Can we spot a neighborhood from the air? Defining neighborhood structure in Accra, Ghana
Can we spot a neighborhood from the air? Defining neighborhood structure in Accra, Ghana
Slums are home to a large fraction of urban residents in cities of developing nations, but little attempt has been made to go beyond a simple slum/non-slum dichotomy, nor to identify slums more quantitatively than through local reputation. We use census data from Accra, Ghana, to create an index that applies the UN-Habitat criteria for a place to be a slum. We use this index to identify neighborhoods on a continuum of slum characteristics and on that basis are able to locate the worst slums in Accra. These do include the areas with a local reputation for being slums, lending qualitative validation to the index. We show that slums also have footprints that can be identified from data classified from satellite imagery. However, variability among slums in Accra is also associated with some variability in the land cover characteristics of slums.
9-22
Weeks, John R.
78515864-f87d-4ef8-8801-df8a8fd3801d
Hill, Allan
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Stow, Douglas
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Getis, Arthur
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Fugate, Debbie
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2007
Weeks, John R.
78515864-f87d-4ef8-8801-df8a8fd3801d
Hill, Allan
5b17aa71-0c14-4fbf-8bc9-807c8294d4ae
Stow, Douglas
7ce2fd13-6153-489c-bd81-ca0bb45db966
Getis, Arthur
e81b5dab-893f-495c-91a6-335c263878e2
Fugate, Debbie
dd3a9c4c-e127-4635-8ddb-c263fffb4be0
Weeks, John R., Hill, Allan, Stow, Douglas, Getis, Arthur and Fugate, Debbie
(2007)
Can we spot a neighborhood from the air? Defining neighborhood structure in Accra, Ghana.
GeoJournal, 69 (1-2), .
(doi:10.1007/s10708-007-9098-4).
Abstract
Slums are home to a large fraction of urban residents in cities of developing nations, but little attempt has been made to go beyond a simple slum/non-slum dichotomy, nor to identify slums more quantitatively than through local reputation. We use census data from Accra, Ghana, to create an index that applies the UN-Habitat criteria for a place to be a slum. We use this index to identify neighborhoods on a continuum of slum characteristics and on that basis are able to locate the worst slums in Accra. These do include the areas with a local reputation for being slums, lending qualitative validation to the index. We show that slums also have footprints that can be identified from data classified from satellite imagery. However, variability among slums in Accra is also associated with some variability in the land cover characteristics of slums.
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Published date: 2007
Organisations:
Social Statistics & Demography
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Local EPrints ID: 340412
URI: http://eprints.soton.ac.uk/id/eprint/340412
ISSN: 0343-2521
PURE UUID: cae4593e-4d5a-4c71-9504-002c3efa43a4
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Date deposited: 21 Jun 2012 09:20
Last modified: 15 Mar 2024 03:38
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Author:
John R. Weeks
Author:
Douglas Stow
Author:
Arthur Getis
Author:
Debbie Fugate
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