The purpose of atmospheric correction is to produce more accurate surface reflectance and to potentially improve the extraction of surface parameters from satellite images. To achieve this goal the influences of the atmosphere, solar illumination, sensor viewing geometry and terrain information have to be taken into account. Although a lot of information from satellite imagery can be extracted without atmospheric correction, the physically based approach offers advantages, especially when dealing with multitemporal data and/or when a comparison of data provided by different sensors is required. The use of atmospheric correction models is limited by the need to supply data related to the condition of the atmosphere at the time of imaging. Such data are not always available and the cost of their collection is considerable, hence atmospheric correction is performed with the use of standard atmospheric profiles. The use of these profiles results in a loss of accuracy. Therefore, site-dependent databases of atmospheric parameters are needed to calibrate and to adjust atmospheric correction methods for local level applications. In this article, the methodology and results of the project Adjustment of Atmospheric Correction Methods for Local Studies: Application in ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) (ATMOSAT) for the area of Crete are presented. ATMOSAT aimed at comparing several atmospheric correction methods for the area of Crete, as well as investigating the effects of atmospheric correction on land cover classification and change detection. Databases of spatio-temporal distributions of all required input parameters (atmospheric humidity, aerosols, spectral signatures, land cover and elevation) were developed and four atmospheric correction methods were applied and compared. The baseline for this comparison is the spatial distribution of surface reflectance, emitted radiance and brightness temperature as derived by ASTER Higher Level Products (HLPs). The comparison showed that a simple image based method, which was adjusted for the study area, provided satisfactory results for visible, near infrared and short-wave infrared spectral areas; therefore it can be used for local level applications. Finally, the effects of atmospheric correction on land cover classification and change detection were assessed using a time series of ASTER multispectral images acquired in 2000, 2002, 2004 and 2006. Results are in agreement with past studies, indicating that for this type of application, where a common radiometric scale is assumed among the multitemporal images, atmospheric correction should be taken into consideration in pre-processing.
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Document Type: Research Article
Foundation for Research and Technology - Hellas, Institute of Applied and Computational Mathematics, Vassilika Vouton, Heraklion, Crete, Greece
Jet Propulsion Laboratory, California Institute of Technology, MS 183-501, 4800 Oak Grove Drive, Pasadena, CA, USA
Department of Meteorology and Climatology, School of Geology, Aristotle University of Thessaloniki, Thessaloniki, Greece
Saga University, 1 Honjo, Saga, Japan
Publication date: 2010-07-01
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