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Urban expansion and its impacts on local temperature in San Salvador, El Salvador.

Authors :
Son, N.T.
Chen, C.F.
Chen, C.R.
Source :
Urban Climate; Jun2020, Vol. 32, pN.PAG-N.PAG, 1p
Publication Year :
2020

Abstract

Information on urban growth associated with surface temperature is crucial for urban planning. This study evaluated the urban growth and its impacts on land surface temperature (LST) from Landsat imageries in San Salvador City, El Salvador during periods 1986–2001–2016. The results of urban classification were verified with the reference data, indicating close agreement between these two datasets. The overall accuracy and Kappa coefficient were generally higher than 89.8% and 0.8, respectively. The built-up area had expanded from 1778.2 ha during 1986–2001 to 876.5 ha during 2001–2016. Due to rapid urbanization, the area, where the LST was higher than 36 °C, had remarkably increased from 31.6% (1986) to 39.7% (2001), and 51.4% (2016), respectively. These findings were reflected by the increased proportion of very hot spots from 32% (1986) to 37.7% (2001), and 39.9% (2016), respectively. The decadal impacts of urbanization on local temperature were confirmed by significant relationship of LST with the normalized difference vegetation index (NDVI) and normalized difference built-up area index (NDBI) (R <superscript>2</superscript> > 0.72). Such an information on the trend of urban expansion and local climate change could be valuable to planners to formulate successful planning strategies to regulate impacts of urban heats on the city's livability. • Multi-temporal Landsat data for urban growth monitoring. • Decadal impacts of urban expansion on local thermal environment. • Relationship of LST with vegetation indices. • Information of urban growth associated with LST is crucial for urban planning. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
22120955
Volume :
32
Database :
Supplemental Index
Journal :
Urban Climate
Publication Type :
Academic Journal
Accession number :
143247961
Full Text :
https://doi.org/10.1016/j.uclim.2020.100617