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Abstract Details
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Activity Number:
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363
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Type:
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Contributed
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Date/Time:
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Tuesday, August 2, 2011 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Statistics and the Environment
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| Abstract - #302766 |
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Title:
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EM Algorithm for Matching Multiband Satellite Data and Land-Cover Classification
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Author(s):
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Jason Stover*+ and Matthew Ulm and Timothy Andrzejewski and Matthew Yonz
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Companies:
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Georgia College and Georgia College and Georgia College and Georgia College
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Address:
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Mathematics Department, Milledgeville, GA, 31061,
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Keywords:
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iterated conditional modes ;
remote sensing ;
markov random field
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Abstract:
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Matching reflectivity of infrared Earth images of different resolutions is possible with the EM algorithm. These matched data can then be used to estimate land cover via iterated conditional modes. Data from NASA's ASTER mission consist of reflectivity of Earth's surface measured in nine different wavelengths. Each wavelength has a resolution of either 15m or 90m, which makes simultaneous use of all bands difficult given the consequent mismatch of pixels. Using the correlation among bands and training data taken from the ground, the EM algorithm was used to impute the reflectivity of the larger pixels, thereby improving the estimated land-cover.
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