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Please use this identifier to cite or link to this item: http://hdl.handle.net/10204/4021

Title: Within- and between- class variability of spectrally similar tree species
Authors: Debba, P
Cho, MA
Mathieu, R
Keywords: Species separability
Spectrally similar
Spectral unmixing
Spectral resolution
Electromagnetic spectrum
Spectral degradation
Derivative spectra
Remote sensing
Geoscience
Issue Date: Jul-2009
Publisher: IEEE
Citation: Debba, P, Cho, MA and Mathieu, R 2009. Within- and between- class variability of spectrally similar tree species. IEEE, International Geoscience and Remote Sensing Symposium (IGARSS), Cape Town, South Africa, 12-17 July 2009, pp 1-4
Abstract: In this paper, a comparison is made through evaluating the within and between-class species variability for the original, the first derivative and second derivative spectra. For each, the experiment was conducted (i) over the entire electromagnetic spectrum (EMS), (ii) the visible (VIS) region, (iii) the near infrared (NIR) region, (iv) the short wave infrared (SWIR) region, (v) using band selection, for example, best 10, 20, 30 and 65 bands selected, through linear stepwise discriminant analysis (vi) using sequential selection of bands, for example, every 5th, 9th, 15th, 19th or 25th band selected and (vii) spectral degradation of the spectral bands by averaging the reflectance values for every 5th, 9th, 15th, 19th or 25th band. The authors concluded that for this data set, there are important bands from the original spectra, the first and second derivative spectra and from various regions of the EMS (VIS, NIR, SWIR) that is important for species separability. Furthermore, there did not seem to be any decrease in species separability, for this data set, by degrading the spectral bands through averaging the reflectance. This implies that hyperspectral (high spectral) measurements did not prove useful in species separability compared to lower spectral resolution data.
Description: IEEE, International Geoscience and Remote Sensing Symposium (IGARSS), Cape Town, South Africa, 12-17 July 2009
URI: http://hdl.handle.net/10204/4021
ISBN: 978-1-4244-3395-7
Appears in Collections:Logistics and quantitative methods
General science, engineering & technology

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