Authors / CoAuthors
Li, F. | Jupp, D.L.B. | Reddy, S. | Lymburner, L. | Mueller, N. | Tan, T. | Islam, A.
Abstract
Normalising for atmospheric and land surface bidirectional reflectance distribution function (BRDF) effects is important in satellite data processing. It is particularly important for standardising time series data and for inter-sensor calibration and comparison. Procedures based on physical models have been applied successfully with the Moderate Resolution Imaging Spectroradiometer (MODIS) data products at global scales. For Landsat and other higher resolution data, similar options exist except that the estimation of BRDF using internal fitting, as used for MODIS, is not available due to the smaller variation of view and solar angles, sun-synchronous view and infrequent revisits. Despite this, the use of physical models for atmospheric correction and BRDF normalising can still be appropriate. In this study, we explore the potential for developing operational procedures to correct higher resolution sensor data based on combined atmospheric and BRDF models. The process was realised using BRDF parameters (shape functions) derived from MODIS and using the MODTRAN 4 radiative transfer model. The approach was tested using Landsat data for two sites with different land covers in Australia. The retrieved Landsat reflectance values have good agreement with ground based spectroradiometer measurements with the root mean square difference (RMSD) for both sites being less than 3%. The comparison between normalised Landsat and MODIS reflectance shows a strong relationship, indicating that cross-calibration between the two sensors is achievable. Strategies which may provide effective BRDF parameters before MODIS was available (and after its mission is complete) are also discussed as well as the options that exist for an operational system in the context of monitoring land cover change.
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nonGeographicDataset
eCat Id
69168
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- External PublicationScientific Journal Paper
- ( Theme )
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- remote sensing
- Australian and New Zealand Standard Research Classification (ANZSRC)
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- Earth Sciences
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- Published_Internal
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2010-01-01T00:00:00
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