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
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