A method for retrieving water-leaving radiance from Landsat TM image in Taihu Lake, East China

Autor: MA Ronghua, Kang Guoding, Feng Xuezhi, Wang Deyu
Rok vydání: 2007
Předmět:
Zdroj: Chinese Geographical Science. 17:364-369
ISSN: 1993-064X
1002-0063
DOI: 10.1007/s11769-007-0364-7
Popis: The visible and infrared bands of Landsat Thematic Mapper (TM) can be used for inland water studies. A method of retrieving water-leaving radiance from TM image over Taihu Lake in Jiangsu Province of China was investigated in this article. To estimate water-leaving radiance, atmospheric correction was performed in three visible bands of 485nm, 560nm and 660nm. Rayleigh scattering was computed precisely, and the aerosol contribution was estimated by adopting the clear-water-pixels approach. The clear waters were identified by using the Landsat TM middle-infrared band (2.1 μm), and the water-leaving radiance of clear water pixels in the green band was estimated by using field data. Aerosol scattering at green band was derived for six points, and interpolated to match the TM image. Assuming the atmospheric correction coefficient was 1.0, the aerosol scattering image at blue and red bands were derived. Based on a simplified atmospheric radiation transfer model, the water-leaving radiance for three visible bands was retrieved. The water-leaving radiance was normalized to make it comparable with that estimated from other remotely sensed data acquired at different times, and under different atmospheric conditions. Additionally, remotely sensed reflectance of water was computed. To evaluate the atmospheric correction method presented in this article, the correlation was analyzed between the corrected remotely sensed data and the measured water parameters based on the retrieval model. The results show that the atmospheric correction method based on the image itself is more effective for the retrieval of water parameters from Landsat TM data than 6S (Second Simulation of the Satellite Signal in the Solar Spectrum) code based on standard atmospheric and aerosol models.
Databáze: OpenAIRE
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