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Proceedings Paper

Atmospheric compensation for WorldView-2 satellite and in-water component retrieval
Author(s): Javier A. Concha; Aaron D. Gerace
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Paper Abstract

In the present work, the WorldView-2 (WV2) capability for retrieving Case 2 water components is analyzed. The WV2 sensor characteristics, such as a 11-bit quantization, 8 bands in the VNIR (visible and near infrared) region and high Signal-to-Noise Ratios (SNR) make WV2 potentially suitable for a retrieval process. In the Case 2 water problem, the sensor-reaching signal due to water is very small when compared to the signal due to the atmospheric eects. Therefore, adequate atmospheric compensation becomes an important rst step to accurately retrieve water parameters. The problem becomes more dicult when using multispectral imagery as there are typically only a handful of bands suitable for performing atmospheric compensation. In this work, we test atmospheric compensation techniques for the WV2 satellite, enabling it to be used for water constituent retrieval in both deep and shallow water. A look-up-table (LUT) methodology is implemented to retrieve the water parameters chlorophyll, suspended materials, colored dissolved organic matter, bathymetry, bottom type and water clarity for a simulated case study. The in-water radiative transfer code HydroLight is used to simulate re ectance data in this study while the MODTRAN code is used to simulate atmospheric eects. The resulting modeled sensor-reaching radiance data can be sampled to a WV2 sensor model to simulate WV2 image data. This data is used to test the proposed methodology. Finally, a sensitivity analysis is performed to evaluate how sensitive the constituent retrieval process is to adequate atmospheric compensation.

Paper Details

Date Published: 14 May 2012
PDF: 9 pages
Proc. SPIE 8390, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVIII, 83900W (14 May 2012); doi: 10.1117/12.918962
Show Author Affiliations
Javier A. Concha, Rochester Institute of Technology (United States)
Aaron D. Gerace, Rochester Institute of Technology (United States)


Published in SPIE Proceedings Vol. 8390:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVIII
Sylvia S. Shen; Paul E. Lewis, Editor(s)

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