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About
Dear User,
Settlement dynamics have profoundly reshaped the social and economic geography of West Africa over the past 60 years. Urbanisation and the development of dense urban networks are the most spectacular demonstrations of population redistribution. To better analyse and describe these dynamics at the regional level the Sahel and West Africa Club Secretariat (SWAC/OECD) has used new and homogenous urbanisation data and modeling.
The data presented here has been compiled from various sources, harmonised and further developed over the course of a two-year programme on “Settlement, market, and food security”. The final report concludes a series of studies on the West African settlement and market dynamics and presents key issues for policy makers. The report is soon available on the SWAC website.

The data of the Statistical, Mapping and Regional Analysis Tool — SMART illustrate these dynamics and transformations. SMART allows you to map, follow and compare key settlement data for the 17 West African countries and country groups between 1950 and 2050. By linking this data with agricultural performance it also provides examples on how settlement dynamics change the way we interpret past trends and assess future potential. We consider SMART as work in progress and encourage users to provide feedback, ideas and suggestions to help us further develop and broaden it. Data can be downloaded as excel file; graphics and maps are available as image files.
Enjoy using SMART!

Laurent BOSSARD, Director, Sahel and West Africa Club Secretariat
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Urban Population
Total Population in million
City size by population
20000 — 50000
50000 — 100000
100000 — 350000
350000 — 1 million
1 — 2 millions
> 2 millions
1
2
3
Urban Network Urban Network Urban Network Urban Network Urban Network Urban Network
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About the data
The data presented in this tool illustrates how settlement dynamics have emerged and changed over time, and covers the period from 1950 to 2050. It helps to understand the region’s shift between rural and urban population and its effect on the ratio between agricultural and non-agricultural population. The research draws from multiple sources and the data has been harmonised by the authors to provide a coherent picture of the development in West Africa. For more details on the methodology for this harmonisation as well as background information you can access the series of notes that preceded the report. SMART is largely drawing on West African urbanisation data produced by Africapolis (2008) which is based on satellite and aerial imagery as well as census data to estimate the number of agglomerated people in 1950, 1960, 1970, 1980, 1990 and in 2000.

About the tool
This data tool was realised in cooperation with Thomas Ranker of Red Rooster Mobile who developed this tool and designed by Daniel Krüger of grand krü.

Data Sources and Methodology
Mali
19xx
Inhabitants
xxxxx
19xx
Urban Population
xxx
Total Population
xxx
Rural Population
URBAN
Urban network
POPULATION
Total population
Urban population
Rural population
Level of urbanisation
Ratio urban/rural
Agricultural population
Non agricultural population
Ratio non-agri pop/agri pop
Rural non-agriultural pop
Urban agricultural pop
Population growth
Urban population growth
Rural population growth
Agricultural population growth
Non-agricultural pop growth
AGRICULTURE
Agricultural production
Food imports
Imports per capita
Imports per urban
Harvested area
Area/agricultural pop
Yield
Agricultural productivity
Production growth
Import growth
Imports per capita growth
Imports per urban growth
Yield growth
Productivity growth
some country
some year
some value