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Method of Integrating Landsat-5 and Landsat-7 Data to Retrieve Sea Surface Temperature in Coastal Waters on the Basis of Local Empirical Algorithm  

Xing, Qianguo (LED, South China Sea Institute of Oceanography, Chinese Academy of Science)
Chen, Chu-Qun (LED, South China Sea Institute of Oceanography, Chinese Academy of Science)
Shi, Ping (LED, South China Sea Institute of Oceanography, Chinese Academy of Science)
Publication Information
Ocean Science Journal / v.41, no.2, 2006 , pp. 97-104 More about this Journal
Abstract
A useful radiance-converting method was developed to convert the Landsat-7 ETM+thermal-infrared (TIR) band's radiance ($L_{{\lambda},L7/ETM+}$) to that of Landsat-5 TM TIR ($L_{{\lambda},L5/TM+})$ as: $L_{{\lambda},L5/TM}=0.9699{\times}L_{{\lambda},L7/ETM+}+0.1074\;(R^2=1)$. In addition, based on the radiance-converting equation and the linear relation between digital number (DN) and at-satellite radiance, a DN-converting equation can be established to convert DN value of the TIR band between Landsat-5 and Landsat-7. Via this method, it is easy to integrate Landsat-5 and Landsat-7 TIR data to retrieve the sea surface temperature (SST) in coastal waters on the basis of local empirical algorithms in which the radiance or DN of Lansat-5 and 7 TIR band is usually the only input independent variable. The method was employed in a local empirical algorithm in Daya Bay, China, to detect the thermal pollution of cooling water discharge from the Daya Bay nuclear power station (DNPS). This work demonstrates that radiance conversion is an effective approach to integration of Landsat-5 and Landsat-7 data in the process of a SST retrieval which is based on local empirical algorithms.
Keywords
remote sensing; sea surface temperature; Landsat; coastal waters;
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