Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2019 Sep 30;14(9):e0223249.
doi: 10.1371/journal.pone.0223249. eCollection 2019.

Coastal proximity of populations in 22 Pacific Island Countries and Territories

Neil L Andrew  1 , Phil Bright  2 , Luis de la Rua  2 , Shwu Jiau Teoh  3 , Mathew Vickers  1
Affiliations

Coastal proximity of populations in 22 Pacific Island Countries and Territories

Neil L Andrew et al. PLoS One. .

Abstract

The coastal zones of Small Island States are hotspots of human habitation and economic endeavour. In the Pacific region, as elsewhere, there are large gaps in understandings of the exposure and vulnerability of people in coastal zones. The 22 Pacific Countries and Territories (PICTs) are poorly represented in global analyses of vulnerability to seaward risks. We combine several data sources to estimate populations to zones 1, 5 and 10 km from the coastline in each of the PICTs. Regional patterns in the proximity of Pacific people to the coast are dominated by Papua New Guinea. Overall, ca. half the population of the Pacific resides within 10 km of the coast but this jumps to 97% when Papua New Guinea is excluded. A quarter of Pacific people live within 1 km of the coast, but without PNG this increases to slightly more than half. Excluding PNG, 90% of Pacific Islanders live within 5 km of the coast. All of the population in the coral atoll nations of Tokelau and Tuvalu live within a km of the ocean. Results using two global datasets, the SEDAC-CIESIN Gridded Population of the World v4 (GPWv4) and the Oak Ridge National Laboratory Landscan differed: Landscan under-dispersed population, overestimating numbers in urban centres and underestimating population in rural areas and GPWv4 over-dispersed the population. In addition to errors introduced by the allocation models of the two methods, errors were introduced as artefacts of allocating households to 1 km x 1 km grid cell data (30 arc-seconds) to polygons. The limited utility of LandScan and GPWv4 in advancing this analysis may be overcome with more spatially resolved census data and the inclusion of elevation above sea level as an important dimension of vulnerability.

PubMed Disclaimer

Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Zones used in analysis of coastal proximity of PICT populations.
Zones of 1km, 5km, and 10km (black lines) overlaid onto local census enumeration areas in south-west Santo Island, Vanuatu. Enumeration areas that crossed boundaries were assigned a single zone based on the centroid of the enumeration area.
Fig 2
Fig 2. Differences in allocation of houses to 1 km zone using Landscan and GAUL boundaries illustrated using ArcGIS.
(A) LandScan zone boundaries (brown) and associated 1 km zone miss-allocated many houses (green points) around inlet bays. (B) Allocations using GAUL land boundaries correctly allocated houses to zones.
Fig 3
Fig 3. Proportions of households within 1, 5 and 10 km from the coast in 22 PICTSs.
Proportions of households in each of the three buffers (see legend). See Table 1 for interpretation of the three digit ISO country codes.
Fig 4
Fig 4. Comparison of methods for disaggregating populations to enumeration areas and zones.
Known household locations shown in the top row (green) translated to high-precision estimates of population (second row), when population was known. LandScan estimates of population distribution overestimated populations in urban centres (row 3). GPWv4 did not favour urban populations, instead, the population was averaged across areas (row 4). The maps show the islands of Tongatapu (Tonga), Viti Levu (Fiji), and part of Upolu (Samoa).
Fig 5
Fig 5. Differences in allocation between global population datasets.
Percent differences between estimates of the population in (a) 1 km, (b) 5 km, and (c) 10 km buffer zone estimated by GPWv4 and LandScan and estimates using the census method.
See this image and copyright information in PMC

References

    1. Small C, Nicholls RJ. A global analysis of human settlement in coastal zones. J Coast Res [Internet]. 2003;19(3):584–99. Available from: http://www.jstor.org/stable/4299200
    1. Neumann B, Vafeidis AT, Zimmermann J, Nicholls RJ. Future coastal population growth and exposure to sea-level rise and coastal flooding—A global assessment. PLoS One [Internet]. 2015;10(3). Available from: 10.1371/journal.pone.0118571 - DOI - PMC - PubMed
    1. Mortreux C, Barnett J. Climate change, migration and adaptation in Funafuti, Tuvalu. Glob Environ Chang. 2009;19(1):105–12.
    1. Rudiak-Gould P. Promiscuous corroboration and climate change translation: A case study from the Marshall Islands. Glob Environ Chang [Internet]. Elsevier Ltd; 2012;22(1):46–54. Available from: 10.1016/j.gloenvcha.2011.09.011 - DOI
    1. Hau’ofa E. We are the ocean. A new Ocean Rediscovering our sea islands [Internet]. 2008;188 Available from: http://savageminds.org/wp-content/image-upload/our-sea-of-islands-epeli-...

Publication types