Authors / CoAuthors
Wang, L. | Li, F. | Alam, I. | Jupp, D. | Oliver, S. | Thankappan, M.
Abstract
CEOS Analysis Ready Data for Land (CARD4L) are satellite data that have been processed to a minimum set of requirements and organized into a form that allows immediate analysis with a minimum of additional user effort and interoperability both through time and with other datasets [1]. In this paper, key input data (e.g. aerosol optical depth, precipitable water, BRDF parameters) needed for atmospheric and BRDF corrections of Landsat data are identified and a sensitivity analysis is conducted using outputs of a physics based atmospheric and BRDF model. The results show that aerosol impacts more on the visible bands where the average variation of reflectance could reach 0.05 of reflectance unit. The variation over dark targets can be much higher so that it is a critical parameter for aquatic applications. By contrast, precipitable water (water vapor in the rest of the paper) only impacts the near-infrared (NIR) and shortwave (SWIR) bands and the extent of change is much smaller. BRDF parameters impact time series most on winter and summer images of highly anisotropic areas and when they are normalized to 45º solar angle. Different BRDF levels for different spectrum ranges not only impact the magnitude of reflectance, but also the signature for these areas. It seems that it is necessary to normalize surface BRDF to ensure time series consistency of the Landsat ARD product. Abstract presented at 2019 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)
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document
eCat Id
128809
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Keywords
- theme.ANZRC Fields of Research.rdf
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- EARTH SCIENCES
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- Bi-directional Reflectance Distribution Function - BRDF
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- Analysis Ready Data - ARD
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- surface reflectance
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- atmospheric correction
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- Published_External
Publication Date
2024-04-08T03:10:50
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completed
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geoscientificInformation
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IEEE International Geoscience and Remote Sensing Symposium (IGARSS) 28 July - 2 August 2019 Yokohama, Japan
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Abstract submission for IGARSS Symposium 2019
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[-44.00, -9.00, 112.00, 154.00]
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Spatial Resolution
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