The production of the AfriPop spatial datasets principally follows the methodologies outlined in Tatem et al and Linard et al. A full data and methodological description will be available soon, but brief details are provided below:

 

 

Mapping Populations

 

Through detailed mapping of settlements, and linkage of these settlement extents with gazetteer population numbers, the substantial majority of African residents can be mapped within settlements with good precision. Mapping of the remaining minority rural populations follows the approaches outlined in detail elsewhere. The settlement maps are used to refine land cover data, while local high resolution census data from across the continent is exploited to identify typical regional per-land cover class population densities, which are then applied to redistribute census counts to map human population distributions.

A Census Database

 

Previous AfriPop work showed the importance of detailed, contemporary census data in producing accurate population distribution datasets, irrespective of modelling approach. AfriPop has therefore made the construction of a unique GIS-linked database of census and official population estimate data a priority, targeting the most recent and spatially detailed datasets available. The figure below shows comparisons between the ages and spatial resolution of population data used in the construction of the Global Rural Urban Mapping Project (GRUMP) datasets versus AfriPop. A summary of the input census/population count datasets used as input to AfriPop are available here.

Comparison of the spatial and temporal characteristics of population data used in the construction of the Gridded Population of the World (GPW) version 3 and the Global Rural Urban Mapping Project (GRUMP) datasets (http://sedac.ciesin.columbia.edu/gpw/spreadsheets/GPW3_GRUMP_SummaryInformation_Oct05prod.xls) and AfriPop. A, B: Year of input population data. C, D: average spatial resolution (ASR) of input population data. The ASR measures the effective resolution of administrative units in kilometers. It is calculated as the square root of the land area divided by the number of administrative units.

False color Landsat ETM image of Kampala and surrounds, Uganda

Automated extraction of settlements from image

Mapping Settlements

 

The vast majority of people across Africa reside in settlements of varying sizes, therefore, the accurate mapping of settlements—from large cities to small villages—is important for identifying where populations reside within census units. AfriPop utilises satellite imagery for mapping settlements—specifically, 30m spatial resolution Landsat Enhanced Thematic Mapper (ETM) satellite imagery. For many countries, expert-opinion manual satellite imagery interpretation was used to map settlements. For other countries, the latest imagery of the regions of interest were acquired and subject to pre-processing and georegistration. For the country of interest, all spatially-referenced ancillary data available on settlement locations, land cover and infrastructure will be gathered and used to aid computer-automated classifiers in identifying the unique multispectral reflectance and, where appropriate, image texture signatures of settlements within a specific land cover region. These signatures were then used with separate training data and visual interpretation to map settlements and assess mapping accuracies. The figures below show example settlement extent extraction for an area of Uganda. See Tatem et al for full details. A summary of the input settlement datasets used as input to AfriPop are available here.

Visual comparisons of AfriPop with GRUMP and LandScan gridded population datasets. Upper figures show the North-East region of Guinea, along the Niger river using A. AfriPop, B. GRUMP and C. LandScan. Lower figures show the region around Dar es Salaam, United Republic of Tanzania, using A. AfriPop, B. GRUMP and C. LandScan.