This document discusses a study that used analysis of mobile phone call data records to estimate population distribution in Cote d'Ivoire. The study analyzed calling patterns from a dataset of 500,000 anonymized call records to attribute populations to base stations. At a national level, the results were roughly consistent with other datasets, reproducing general patterns of population distribution. At an urban level, the analysis provided insights into inner-city population distributions, though corrections may be needed due to non-homogeneous phone usage. The study demonstrated the potential of using call data records for population modeling but noted challenges around data availability, privacy, and accounting for socioeconomic factors.

1. Slide: 1
“Calling Abidjan”
Estimating population distribution
through analysis of
mobile phone call data records
Harald Sterly1, Benjamin Hennig2, Kouassi Dongo3
1Institute of Geography, University of Cologne (h.sterly@uni-koeln.de)
2School of Geography and the Environment, University of Oxford (benjamin.hennig@ouce.ox.ac.uk)
3Université de Cocody-Abidjan / Centre Suisse de Recherches Scientifiques en Côte d'Ivoire, CSRS
(kouassi.dongo@csrs.ci)

2. Overview
Slide: 2
• Urbanisation in Africa – an information
challenge?
• Data
• Approach
• Results
• Discussion – Conclusion
Harald Sterly
Benjamin Hennig
Kouassi Dongo
Calling Abidjan
Estimating populatiopn distribution through analysis of mobile phone call data records
Deutscher Kongress für Geogrtaphie, 1 October 2015, Berlin (Germany)

3. Urbanisation in Africa: a
considerable challenge
Slide: 3
(Source: UN 2010)
• Cities in low and middle income countries to
accomodate 89% of global population
increase (UNDESA 2012)
• High urban growth in
Subsahara-Africa: 3,7%
(2005-10)
• Côte d‘Ivoire: high urban
poverty rates, ~2/3 in low-
income housing
Harald Sterly
Benjamin Hennig
Kouassi Dongo
Calling Abidjan
Estimating populatiopn distribution through analysis of mobile phone call data records
Deutscher Kongress für Geogrtaphie, 1 October 2015, Berlin (Germany)

4. Urbanisation: also an
information challenge?
Slide: 4
• Limited resources for more sustainable and
equitable urban development
• Very limited knowledge on population
distribution & dynamics
• Côte d‘Ivoire: last census 1998, latest official
national estimates 2008
 need for actual data on local level
Harald Sterly
Benjamin Hennig
Kouassi Dongo
Calling Abidjan
Estimating populatiopn distribution through analysis of mobile phone call data records
Deutscher Kongress für Geogrtaphie, 1 October 2015, Berlin (Germany)

5. Urbanisation and Visualisation
Slide: 5
Urban Slums
City Living
City Growth
Harald Sterly
Benjamin Hennig
Kouassi Dongo
Calling Abidjan
Estimating populatiopn distribution through analysis of mobile phone call data records
Deutscher Kongress für Geogrtaphie, 1 October 2015, Berlin (Germany)

6. Mobile phone use
Slide: 6
Harald Sterly
Benjamin Hennig
Kouassi Dongo
Calling Abidjan
Estimating populatiopn distribution through analysis of mobile phone call data records
Deutscher Kongress für Geogrtaphie, 1 October 2015, Berlin (Germany)

7. Slide: 7
Harald Sterly
Benjamin Hennig
Kouassi Dongo
Calling Abidjan
Estimating populatiopn distribution through analysis of mobile phone call data records
Deutscher Kongress für Geogrtaphie, 1 October 2015, Berlin (Germany)

8. Proof of Concept
• Deduce information on
population distribution from
existing data (mobile phone call
data records)
• Use standard hardware and
open source software
• approach by non-experts for big
data analysis (social
geographers, urban planner)
Slide: 8
Harald Sterly
Benjamin Hennig
Kouassi Dongo
Calling Abidjan
Estimating populatiopn distribution through analysis of mobile phone call data records
Deutscher Kongress für Geogrtaphie, 1 October 2015, Berlin (Germany)

9. The Dataset
„Data for Development“ (D4D)
Challenge (Orange Télécom
Côte d‘Ivoire)
• Anonymised call data records,
Base station, timestamp,
caller ID
• 500,000 Orange Télecom
users
• 1079 base stations
• 183 days
• 13 GB data
Slide: 9
Harald Sterly
Benjamin Hennig
Kouassi Dongo
Calling Abidjan
Estimating populatiopn distribution through analysis of mobile phone call data records
Deutscher Kongress für Geogrtaphie, 1 October 2015, Berlin (Germany)

10. Approach
• Analysis of diurnal patterns:
„being home“ = 7pm–5am
• Attribution of residence to
base stations (diurnal patterns,
highest number of calls in 14
days)
• Extrapolation to 21 Million
Ivorians (national level)
• Spatial attribution to base
stations (Voronoi polygons)
Slide: 10
Harald Sterly
Benjamin Hennig
Kouassi Dongo
Calling Abidjan
Estimating populatiopn distribution through analysis of mobile phone call data records
Deutscher Kongress für Geogrtaphie, 1 October 2015, Berlin (Germany)

11. Results - national
Slide: 11
• Roughly consistent
with AfriPoP and
Landscan data;
• Reproduces the
general patterns
• Urban areas:
overestimation of
population; rural areas:
underestimation
(differential usage)
CRD Analysis
Afripop
Harald Sterly
Benjamin Hennig
Kouassi Dongo
Calling Abidjan
Estimating populatiopn distribution through analysis of mobile phone call data records
Deutscher Kongress für Geogrtaphie, 1 October 2015, Berlin (Germany)

12. Results - national
Slide: 12
CRD Analysis
Afripop
Harald Sterly
Benjamin Hennig
Kouassi Dongo
Calling Abidjan
Estimating populatiopn distribution through analysis of mobile phone call data records
Deutscher Kongress für Geogrtaphie, 1 October 2015, Berlin (Germany)

13. Results - population
Slide: 13
Harald Sterly
Benjamin Hennig
Kouassi Dongo
Calling Abidjan
Estimating populatiopn distribution through analysis of mobile phone call data records
Deutscher Kongress für Geogrtaphie, 1 October 2015, Berlin (Germany)

14. Results - urban
Slide: 14
CRD AnalysisAfriPop data
Harald Sterly
Benjamin Hennig
Kouassi Dongo
Calling Abidjan
Estimating populatiopn distribution through analysis of mobile phone call data records
Deutscher Kongress für Geogrtaphie, 1 October 2015, Berlin (Germany)

15. Discussion
• Potential for improving knowledge on
inner-urban population distribution
(and dynamics)
• Non-homogeneity of subscription
and usage  socio-spatial correction
factors (calling patterns, service
provider, surveys)
• Data availability / accessibility
• Privacy
Slide: 15
Harald Sterly
Benjamin Hennig
Kouassi Dongo
Calling Abidjan
Estimating populatiopn distribution through analysis of mobile phone call data records
Deutscher Kongress für Geogrtaphie, 1 October 2015, Berlin (Germany)