Using Information on Settlement Patterns to Improve the Spatial Distribution of Population in Coastal Impact Assessments.

Merkens, Jan-Ludolf and Vafeidis, A. T. (2018) Using Information on Settlement Patterns to Improve the Spatial Distribution of Population in Coastal Impact Assessments. Open Access Sustainability, 10 (9). p. 3170. DOI 10.3390/su10093170.

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Supplementary data:

Abstract

Broad-scale impact and vulnerability assessments are essential for informing decisions on long-term adaptation planning at the national, regional, or global level. These assessments rely on population data for quantifying exposure to different types of hazards. Existing population datasets covering the entire globe at resolutions of 2.5 degrees to 30 arc-seconds are based on information available at administrative-unit level and implicitly assume uniform population densities within these units. This assumption can lead to errors in impact assessments and particularly in coastal areas that are densely populated. This study proposes and compares simple approaches to regionalize population within administrative units in the German Baltic Sea region using solely information on urban extent from the Global Urban Footprint (GUF). Our results show that approaches using GUF can reduce the error in predicting population totals of municipalities by factor 2 to 3. When assessing exposed population, we find that the assumption of uniform population densities leads to an overestimation of 120% to 140%. Using GUF to regionalise population within administrative units reduce these errors by up to 50%. Our results suggest that the proposed simple modeling approaches can result in significantly improved distribution of population within administrative units and substantially improve the results of exposure analyses.

Document Type: Article
Keywords: spatial population; Global Urban Footprint; Dasymetric Mapping; coastal exposure; impact assessment; Baltic Sea
Research affiliation: Kiel University > Kiel Marine Science
OceanRep > The Future Ocean - Cluster of Excellence
Kiel University
Refereed: Yes
Open Access Journal?: Yes
DOI etc.: 10.3390/su10093170
ISSN: 2071-1050
Projects: Future Ocean
Date Deposited: 30 Jan 2019 12:49
Last Modified: 19 Mar 2019 09:32
URI: http://oceanrep.geomar.de/id/eprint/45612

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