and Housing Censuses
40
Carta
Char
Mapt
13
Entity-Relationship Example:
EA entity can be linked to the entity crew leader area. The table for this entity
could have attributes such as the name of the crew leader, the regional office
responsible, contact information, and the crew leader code (CL code) as primary
code, which is also present in the EA entity.
R
EA
EA-code
Area
Pop.
1-1
Crew leader area
1-N
CL-code
Name
RO responsible
United Nations Sub-regional Workshop on Collection and Dissemination of Socio-economic Data from
Population and Housing Censuses
New Delhi, India, 28-30 May, 2012
Implementation of an EA database
Entity: Enumeration areas
 : Example of an entity table
– enumeration area
Type (attributes)
Instances
EA-Code
Area
Pop
723101
723102
723103
723201
723202
723203
723204
…
32.1
28.4
19.1
34.6
25.7
28.3
12.4
…
763
593
838
832
632
839
388
…
CL-Code
88
88
88
88
89
89
89
…
Primary
key
United Nations Sub-regional Workshop on Collection and Dissemination of Socio-economic Data from
Population and Housing Censuses
New Delhi, India, 28-30 May, 2012
Components of a digital geographic census database
United Nations Sub-regional Workshop on Collection and Dissemination of Socio-economic Data from
Population and Housing Censuses
New Delhi, India, 28-30 May, 2012
Spatial Analysis
 Geographical features (Conceptual Model)



Components selection
Attributes
Structure
 Spatial Relationships (explicit -Topolgy)
 Spatial Analysis
United Nations Sub-regional Workshop on Collection and Dissemination of Socio-economic Data from
Population and Housing Censuses
New Delhi, India, 28-30 May, 2012
Spatial relationships
 Logical connections between spatial objects represented by
points, lines and polygons:
- point-in-polygon
- line-line
- polygon-polygon
 Spatial relationships:
- “adjacent to”;
- “connected to”
- “near to”;
- “intersects with”
- “within”;
- “overlaps”
Street Network
Buildings
Boundaries
Annotation and symbols
- etc.
349
United Nations Sub-regional Workshop on Collection and Dissemination of Socio-economic
Data from
Population and Housing Censuses
350
New Delhi, India, 28-30 May, 2012
358
362
Spatial Analysis Techniques
 Techniques include: queries, distance
measurements, buffering, linear interpolation, point
pattern analysis, and cartograms, etc.
 the main use of spatial analysis is for census
products and services
United Nations Sub-regional Workshop on Collection and Dissemination of Socio-economic Data from
Population and Housing Censuses
New Delhi, India, 28-30 May, 2012
Spatial 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 Sub-regional Workshop on Collection and Dissemination of Socio-economic Data from
Population and Housing Censuses
New Delhi, India, 28-30 May, 2012
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 Sub-regional Workshop on Collection and Dissemination of Socio-economic Data from
Population and Housing Censuses
New Delhi, India, 28-30 May, 2012
Identification of a set of areas
United Nations Sub-regional Workshop on Collection and Dissemination of Socio-economic Data from
Population and Housing Censuses
New Delhi, India, 28-30 May, 2012
United Nations Sub-regional Workshop on Collection and Dissemination of Socio-economic Data from
Population and Housing Censuses
New Delhi, India, 28-30 May, 2012
“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 Sub-regional Workshop on Collection and Dissemination of Socio-economic Data from
Population and Housing Censuses
New Delhi, India, 28-30 May, 2012
Travelling the Distance: A GPS-based Study of the Access to Birth
Registration Services in Latin America and the Caribbean

Inter-American Development, March 2012

Using GPS-collected data, the study examines how the distance from
households to civil registries affects the probability of birth
registration of children aged 0 to 4 (Countries: Bolivia, Dominican
Republic and Peru)

Confirmation: Distance and location are crucial determinants of many
households’ decisions:


