Title :
Analysis and study of urban heat environment and respirable particulate matter in Beijing city
Author :
Shanshan, Li ; Huili, Gong ; Wenji, Zhao ; Yonghua, Sun
Author_Institution :
Coll. of Resources, Environ. & Tourism, Capital Normal Univ., Beijing
Abstract :
The phenomenon of temperature in urban cities is higher than that in suburbs is called Urban Heat Island (UHI), which is put forward by Lake Howard in 1833. Three main algorithms of land surface temperature retrieval of existing thermal infrared remote sensed data has been developed: single channel algorithm, split window algorithm and multi-band algorithm. The thesis selected split window algorithm and improves the split window algorithm of AVHRR to suit MODIS image data. This split window algorithm is based on the thermal radiation data which is observed by NOAA-AVHRR. This paper retrieved land surface temperature and analysis the spatial characteristics of Beijing urban heat island as well as its influencing factors. The result indicates that analysis on urban heat island effect based on split window algorithm of Beijing is available. There is a clear urban heat island in summer, and it is quite close with vegetation index. Besides, the negative correlation relationship between land surface temperature and Respirable Particulate Matter is also emphasizely analyzed.
Keywords :
aerosols; atmospheric temperature; land surface temperature; remote sensing; AVHRR; Beijing City; China; NOAA; Respirable Particulate Matter; Urban Heat Island; atmospheric temperature phenomenon; land surface temperature retrieval; multi-band algorithm; single channel algorithm; split window algorithm; thermal infrared remote sensed data; urban heat environment; Algorithm design and analysis; Cities and towns; Information retrieval; Lakes; Land surface; Land surface temperature; MODIS; Remote sensing; Temperature sensors; Thermal pollution; PM10; atmospheric transmittance; land surface emissivity; land surface temperature; split window algorithm; urban heat island;
Conference_Titel :
Urban Remote Sensing Event, 2009 Joint
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-3460-2
Electronic_ISBN :
978-1-4244-3461-9
DOI :
10.1109/URS.2009.5137565