KalacskaArroyo2009

Reference

Kalacska, M., Arroyo, P. (2009) The cost of time - Implications of hyperspectral data volume and feature selection routines for conservation science. In WHISPERS '09 - 1st Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing. (Scopus )

Abstract

The recent greater availability of airborne hyperspectral imagery in the tropics has allowed for the analysis of increasingly complex analytical questions in ecology such as remote tree species identification. In comparison to species identification the spectral expression of gender in dioecious species has been generally overlooked despite its effects on plant ecophysiological functioning and the prevalence of dioecious species in the tropics. A problem often implied but not frequently addressed in these analyses is the complexity posed by the data volume collected by airborne sensors. We examine the effect of this volume specifically on feature selection routines for classification and the implication of the resultant limitations on the use of airborne hyperspectral imagery at regional operational scales. We conclude based on an examination of analytical time and the cost of high performance computing systems, that an efficient alternative for such large scale academic or NGO research is a cluster of PlayStationâ„¢ 3s. © 2009 IEEE.

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@INPROCEEDINGS { KalacskaArroyo2009,
    AUTHOR = { Kalacska, M. and Arroyo, P. },
    TITLE = { The cost of time - Implications of hyperspectral data volume and feature selection routines for conservation science },
    BOOKTITLE = { WHISPERS '09 - 1st Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing },
    YEAR = { 2009 },
    PAGES = { -- },
    ABSTRACT = { The recent greater availability of airborne hyperspectral imagery in the tropics has allowed for the analysis of increasingly complex analytical questions in ecology such as remote tree species identification. In comparison to species identification the spectral expression of gender in dioecious species has been generally overlooked despite its effects on plant ecophysiological functioning and the prevalence of dioecious species in the tropics. A problem often implied but not frequently addressed in these analyses is the complexity posed by the data volume collected by airborne sensors. We examine the effect of this volume specifically on feature selection routines for classification and the implication of the resultant limitations on the use of airborne hyperspectral imagery at regional operational scales. We conclude based on an examination of analytical time and the cost of high performance computing systems, that an efficient alternative for such large scale academic or NGO research is a cluster of PlayStationâ„¢ 3s. © 2009 IEEE. },
    COMMENT = { Export Date: 10 February 2010 Source: Scopus Art. No.: 5289056 doi: 10.1109/WHISPERS.2009.5289056 },
    ISSN = { 9781424446872 (ISBN) },
    KEYWORDS = { CELL, Dioecious, Feature selection, High performance computing, Tropical forest, Air-borne sensors, Conservation science, Data volume, Feature selection, High performance computing, High performance computing systems, Hyperspectral Data, Hyperspectral imagery, Operational scale, PlayStation, Species identification, Tree species, Tropical forest, Computer science, Remote sensing, Signal processing, Tropics },
    OWNER = { Luc },
    TIMESTAMP = { 2010.02.10 },
    URL = { http://www.scopus.com/inward/record.url?eid=2-s2.0-72149111716&partnerID=40&md5=018dafde7d306918bfc82fa9b37e0da2 },
}

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