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  • 1
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    A method for classification of multisource data using interval-valued probabilities and its application to HIRIS data (1991)
    In:  CASI
    Details
    Publication Date: 2013-08-31
    Description: A method of classifying multisource data in remote sensing is presented. The proposed method considers each data source as an information source providing a body of evidence, represents statistical evidence by interval-valued probabilities, and uses Dempster's rule to integrate information based on multiple data source. The method is applied to the problems of ground-cover classification of multispectral data combined with digital terrain data such as elevation, slope, and aspect. Then this method is applied to simulated 201-band High Resolution Imaging Spectrometer (HIRIS) data by dividing the dimensionally huge data source into smaller and more manageable pieces based on the global statistical correlation information. It produces higher classification accuracy than the Maximum Likelihood (ML) classification method when the Hughes phenomenon is apparent.
    Keywords: EARTH RESOURCES AND REMOTE SENSING
    Type: NASA, Goddard Space Flight Center, Multisource Data Integration in Remote Sensing; p 75-81
    Format: application/pdf
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    NASA TECHNICAL REPORTS
  • 2
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    A method for classification of multisource data using interval-valued probabilities and its application to HIRIS data (1990)
    In:  Other Sources
    Details
    Publication Date: 2019-06-28
    Description: A method of classifying multisource data in remote sensing is presented. The proposed method considers each data source as an information source providing a body of evidence, represents statistical evidence by interval-valued probabilities, and uses Dempster's rule to integrate information based on multiple data sources. The method is applied to the problems of ground-cover classification of multispectral data combined with digital terrain data such as elevation, slope, and aspect. Then this method is applied to simulated 201-band High Resolution Imaging Spectrometer (HIRIS) data by dividing the dimensionally huge data source into smaller and more manageable pieces based on the global statistical correlation information. It produces higher classification accuracy than the Maximum Likelihood (ML) classification method when the Hughes phenomenon is apparent.
    Keywords: EARTH RESOURCES AND REMOTE SENSING
    Format: text
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    NASA TECHNICAL REPORTS
  • 3
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    Combining multispectral and ancillary data in remote sensing using interval-valued probabilities (1989)
    In:  Other Sources
    Details
    Publication Date: 2019-06-28
    Description: This paper presents a method for classifying multisource data in remote sensing and geographic information systems using interval-valued probabilities. In this method, each data source is considered as an information source which provides a body of statistical evidence. In order to integrate information obtained from multiple data sources, the method adopts Dempster's rule for combining multiple bodies of evidence. Preliminary experiments have been undertaken to illustrate the use of the method in a supervised ground-cover classification on multispectral data combined with digital elevation data. They demonstrate the ability of the method in capturing information provided by inexact and incomplete evidence when there are not enough training samples to estimate statistical parameters.
    Keywords: EARTH RESOURCES AND REMOTE SENSING
    Format: text
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    NASA TECHNICAL REPORTS
  • 4
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    Ocean Chlorophyll Studies from a U-2 Aircraft Platform (1979)
    In:  CASI
    Details
    Publication Date: 2019-06-27
    Description: Chlorophyll gradient maps of large ocean areas were generated from U-2 ocean color scanner data obtained over test sites in the Pacific and Atlantic Oceans. The delineation of oceanic features using the upward radiant intensity relies on an analysis method which presupposes that radiation backscattered from the atmosphere and ocean surface can be properly modeled using a measurement made at 778 nm. An estimation of the chlorophyll concentration was performed by properly ratioing radiances measured at 472 nm and 548 nm after removing the atmospheric effects. The correlation between the remotely sensed data and in-situ surface chlorophyll measurements was validated in two sets of data. The results show that the correlation between the in-situ measured chlorophyll and the derived quantity is a negative exponential function and the correlation coefficient was calculated to be -0.965.
    Keywords: EARTH RESOURCES AND REMOTE SENSING
    Type: NASA-TM-80574
    Format: application/pdf
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    NASA TECHNICAL REPORTS
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