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Urban surface temperature retrieval ...

City University of New York., Earth & Environmental Sciences.

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Urban surface temperature retrieval from space through emissivity classification.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Urban surface temperature retrieval from space through emissivity classification./
作者:	Ahn, Hyo Jin.
面頁冊數:	129 p.
附註:	Adviser: Karl H. Szekielda.
Contained By:	Dissertation Abstracts International69-05B.
標題:	Environmental Sciences. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3310586
ISBN:	9780549584971

Urban surface temperature retrieval from space through emissivity classification.
Ahn, Hyo Jin.

Urban surface temperature retrieval from space through emissivity classification. - 129 p.

Adviser: Karl H. Szekielda.

Thesis (Ph.D.)--City University of New York, 2008.

Deriving accurate surface temperatures from satellite remote sensing data for urban environment and climate studies is problematic because it requires at least 10 to 15 m spatial resolution with pre-knowledge of emissivity information. This research focused on developing new techniques for the enhancement of spatial resolution to a 15 m urban surface temperature mapping through image fusion, improving classification accuracy, and application of classified emissivity and atmospheric corrections. The major findings are as follows: (1) In enhancing spatial resolution of Landsat 7 Enhanced Thematic Mapper Plus (ETM+) to 15 m pixel size, the principal component spectral sharpening and the Gram-Schmidt sharpening provide the best result with the least distortion of the original spectral properties. The consequent classification product by maximum likelihood classifier shows an overall accuracy of 97% and a Kappa coefficient of 0.82 by increased number of input bands including three principal components, and twelve ratio bands. (2) As a part of classification accuracy test, the Scaled Difference Vegetation Index (SDVI) method shows an efficient quantitative analysis for vegetation estimation within less than 0 to 0.4% deviations. (3) For deriving the ETM+ surface temperature from its radiance data, applying the emissivities retrieved from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) at the wavelength region 10.95-11.65 microm is superior to those from the wavelength region 10.25-10.95 microm. (4) The cross examination shows that 0.30 ºC higher by ETM+ surface temperature and 0.55 ºC higher by ASTER surface temperature than the buoy measurements of sea surface temperatures (SSTs), but both measurements are acceptable at the 95% confidence interval. The comparison between ASTER and Moderate Resolution Imaging Spectroradiometer (MODIS) shows that the MODIS LST underestimates the average 3.8 ºC. This new approach provides an improvement over existing techniques that retrieve surface temperature based on single or few levels of surface emissivities.

ISBN: 9780549584971Subjects--Topical Terms:

676987
Environmental Sciences.

Urban surface temperature retrieval from space through emissivity classification.
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502 $a Thesis (Ph.D.)--City University of New York, 2008.
520 $a Deriving accurate surface temperatures from satellite remote sensing data for urban environment and climate studies is problematic because it requires at least 10 to 15 m spatial resolution with pre-knowledge of emissivity information. This research focused on developing new techniques for the enhancement of spatial resolution to a 15 m urban surface temperature mapping through image fusion, improving classification accuracy, and application of classified emissivity and atmospheric corrections. The major findings are as follows: (1) In enhancing spatial resolution of Landsat 7 Enhanced Thematic Mapper Plus (ETM+) to 15 m pixel size, the principal component spectral sharpening and the Gram-Schmidt sharpening provide the best result with the least distortion of the original spectral properties. The consequent classification product by maximum likelihood classifier shows an overall accuracy of 97% and a Kappa coefficient of 0.82 by increased number of input bands including three principal components, and twelve ratio bands. (2) As a part of classification accuracy test, the Scaled Difference Vegetation Index (SDVI) method shows an efficient quantitative analysis for vegetation estimation within less than 0 to 0.4% deviations. (3) For deriving the ETM+ surface temperature from its radiance data, applying the emissivities retrieved from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) at the wavelength region 10.95-11.65 microm is superior to those from the wavelength region 10.25-10.95 microm. (4) The cross examination shows that 0.30 ºC higher by ETM+ surface temperature and 0.55 ºC higher by ASTER surface temperature than the buoy measurements of sea surface temperatures (SSTs), but both measurements are acceptable at the 95% confidence interval. The comparison between ASTER and Moderate Resolution Imaging Spectroradiometer (MODIS) shows that the MODIS LST underestimates the average 3.8 ºC. This new approach provides an improvement over existing techniques that retrieve surface temperature based on single or few levels of surface emissivities.
520 $a Therefore, semi-automated approaches in the retrieval of urban surface temperatures using the enhanced pixel resolution of Landsat ETM+ thermal data based on differentiated surface emissivity classes with the atmospheric correction parameter sets show that it is possible to establish a mapping with surface temperature database in its accuracy up to 96% relative to the ASTER surface temperatures.
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