Atmospheric correction for inland water based on Gordon model

Remote sensing technique is soundly used in water quality monitoring since it can receive area radiation information at the same time. But more than 80% radiance detected by sensors at the top of the atmosphere is contributed by atmosphere not directly by water body. Water radiance information is seriously confused by atmospheric molecular and aerosol scattering and absorption. A slight bias of evaluation for atmospheric influence can deduce large error for water quality evaluation. To inverse water composition accurately we have to separate water and air information firstly. In this paper, we studied on atmospheric correction methods for inland water such as Taihu Lake. Landsat-5 TM image was corrected based on Gordon atmospheric correction model. And two kinds of data were used to calculate Raleigh scattering, aerosol scattering and radiative transmission above Taihu Lake. Meanwhile, the influence of ozone and white cap were revised. One kind of data was synchronization meteorology data, and the other one was synchronization MODIS image. At last, remote sensing reflectance was retrieved from the TM image. The effect of different methods was analyzed using in situ measured water surface spectra. The result indicates that measured and estimated remote sensing reflectance were close for both methods. Compared to the method of using MODIS image, the method of using synchronization meteorology is more accurate. And the bias is close to inland water error criterion accepted by water quality inversing. It shows that this method is suitable for Taihu Lake atmospheric correction for TM image.

[1]  P. Teillet,et al.  Rayleigh optical depth comparisons from various sources. , 1990, Applied optics.

[2]  H. Gordon.  Radiative Transfer in the Atmosphere for Correction of Ocean Color Remote Sensors , 1993 .

[3]  G. Zibordi,et al.  Remote sensing of ocean colour: Accuracy assessment of an approximate atmospheric correction method , 2003 .

[4]  H. Gordon.  Radiometric considerations for ocean color remote sensors. , 1990, Applied optics.

[5]  P Koepke,et al.  Effective reflectance of oceanic whitecaps. , 1984, Applied optics.

[6]  B. Markham,et al.  Revised Landsat-5 TM radiometric calibration procedures and postcalibration dynamic ranges , 2003, IEEE Trans. Geosci. Remote. Sens..

[7]  Sasithorn Aranuvachapun,et al.  Variation of atmospheric optical depth for remote sensing radiance calculations , 1983 .

[8]  Kenneth J. Voss,et al.  MODIS Normalized Water-leaving Radiance Algorithm Theoretical Basis Document ( MOD 18 ) Version 4 Submitted by Howard , 1999 .

[9]  Menghua Wang,et al.  A simple, moderately accurate, atmospheric correction algorithm for SeaWiFS☆ , 1994 .

[10]  Menghua Wang,et al.  Retrieval of water-leaving radiance and aerosol optical thickness over the oceans with SeaWiFS: a preliminary algorithm. , 1994, Applied optics.

[11]  Mati Kahru,et al.  Ocean Optics Protocols for Satellite Ocean Color Sensor Validation. Volume 4; Inherent Optical Properties: Instruments, Characterizations, Field Measurements and Data Analysis Protocols; Revised , 2003 .

[12]  R. W. Austin,et al.  Ocean Optics Protocols for Satellite Ocean Color Sensor Validation , 2013 .

[13]  H. Gordon,et al.  Clear water radiances for atmospheric correction of coastal zone color scanner imagery. , 1981, Applied optics.

[14]  Delu Pan,et al.  THE ATMOSPHERIC CORRECTION ALGORITHM OF SeaWiFS DATA IN CHINA SEAS , 2001 .

[15]  Tang Jun.  The Methods of Water Spectra Measurement and Analysis I:Above-Water Method , 2004 .

[16]  G. Zibordi,et al.  SeaWiFS atmospheric correction by an approximate model and vicarious calibration , 2002 .

[17]  H. Gordon,et al.  Removal of atmospheric effects from satellite imagery of the oceans. , 1978, Applied optics.