Spatial non-stationarity in the relationships between land cover and surface temperature in an urban heat island and its impacts on thermally sensitive populations
Journal
Landscape and Urban Planning
Journal Volume
107
Journal Issue
2
Pages
172-180
Date Issued
2012
Author(s)
Abstract
Past studies focused on the relationships between land cover and urban temperature have commonly assumed stationarity and used conventional (global) regression analysis. In this study, geographically weighted regression (GWR) was used to test the spatial stationarity of the relationships between a set of land cover types (built-up, water, paddy field, and other vegetation) and the surface temperature in TaoYuan, Taiwan. By adopting the GWR approach, significant spatial non-stationarity of these relationships was observed and the strength of these relationships was markedly higher than from a conventional regression analysis. The differences have large impacts. If the regression models were used to derive an estimate of the urban heat island intensity for TaoYuan this would equate to 2.63 °C and 3.17 °C for the global and GWR models, respectively. This result showed that the urban heat island was underestimated by global model and this, therefore, increased potential to underestimate the risk of ill-health and discomfort for urban populations. The mapped parameters derived from GWR analyses provided useful information for planning temperature mitigation and adaptation strategies especially for the very young and elderly that are particularly sensitive to temperature. © 2012 Elsevier B.V.
Subjects
Land cover conversion; Spatial non-stationarity; Surface temperature; Urban heat island
Other Subjects
Adaptation strategies; Geographically weighted regression; Global models; Land cover; Land-cover types; Paddy fields; Regression model; Spatial non-stationarity; Stationarity; Surface temperatures; Urban heat island; Urban population; C (programming language); Health risks; Landforms; Regression analysis; Statistics; Surface properties; Thermal pollution; Atmospheric temperature; land cover; numerical model; regression analysis; spatial analysis; surface temperature; urban planning; urban population; Taiwan; Taoyuan [Taiwan]
Type
journal article