Spatial Variation in Seasonal Water Poverty Index for Laos: An Application of Geographically Weighted Principal Component Analysis

dc.contributorAalto-yliopistofi
dc.contributorAalto Universityen
dc.contributor.authorKallio, Markoen_US
dc.contributor.authorGuillaume, Josephen_US
dc.contributor.authorKummu, Mattien_US
dc.contributor.authorVirrantaus, Kirsi-Kanervaen_US
dc.contributor.departmentDepartment of Built Environmenten
dc.contributor.groupauthorGeoinformaticsen
dc.contributor.groupauthorWater and Environmental Engineeringen
dc.date.accessioned2018-02-09T10:02:13Z
dc.date.available2018-02-09T10:02:13Z
dc.date.embargoinfo:eu-repo/date/embargoEnd/2019-12-01en_US
dc.date.issued2018-12-01en_US
dc.description.abstractWater poverty, defined as insufficient water of adequate quality to cover basic needs, is an issue that may manifest itself in multiple ways. Extreme seasonal variation in water availability, such as in Laos, located in Monsoon Asia, results in large differences in water poverty conditions between dry and wet seasons. In this study, seasonal Water Poverty Indices (WPI) are developed for 8215 villages in Laos. WPI is a multidimensional composite index integrating five dimensions of water: resource availability, access to safe water, capacity to manage the resource, its use and environmental requirements. Principal Component Analysis (PCA) and Geographically Weighted PCA (GWPCA) were used to examine drivers of water poverty and to derive different weighting schemes. Three major drivers were identified: poverty, commercial/subsistence agriculture and village location. The least water poor areas are located around the capital city and along the Mekong River Valley while the highest water poverty is found in sparsely populated mountainous areas. Wet season WPI is on average more than 12 index points higher than in the dry season, but in some villages monsoon rain does not improve the situation. The results indicate large spatial and temporal differences in WPI within Laos. In analysis of WPI components, a mean–variance scaled PCA is recommended due to its capacity for uncovering processes driving water poverty. Extending to GWPCA is recommended when information on local differences is of interest.en
dc.description.versionPeer revieweden
dc.format.extent27
dc.format.mimetypeapplication/pdfen_US
dc.identifier.citationKallio, M, Guillaume, J, Kummu, M & Virrantaus, K-K 2018, 'Spatial Variation in Seasonal Water Poverty Index for Laos: An Application of Geographically Weighted Principal Component Analysis', Social Indicators Research, vol. 140, no. 3, pp. 1131-1157. https://doi.org/10.1007/s11205-017-1819-6en
dc.identifier.doi10.1007/s11205-017-1819-6en_US
dc.identifier.issn0303-8300
dc.identifier.issn1573-0921
dc.identifier.otherPURE UUID: 93aa712f-bb55-4a14-9caf-012109b31fdcen_US
dc.identifier.otherPURE ITEMURL: https://research.aalto.fi/en/publications/93aa712f-bb55-4a14-9caf-012109b31fdcen_US
dc.identifier.otherPURE FILEURL: https://research.aalto.fi/files/31051790/ENG_Kallio_Marko_et_al_Spatial_variation_in_seasonal_Social_indicators_research.pdf
dc.identifier.urihttps://aaltodoc.aalto.fi/handle/123456789/29911
dc.identifier.urnURN:NBN:fi:aalto-201802091408
dc.language.isoenen
dc.publisherSpringer
dc.relation.ispartofseriesSocial Indicators Researchen
dc.relation.ispartofseriesVolume 140, issue 3, pp. 1131-1157en
dc.rightsopenAccessen
dc.subject.keywordWater Poverty Indexen_US
dc.subject.keywordGeographically weighted principal component analysisen_US
dc.subject.keywordMonsoonen_US
dc.subject.keywordWater povertyen_US
dc.subject.keywordSpatio-temporal analysisen_US
dc.subject.keywordLaosen_US
dc.titleSpatial Variation in Seasonal Water Poverty Index for Laos: An Application of Geographically Weighted Principal Component Analysisen
dc.typeA1 Alkuperäisartikkeli tieteellisessä aikakauslehdessäfi
dc.type.versionacceptedVersion

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