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ISPRS Int. J. Geo-Inf. 2015, 4(4), 2561-2582; doi:10.3390/ijgi4042561

Data Integration for Climate Vulnerability Mapping in West Africa

Center for International Earth Science Information Network, The Earth Institute at Columbia University, P.O. Box 1000, Palisades, NY 10964, USA
These authors contributed equally to this work.
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Academic Editors: Christoph Aubrecht and Wolfgang Kainz
Received: 20 June 2015 / Revised: 27 October 2015 / Accepted: 9 November 2015 / Published: 19 November 2015
(This article belongs to the Special Issue Geoinformation for Disaster Risk Management)
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Abstract

Vulnerability mapping reveals areas that are likely to be at greater risk of climate-related disasters in the future. Through integration of climate, biophysical, and socioeconomic data in an overall vulnerability framework, so-called “hotspots” of vulnerability can be identified. These maps can be used as an aid to targeting adaptation and disaster risk management interventions. This paper reviews vulnerability mapping efforts in West Africa conducted under the USAID-funded African and Latin American Resilience to Climate Change (ARCC) project. The focus is on the integration of remotely sensed and socioeconomic data. Data inputs included a range of sensor data (e.g., MODIS NDVI, Landsat, SRTM elevation, DMSP-OLS night-time lights) as well as high-resolution poverty, conflict, and infrastructure data. Two basic methods were used, one in which each layer was transformed into standardized indicators in an additive approach, and another in which remote sensing data were used to contextualize the results of composite indicators. We assess the benefits and challenges of data integration, and the lessons learned from these mapping exercises. View Full-Text
Keywords: climate change; exposure; vulnerability; risk modeling for decision support climate change; exposure; vulnerability; risk modeling for decision support
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

de Sherbinin, A.; Chai-Onn, T.; Jaiteh, M.; Mara, V.; Pistolesi, L.; Schnarr, E.; Trzaska, S. Data Integration for Climate Vulnerability Mapping in West Africa. ISPRS Int. J. Geo-Inf. 2015, 4, 2561-2582.

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