DocumentCode
3356605
Title
Relationships of LST to NDBI and NDVI in Wuhan City based on Landsat ETM+ image
Author
Longyin Chen ; Mengyun Li ; Fang Huang ; Shuangling Xu
Author_Institution
Sch. of Geogr. Sci., Northeast Normal Univ., Changchun, China
Volume
2
fYear
2013
fDate
16-18 Dec. 2013
Firstpage
840
Lastpage
845
Abstract
Based on four Landsat ETM+ images covering Wuhan City, Normalized Difference Vegetation Index (NDVI) and Normalized Difference Built-up Index (NDBI) in spring, summer, autumn and winter were calculated. The land surface temperature (LST) of the city in four seasons was estimated using the radiative transfer model. The spatial and temporal pattern and characteristics of NDVI, NDBI and LST and their relationship were analyzed in detail. Results show that the regions with higher NDBI and LST values were mainly in the municipal district of Wuhan City, including Hankou and Wuchang. The maximum NDBI of the district in four seasons was 0.669, 0.685, 0.659 and 0.703 respectively, while the maximum LST was 43.529°C, 59.849°C, 47.143°C and 23.875°C. Higher NDVI values were mainly distributed in the regions such as along the Han River, the lake beach and the wetlands area in the southwest and central hilly areas, and the maximum NDVI in different seasons was 0.432, 0.564, 0.442 and 0.158 respectively. There existed a strong positive correlation between NDBI and LST in all seasons. The Pearson´s correlation coefficient in four seasons was 0.639, 0.717, 0.807 and 0.762 respectively. In autumn, NDBI and LST were most significantly correlated. The relationship between NDVI and LST changed with season, but without obvious regularity. The correlation between NDVI and LST was weaker in four seasons than that between NDBI and LST, with the Pearson coefficients of -0.515, -0.577, -0.246 and -0.038 respectively. NDVI values had negatively linkage with NDBI. The Pearson´s correlation coefficients in four seasons was -0.568, -0.582, -0.536 and -0.242, which indicated that NDVI could be used to characterize the evolution of urban construction land. The throughout study suggests that NDBI not only can be used as an important indicator to analyze LST and urban heat island effects, but also will provide a reliable basis for urban construction and planning.
Keywords
geophysical image processing; remote sensing; LST; Landsat ETM+ image; NDBI; NDVI; Pearson coefficients; Wuhan city; land surface temperature; normalized difference built-up index; normalized difference vegetation index; radiative transfer model; remote sensing; strong positive correlation; urban construction land; Cities and towns; Correlation; Indexes; Land surface; Land surface temperature; Temperature sensors; Vegetation mapping; Correlation Analysis; Land Surface Temperature; NDBI; NDVI; Wuhan City;
fLanguage
English
Publisher
ieee
Conference_Titel
Image and Signal Processing (CISP), 2013 6th International Congress on
Conference_Location
Hangzhou
Print_ISBN
978-1-4799-2763-0
Type
conf
DOI
10.1109/CISP.2013.6745282
Filename
6745282
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