DocumentCode :
124641
Title :
Seasonal dynamics of the relationship between landscape pattern and land surface temperature in a coastal city
Author :
Xiaofeng Zhao ; Yanchuang Zhao ; Da Kuang
Author_Institution :
Key Lab. of Urban Environ. & Health, Inst. of Urban Environ., Xiamen, China
fYear :
2014
fDate :
11-14 June 2014
Firstpage :
418
Lastpage :
422
Abstract :
The effects of land cover on LST have been found varying with season. Yet the seasonal dynamics of the relationship between metrics measured landscape pattern and LST has seldom been investigated. This study used a seasonal series of Landsat TM/ETM+ images in the year 2002 to examine the landscape pattern-LST relationship in Xiamen city. Landscape metrics and partial Pearson correlation were employed. The results showed that all the bivariate correlations between landscape metrics and LST changed with season to different extents. There were 7 consistently significant metrics across seasons for the year in Pearson correlation. All the configuration metrics lost their consistent significance in correlations with LST across seasons after partial Pearson correlation. Composition metrics of forest (PLAND3) was found to be the effective metric affecting LST consistently across seasons in the year. And the strongest bivariate correlation of PLAND3 happened in autumn for the study years.
Keywords :
land cover; land surface temperature; vegetation; AD 2002; LST changed; LST correlation; Landsat TM-ETM+ image seasonal series; PLAND3 strongest bivariate correlation; Xiamen city; autumn season; bivariate correlation; coastal city; configuration metric; effective LST metric; forest composition metric; land cover effect; land surface temperature; landscape metric; landscape pattern-LST relationship; partial Pearson correlation; seasonal dynamic; Cities and towns; Earth; Image resolution; Indexes; Remote sensing; Satellites; Springs; land surface temperature; landscape pattern; seasonal dynamics; urban heat island;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Earth Observation and Remote Sensing Applications (EORSA), 2014 3rd International Workshop on
Conference_Location :
Changsha
Print_ISBN :
978-1-4799-5757-6
Type :
conf
DOI :
10.1109/EORSA.2014.6927925
Filename :
6927925
Link To Document :
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