High resolution population maps for low income nations: combining land cover and census in East Africa.

<h4>Background</h4>Between 2005 and 2050, the human population is forecast to grow by 2.7 billion, with the vast majority of this growth occurring in low income countries. This growth is likely to have significant social, economic and environmental impacts, and make the achievement of in...

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Main Authors: Andrew J Tatem, Abdisalan M Noor, Craig von Hagen, Antonio Di Gregorio, Simon I Hay
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2007-12-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0001298
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spelling doaj-496413b20b71458dac0787275cd1a0352021-03-03T22:26:44ZengPublic Library of Science (PLoS)PLoS ONE1932-62032007-12-01212e129810.1371/journal.pone.0001298High resolution population maps for low income nations: combining land cover and census in East Africa.Andrew J TatemAbdisalan M NoorCraig von HagenAntonio Di GregorioSimon I Hay<h4>Background</h4>Between 2005 and 2050, the human population is forecast to grow by 2.7 billion, with the vast majority of this growth occurring in low income countries. This growth is likely to have significant social, economic and environmental impacts, and make the achievement of international development goals more difficult. The measurement, monitoring and potential mitigation of these impacts require high resolution, contemporary data on human population distributions. In low income countries, however, where the changes will be concentrated, the least information on the distribution of population exists. In this paper we investigate whether satellite imagery in combination with land cover information and census data can be used to create inexpensive, high resolution and easily-updatable settlement and population distribution maps over large areas.<h4>Methodology/principal findings</h4>We examine various approaches for the production of maps of the East African region (Kenya, Uganda, Burundi, Rwanda and Tanzania) and where fine resolution census data exists, test the accuracies of map production approaches and existing population distribution products. The results show that combining high resolution census, settlement and land cover information is important in producing accurate population distribution maps.<h4>Conclusions</h4>We find that this semi-automated population distribution mapping at unprecedented spatial resolution produces more accurate results than existing products and can be undertaken for as little as $0.01 per km(2). The resulting population maps are a product of the Malaria Atlas Project (MAP: http://www.map.ox.ac.uk) and are freely available.https://doi.org/10.1371/journal.pone.0001298
collection DOAJ
language English
format Article
sources DOAJ
author Andrew J Tatem
Abdisalan M Noor
Craig von Hagen
Antonio Di Gregorio
Simon I Hay
spellingShingle Andrew J Tatem
Abdisalan M Noor
Craig von Hagen
Antonio Di Gregorio
Simon I Hay
High resolution population maps for low income nations: combining land cover and census in East Africa.
PLoS ONE
author_facet Andrew J Tatem
Abdisalan M Noor
Craig von Hagen
Antonio Di Gregorio
Simon I Hay
author_sort Andrew J Tatem
title High resolution population maps for low income nations: combining land cover and census in East Africa.
title_short High resolution population maps for low income nations: combining land cover and census in East Africa.
title_full High resolution population maps for low income nations: combining land cover and census in East Africa.
title_fullStr High resolution population maps for low income nations: combining land cover and census in East Africa.
title_full_unstemmed High resolution population maps for low income nations: combining land cover and census in East Africa.
title_sort high resolution population maps for low income nations: combining land cover and census in east africa.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2007-12-01
description <h4>Background</h4>Between 2005 and 2050, the human population is forecast to grow by 2.7 billion, with the vast majority of this growth occurring in low income countries. This growth is likely to have significant social, economic and environmental impacts, and make the achievement of international development goals more difficult. The measurement, monitoring and potential mitigation of these impacts require high resolution, contemporary data on human population distributions. In low income countries, however, where the changes will be concentrated, the least information on the distribution of population exists. In this paper we investigate whether satellite imagery in combination with land cover information and census data can be used to create inexpensive, high resolution and easily-updatable settlement and population distribution maps over large areas.<h4>Methodology/principal findings</h4>We examine various approaches for the production of maps of the East African region (Kenya, Uganda, Burundi, Rwanda and Tanzania) and where fine resolution census data exists, test the accuracies of map production approaches and existing population distribution products. The results show that combining high resolution census, settlement and land cover information is important in producing accurate population distribution maps.<h4>Conclusions</h4>We find that this semi-automated population distribution mapping at unprecedented spatial resolution produces more accurate results than existing products and can be undertaken for as little as $0.01 per km(2). The resulting population maps are a product of the Malaria Atlas Project (MAP: http://www.map.ox.ac.uk) and are freely available.
url https://doi.org/10.1371/journal.pone.0001298
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