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Citation Information

Type Journal Article - Geospatial Health
Title Improving AfriPop dataset with settlement extents extracted from RapidEye for the border region comprising South-Africa, Swaziland and Mozambique
Author(s)
Volume 10
Issue 2
Publication (Day/Month/Year) 2015
Page numbers 48-56
URL http://www.geospatialhealth.net/index.php/gh/article/download/336/320
Abstract
For modelling the spatial distribution of malaria incidence, accurate
and detailed information on population size and distribution are of significant
importance. Different, global, spatial, standard datasets of
population distribution have been developed and are widely used.
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. The AfriPop project, launched in July 2009, was initiated
with the aim of producing detailed, contemporary and easily
updatable population distribution datasets for the whole of Africa.
High-resolution satellite sensors can help to further improve this
dataset through the generation of high-resolution settlement layers at
greater spatial details. 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. 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. The
2007 and 2011 population datasets are freely available as a product of
the MALAREO project and can be downloaded from the project website

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