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13 June 2014 Bobcat 2013: a hyperspectral data collection supporting the development and evaluation of spatial-spectral algorithms
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Abstract
The amount of hyperspectral imagery (HSI) data currently available is relatively small compared to other imaging modalities, and what is suitable for developing, testing, and evaluating spatial-spectral algorithms is virtually nonexistent. In this work, a significant amount of coincident airborne hyperspectral and high spatial resolution panchromatic imagery that supports the advancement of spatial-spectral feature extraction algorithms was collected to address this need. The imagery was collected in April 2013 for Ohio University by the Civil Air Patrol, with their Airborne Real-time Cueing Hyperspectral Enhanced Reconnaissance (ARCHER) sensor. The target materials, shapes, and movements throughout the collection area were chosen such that evaluation of change detection algorithms, atmospheric compensation techniques, image fusion methods, and material detection and identification algorithms is possible. This paper describes the collection plan, data acquisition, and initial analysis of the collected imagery.
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Jason Kaufman, Mehmet Celenk, A. K. White, and Alan D. Stocker "Bobcat 2013: a hyperspectral data collection supporting the development and evaluation of spatial-spectral algorithms", Proc. SPIE 9088, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XX, 90880P (13 June 2014); https://doi.org/10.1117/12.2050699
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