Views Read Edit View history. In the present study, the settlement extents included in the MALAREO land use classification were used to generate an enhanced and updated version of the AfriPop dataset for the study area covering southern Mozambique, eastern Swaziland and the malarious part of KwaZulu-Natal in South Africa. Different, global, spatial, standard datasets of population distribution have been developed and are widely used. This page was last edited on 4 September , at The AfriPop project, launched in July , was initiated with the aim of producing detailed, contemporary and easily updatable population distribution datasets for the whole of Africa.
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Novel approaches to extracting detailed spatial data on settlements from satellite imagery [1] have been combined with contemporary detailed census data and land cover to map population densities across sub-Saharan Africa at unprecedented levels of detail.
The AfriPop project, launched in Julywas initiated with the aim of producing detailed, contemporary and easily updatable population distribution datasets for the whole of Africa. Retrieved afripol " https: The and population datasets are freely available as a product of the MALAREO project and can be downloaded from the project website.
Views Read Edit View history.
The AfriPop project was initiated in July with an aim of producing detailed and freely-available population distribution maps for the sfripop of sub-Saharan Africa. For modelling the spatial distribution of malaria incidence, accurate and detailed information on population size and distribution are of significant importance. Logo of the AfriPop Project.
The AfriPop Project - Wikipedia
From Wikipedia, the free encyclopedia. High-resolution satellite sensors can help to further improve this dataset through the generation of high-resolution settlement layers at greater spatial details. By using this site, you agree to the Terms of Use and Privacy Policy.
International Journal of Health Geographics.
However, most of them are not up-to-date and the low spatial resolution of the input census data has limitations for contemporary, national- scale analyses. In the present study, the settlement extents included in the MALAREO land use classification were used to generate an enhanced and updated version of the AfriPop dataset for the study area covering southern Mozambique, eastern Swaziland and the malarious part of KwaZulu-Natal in South Africa. Different, global, spatial, standard datasets of population distribution have been developed and are widely used.
Remote Sensing of Environment.
Results show that it is possible to easily produce a detailed and updated population distribution dataset applying the AfriPop modelling approach with the use of high-resolution settlement layers and population growth rates. High resolution, contemporary data on human population distributions are a prerequisite for the accurate measurement of afgipop impacts of population growth, for monitoring changes and for planning interventions.
This page was last agripop on 4 Septemberat The AfriPop team have assembled a unique spatial database of linked information on contemporary census data across Africa, satellite-imagery derived settlement maps and land cover information.
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