# Introduction

Pacific Island Countries (PICs) are often characterized as being both remote (in a global context) and highly dispersed, but within each country there is enormous variation in the remoteness of individual communities, and the extent to which communities are clustered or dispersed from one another. This paper seeks to better understand, and to empirically measure, the nature of dispersion and remoteness within individual PICs.

This paper defines a new measure of local-area population remoteness which is highly sensitive to variation in settlement patterns. Remoteness of a community is calculated as the population-weighted average distance between the community of interest, and all communities across the country. It is designed to be evaluated using commonly available population census data. A community is measured to be more remote if it is home to a smaller share of the population, relative to other communities further afield. It is also sensitive to the distance between the community of interest and any other community (in particular, a community is measured to be more remote, the more distant it is from large population centers). The remoteness measure for a particular community is unaffected by the overall population level of the country as a whole.

Our new measures of community-level remoteness can be aggregated to derive country-level indicators of (i) the geographical scale of population dispersion, and (ii) a dispersion-adjusted measure of population density, or inversely, sparsity. The geographical scale of dispersion is defined as the population-weighted average remoteness. This indicator is again highly sensitive to variation in settlement patterns (unlike more macro measures of geographical dispersion, such as the size of a country’s Exclusive Economic Zone). The dispersion indicator will be higher when a larger share of the population live in remote communities. Like the community-level remoteness indicator, the dispersion indicator is populationneutral, and unaffected by the overall level of a country’s population. The dispersion-adjusted measure of population density is defined as being proportional to the country’s population divided by the square of the dispersion indicator (with the square operation applied to transform the distance-based dispersion measure to an area-equivalent). It’s inverse captures population sparsity. This indicator is again highly sensitive to population settlement patterns (in contrast to calculations of the country’s average population density).

In this paper, we calculate the local-area remoteness measures, and country-level dispersion and sparsity indicators for eight case-study PICs, relying on census data collected by country National Statistics Offices and made available through the Pacific Community (SPC) PopGIS platform. Our estimates of community remoteness are correlated with local area socio-economic characteristics (the link between remoteness and socio-economic characteristics is explored more comprehensively in a companion piece<sup>2</sup> to this work). At the country level, our indicators emphasize the enormity of the geographical scale of dispersion in Kiribati and the Federated States of Micronesia (FSM); residents live an average of around 650-700km from the rest of the population. The populations of Solomon Islands, Vanuatu and Republic of Marshall Islands (RMI) and are less widely dispersed, with people living an average of around 250km from the rest of the population. The populations of Fiji, Tonga and Tuvalu are more concentrated still, with people living on average around 100-150km from the rest of the population. This dispersion indicator is a population-

> 2 World Bank, 2019. ‘Socio-economic analysis: A spatial analysis of population and housing census data’, a background paper prepared for _A Review of Spatial Development Issues in the Pacific Islands Countries_ (P166346).

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