Dynamics of Land Surface Temperature in Response to Land-Use/Cover Change

In 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 deri...

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Bibliographic Details
Published in:Geographical research 2011-02, Vol.49 (1), p.23-36
Main Authors: ZHOU, XIAOLU, WANG, YI-CHEN
Format: Article
Language:English
Subjects:
China
Environmental change
Geographic information systems
Geographical information systems
geographically weighted regression
Islands
Kunming
Land
Land resources
Land settlement
Land use
Land utilization
land-use/cover change
Landsat
Measurement
mitigation
Modelling
Remote sensing
Spatial analysis
spatial distribution
Temperature
urban heat island
Urban heat islands
urban sprawl
Urbanisation
Urbanization
Vegetation
Water
Weather
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Summary:In 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.
ISSN:1745-5863
1745-5871
DOI:10.1111/j.1745-5871.2010.00686.x