Example of results: increasing the distance to the nearest registry office
by 25 km is associated with a 4 percentage point increase in the
probability of not registering a child’s birth in Bolivia, and 12 percentage
points in the Dominican Republic.
Link:http://idbdocs.iadb.org/wsdocs/getdocument.aspx?docnu
m=36749514
United Nations Sub-regional Workshop on Collection and Dissemination of Socio-economic Data from
Population and Housing Censuses
New Delhi, India, 28-30 May, 2012
“is near to”: Buffer Operations
•
Point buffer
•
Affected area
around a Hospital
•
Catchement area of
a water source
United Nations Sub-regional Workshop on Collection and Dissemination of Socio-economic Data from
Population and Housing Censuses
New Delhi, India, 28-30 May, 2012
Buffer Operations…
•
Line buffer
•
How many people live near the polluted river?
•
What is the area impacted by highway noise?
United Nations Sub-regional Workshop on Collection and Dissemination of Socio-economic Data from
Population and Housing Censuses
New Delhi, India, 28-30 May, 2012
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 Sub-regional Workshop on Collection and Dissemination of Socio-economic Data from
Population and Housing Censuses
New Delhi, India, 28-30 May, 2012
“ is within”: point in polygon
•
Which of the cholera cases are within the
containment area
United Nations Sub-regional Workshop on Collection and Dissemination of Socio-economic Data from
Population and Housing Censuses
New Delhi, India, 28-30 May, 2012
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 Sub-regional Workshop on Collection and Dissemination of Socio-economic Data from
Population and Housing Censuses
New Delhi, India, 28-30 May, 2012
Spatial aggregation
 Example of Spatial aggregation:

fusion of many provinces constituting an
economic region
United Nations Sub-regional Workshop on Collection and Dissemination of Socio-economic Data from
Population and Housing Censuses
New Delhi, India, 28-30 May, 2012
Spatial data transformation: interpolation
Example: Based on a set of station precipitation surface estimates, we
can create a raster surface that shows rainfall in the entire region
13.5
12.7
20.1
26.0
27.2
15.9
24.5
26.1
United Nations Sub-regional Workshop on Collection and Dissemination of Socio-economic Data from
Population and Housing Censuses
New Delhi, India, 28-30 May, 2012
Example of linear interpolation creating contours
United Nations Sub-regional Workshop on Collection and Dissemination of Socio-economic Data from
Population and Housing Censuses
New Delhi, India, 28-30 May, 2012
Areas of influence

Commuting distances:
daily commuters flow
United Nations Sub-regional Workshop on Collection and Dissemination of Socio-economic Data from
Population and Housing Censuses
New Delhi, India, 28-30 May, 2012
Modelling: smoothing

Evolution of the
population
beetwen two
censuses
United Nations Sub-regional Workshop on Collection and Dissemination of Socio-economic Data from
Population and Housing Censuses
New Delhi, India, 28-30 May, 2012
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 Sub-regional Workshop on Collection and Dissemination of Socio-economic Data from
Population and Housing Censuses
New Delhi, India, 28-30 May, 2012
Location-allocation problems
 Site selection
 Optimal allocation
 Multicriteria Analysis
United Nations Sub-regional Workshop on Collection and Dissemination of Socio-economic Data from
Population and Housing Censuses
New Delhi, India, 28-30 May, 2012
Different Geographies
 A geography for data collection:

EA level or even dwelling level
 Another geography for data dissemination:

Aggregated level (confidentiality)
United Nations Sub-regional Workshop on Collection and Dissemination of Socio-economic Data from
Population and Housing Censuses
New Delhi, India, 28-30 May, 2012
Uses of Graphs: Enriching the Understanding of GIS
Data Sets





