Atmospheric and spectral corrections for estimating surface albedo from satellite data using 6S code

Surface albedo is one of the most important physical parameters for climate models, because it governs the exchange of radiation between the land surface and the atmosphere. Therefore, accuracy of the measurement of surface albedo directly affects the results of a climate model. Satellite remote sensing techniques provide a more accurate pixel-level estimation of surface albedo for climate models than traditional field measurements. However, atmospheric effects and band pass limits of satellite sensors are two factors that limit accurate estimation of surface albedo from satellite data. Furthermore, comparative or global studies require a physically based model that is not optimized on one specific satellite scene, test site, and object class. Atmospheric code 6S can play this important role. Therefore, this paper develops a method for making atmospheric and spectral corrections for estimating surface albedo from satellite data using 6S code. The reliability of this method was tested in Kushiro Mire, Japan using comparisons of estimated and observed albedos. The results show that the satellite-inferred albedos agree well with the field-observed albedos, with the average error found to be about 6%. For spectral-to-broadband albedo conversion (spectral correction), results show that compensated band pass limits are better than extended band pass limits; the average error was reduced from 25% to 6%. Results also indicate that a higher spectral resolution sensor is necessary to more accurately estimate surface albedo.

[1]  Didier Tanré,et al.  Second Simulation of the Satellite Signal in the Solar Spectrum, 6S: an overview , 1997, IEEE Trans. Geosci. Remote. Sens..

[2]  J. Otterman,et al.  Satellite Measurements of Surface Albedo and Temperatures in Semi-Desert , 1985 .

[3]  Garik Gutman,et al.  A Simple Method for Estimating Monthly Mean Albedo of Land Surfaces From AVHRR Data , 1988 .

[4]  Charles L. Walthall,et al.  Estimation of Shortwave Hemispherical Reflectance (Albedo) from Bidirectionally Reflected Radiance Data , 1991 .

[5]  Craig S. T. Daughtry,et al.  Surface albedo from bidirectional reflectance , 1991 .

[6]  Kiyotaka Nakagawa,et al.  The Surface Albedo Distribution and Its Seasonal Change over the Nagaoka Area, Niigata Prefecture, Central Japan, Estimated with LANDSAT/MSS Data , 1992 .

[7]  C. Justice,et al.  A Revised Land Surface Parameterization (SiB2) for Atmospheric GCMS. Part II: The Generation of Global Fields of Terrestrial Biophysical Parameters from Satellite Data , 1996 .

[8]  Brian L. Markham,et al.  Surface reflectance retrieval from satellite and aircraft sensors: Results of sensor and algorithm comparisons during FIFE , 1992 .

[9]  M. S. Moran,et al.  Evaluation of simplified procedures for retrieval of land surface reflectance factors from satellite sensor output , 1992 .

[10]  Albedo of the U.S. Great Plains as Determined from NOAA-9 AVHRR Data , 1989 .

[11]  L. Lei,et al.  Correction of Atmospheric Effects on AVHRR Imagery by 6S Code , 1998 .

[12]  G. Campbell,et al.  Simple equation to approximate the bidirectional reflectance from vegetative canopies and bare soil surfaces. , 1985, Applied optics.

[13]  Ann Henderson-Sellers,et al.  Surface albedo data for climatic modeling , 1983 .

[14]  Kurtis J. Thome,et al.  Reflectance factor retrieval from Landsat TM and SPOT HRV data for bright and dark targets , 1995 .

[15]  B. Markham,et al.  Radiometric Calibration of Landsat , 1997 .

[16]  Paul A. Davis,et al.  Estimation of broadband planetary albedo from operational narrowband satellite measurements , 1987 .