Modelling social vulnerability in sub-Saharan West Africa using a geographical information system

In recent times, disasters and risk management have gained significant attention, especially with increasing awareness of the risks and increasing impact of natural and other hazards especially in the developing world. Vulnerability, the potential for loss of life or property from disaster, has biop...

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Main Authors: Olanrewaju Lawal, Samuel B. Arokoyu
Format: Article
Language:English
Published: AOSIS 2015-05-01
Series:Jàmbá
Subjects:
Online Access:https://jamba.org.za/index.php/jamba/article/view/155
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author Olanrewaju Lawal
Samuel B. Arokoyu
author_facet Olanrewaju Lawal
Samuel B. Arokoyu
author_sort Olanrewaju Lawal
collection DOAJ
description In recent times, disasters and risk management have gained significant attention, especially with increasing awareness of the risks and increasing impact of natural and other hazards especially in the developing world. Vulnerability, the potential for loss of life or property from disaster, has biophysical or social dimensions. Social vulnerability relates to societal attributes which has negative impacts on disaster outcomes. This study sought to develop a spatially explicit index of social vulnerability, thus addressing the dearth of research in this area in sub-Saharan Africa. Nineteen variables were identified covering various aspects. Descriptive analysis of these variables revealed high heterogeneity across the South West region of Nigeria for both the state and the local government areas (LGAs). Feature identification using correlation analysis identified six important variables. Factor analysis identified two dimensions, namely accessibility and socioeconomic conditions, from this subset. A social vulnerability index (SoVI) showed that Ondo and Ekiti have more vulnerable LGAs than other states in the region. About 50% of the LGAs in Osun and Ogun have a relatively low social vulnerability. Distribution of the SoVI shows that there are great differences within states as well as across regions. Scores of population density, disability and poverty have a high margin of error in relation to mean state scores. The study showed that with a geographical information system there are opportunities to model social vulnerability and monitor its evolution and dynamics across the continent.
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spelling doaj.art-09df0dd93f684434b905cb7c5f8a19ac2022-12-22T01:19:36ZengAOSISJàmbá1996-14212072-845X2015-05-0171e1e1110.4102/jamba.v7i1.155106Modelling social vulnerability in sub-Saharan West Africa using a geographical information systemOlanrewaju Lawal0Samuel B. Arokoyu1Department of Geography and Environmental Management, Centre for Disaster Risk Management and Development Studies, University of Port HarcourtDepartment of Geography and Environmental Management, Centre for Disaster Risk Management and Development Studies, University of Port HarcourtIn recent times, disasters and risk management have gained significant attention, especially with increasing awareness of the risks and increasing impact of natural and other hazards especially in the developing world. Vulnerability, the potential for loss of life or property from disaster, has biophysical or social dimensions. Social vulnerability relates to societal attributes which has negative impacts on disaster outcomes. This study sought to develop a spatially explicit index of social vulnerability, thus addressing the dearth of research in this area in sub-Saharan Africa. Nineteen variables were identified covering various aspects. Descriptive analysis of these variables revealed high heterogeneity across the South West region of Nigeria for both the state and the local government areas (LGAs). Feature identification using correlation analysis identified six important variables. Factor analysis identified two dimensions, namely accessibility and socioeconomic conditions, from this subset. A social vulnerability index (SoVI) showed that Ondo and Ekiti have more vulnerable LGAs than other states in the region. About 50% of the LGAs in Osun and Ogun have a relatively low social vulnerability. Distribution of the SoVI shows that there are great differences within states as well as across regions. Scores of population density, disability and poverty have a high margin of error in relation to mean state scores. The study showed that with a geographical information system there are opportunities to model social vulnerability and monitor its evolution and dynamics across the continent.https://jamba.org.za/index.php/jamba/article/view/155Social VulnerabilityGISdisaster risk managementSouth West Geopolitical Zonespatial modellingvulnerability assessmentSocial vulnerability index
spellingShingle Olanrewaju Lawal
Samuel B. Arokoyu
Modelling social vulnerability in sub-Saharan West Africa using a geographical information system
Jàmbá
Social Vulnerability
GIS
disaster risk management
South West Geopolitical Zone
spatial modelling
vulnerability assessment
Social vulnerability index
title Modelling social vulnerability in sub-Saharan West Africa using a geographical information system
title_full Modelling social vulnerability in sub-Saharan West Africa using a geographical information system
title_fullStr Modelling social vulnerability in sub-Saharan West Africa using a geographical information system
title_full_unstemmed Modelling social vulnerability in sub-Saharan West Africa using a geographical information system
title_short Modelling social vulnerability in sub-Saharan West Africa using a geographical information system
title_sort modelling social vulnerability in sub saharan west africa using a geographical information system
topic Social Vulnerability
GIS
disaster risk management
South West Geopolitical Zone
spatial modelling
vulnerability assessment
Social vulnerability index
url https://jamba.org.za/index.php/jamba/article/view/155
work_keys_str_mv AT olanrewajulawal modellingsocialvulnerabilityinsubsaharanwestafricausingageographicalinformationsystem
AT samuelbarokoyu modellingsocialvulnerabilityinsubsaharanwestafricausingageographicalinformationsystem