Exploratory Spatial Data Analysis
Linked Maps, Graphs & Tables
Dynamic Feature Selection
Animation
Visualization over Time
United Nations Sub-regional Workshop on Collection and Dissemination of Socio-economic Data from
Population and Housing Censuses
New Delhi, India, 28-30 May, 2012
GIS capabilities: Visualization
United Nations Sub-regional Workshop on Collection and Dissemination of Socio-economic Data from
Population and Housing Censuses
New Delhi, India, 28-30 May, 2012
Web Mapping Architecture
(Ref. B. Dickinson)
 Mapping applications are accessed through standard web
technologies to meet the needs of a specific business
process or user.
Clients
KML/
SOAP
Web Services
KML/
SOAP
Data Stores
United Nations Sub-regional Workshop on Collection and Dissemination of Socio-economic Data from
Population and Housing Censuses
New Delhi, India, 28-30 May, 2012
Web Map Services

A Web Map Service (WMS) is a standard protocol for serving
georeferenced map images over the Internet that are generated by
a map server using data from a GIS database. (developed by OGC)

WMS is a widely supported format for maps and GIS data accessed
via the Internet and loaded into client side GIS software

Most GIS software support WMS

GIS APIs
United Nations Sub-regional Workshop on Collection and Dissemination of Socio-economic Data from
Population and Housing Censuses
New Delhi, India, 28-30 May, 2012
Cont…
 Client technology: from “dumb” mapping to “smart”
mapping application - The overall trend for web-based
mapping is with more highly interactive, user-driven
client interfaces as well as the desire by the general
internet user to see the underlying data as a 3D
environment and not a 2D flat-earth map.
 Server-technology: service-oriented architecture
(SOA) and broad spatial capabilities
United Nations Sub-regional Workshop on Collection and Dissemination of Socio-economic Data from
Population and Housing Censuses
New Delhi, India, 28-30 May, 2012
Dissemination: web service application
United Nations Sub-regional Workshop on Collection and Dissemination of Socio-economic Data from
Population and Housing Censuses
New Delhi, India, 28-30 May, 2012
45
Digital Data Dissemination Strategy
 The wide range of potential users of disaggregated census
data means that the NSO needs to pursue a multi-leveled
digital data dissemination strategy.
 Broadly, we can distinguish between the following types of
users:
 Advanced GIS users
 Computer literate users
 Novice users
United Nations Sub-regional Workshop on Collection and Dissemination of Socio-economic Data from
Population and Housing Censuses
New Delhi, India, 28-30 May, 2012
Handbook on Geospatial Infrastructure
in Support of Census Activities
- Audiences: managerial and
technical
- “Cook-book” to illustrate the role
of geospatial technology in each
step of the census process
- Each country has to find its own
best possible solution
- Available in the six UN official
languages
http://unstats.un.org/unsd/demographic/standmeth/handbooks/default.htm
United Nations Sub-regional Workshop on Collection and Dissemination of Socio-economic Data from
Population and Housing Censuses
New Delhi, India, 28-30 May, 2012
Conclusions
 Geographic Database/Topology
 Variety of techniques: buffering, overlay, modelling…:

Although spatial analysis is sometimes used during the
enumeration phase (clustering, for example, can aid in
identifying housing units to be canvassed), the main use of
spatial analysis is for census products and services
 GIS: Decision making tool
 Web-based applications and services
United Nations Sub-regional Workshop on Collection and Dissemination of Socio-economic Data from
Population and Housing Censuses
New Delhi, India, 28-30 May, 2012
…Conclusions
 Consider the Census Geography Programme as a
continuous process
 Adapt best practices to suit specific census requirements
 Partner with other stakeholders (the public and private
sector) in order to



Build the NSDI
Work jointly on coding efforts
Produce value added products – higher demand for census
data
United Nations Sub-regional Workshop on Collection and Dissemination of Socio-economic Data from
Population and Housing Censuses
New Delhi, India, 28-30 May, 2012
THANK YOU!
United Nations Sub-regional Workshop on Collection and Dissemination of Socio-economic Data from
Population and Housing Censuses
New Delhi, India, 28-30 May, 2012