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Proceedings Paper

Bobcat 2013: a hyperspectral data collection supporting the development and evaluation of spatial-spectral algorithms
Author(s): Jason Kaufman; Mehmet Celenk; A. K. White; Alan D. Stocker
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Paper 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.

Paper Details

Date Published: 13 June 2014
PDF: 12 pages
Proc. SPIE 9088, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XX, 90880P (13 June 2014); doi: 10.1117/12.2050699
Show Author Affiliations
Jason Kaufman, Ohio Univ. (United States)
Mehmet Celenk, Ohio Univ. (United States)
A. K. White, Space Computer Corp. (United States)
Alan D. Stocker, Space Computer Corp. (United States)


Published in SPIE Proceedings Vol. 9088:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XX
Miguel Velez-Reyes; Fred A. Kruse, Editor(s)

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