Please use this identifier to cite or link to this item: https://doi.org/10.1111/j.1745-5871.2010.00686.x
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dc.titleDynamics of Land Surface Temperature in Response to Land-Use/Cover Change
dc.contributor.authorZhou, X.
dc.contributor.authorWang, Y.-C.
dc.date.accessioned2014-04-02T08:18:21Z
dc.date.available2014-04-02T08:18:21Z
dc.date.issued2011-02
dc.identifier.citationZhou, X., Wang, Y.-C. (2011-02). Dynamics of Land Surface Temperature in Response to Land-Use/Cover Change. Geographical Research 49 (1) : 23-36. ScholarBank@NUS Repository. https://doi.org/10.1111/j.1745-5871.2010.00686.x
dc.identifier.issn17455863
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/49759
dc.description.abstractIn this study, we employed Geographical Information Systems and remote sensing techniques to investigate the impact of land-use/cover change on land surface temperature (LST) in a rapidly urbanisation city, Kunming in south-west China. Spatial patterns of LST and land use for 1992 and 2006 were derived from Landsat images to examine how LST responded to urban growth. Remote sensing indices were used to quantify land-use types and employed as explanatory variables in LST modelling. The geographically weighted regression (GWR), a location dependent model, was performed to explore the influences of the spatially varied land-use conditions on the LST patterns. Results revealed that rapid urbanisation in Kunming altered the local thermal environment, particularly in increasing the LST in the zone surrounding the urban core. Remote sensing indices demonstrated that water and vegetation played an important role in mitigating the urban heat island effect, while built-up and barren land accounted for the increase in LST. The GWR improved the goodness-of-fit for LST modelling and provided insights into the spatially varied relationship between LST and land-use conditions. © 2010 The Authors. Geographical Research © 2010 Institute of Australian Geographers.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1111/j.1745-5871.2010.00686.x
dc.sourceScopus
dc.subjectGeographical information systems
dc.subjectGeographically weighted regression
dc.subjectKunming
dc.subjectLand-use/cover change
dc.subjectRemote sensing
dc.subjectUrban heat island
dc.typeArticle
dc.contributor.departmentGEOGRAPHY
dc.description.doi10.1111/j.1745-5871.2010.00686.x
dc.description.sourcetitleGeographical Research
dc.description.volume49
dc.description.issue1
dc.description.page23-36
dc.identifier.isiut000286838300003
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