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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Debba, P. Cho, M.A. Mathieu, R. |
| Copyright Year | 2009 |
| Description | Author affiliation: The Council for Scientific and Industrial Research (CSIR), CSIR Natural Resources of the Environment, P. O. Box 395, 0001, South Africa (Cho, M.A.; Mathieu, R.) || The Council for Scientific and Industrial Research (CSIR), CSIR Built Environment, P. O. Box 395, 0001, South Africa (Debba, P.) |
| 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 step-wise 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. We 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. |
| File Size | 480483 |
| File Format | |
| ISBN | 9781424433940 |
| DOI | 10.1109/IGARSS.2009.5417319 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-07-12 |
| Publisher Place | South Africa |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Image classification Vegetation mapping Reflectivity Hyperspectral imaging Africa Medical services Infrared spectra Degradation Councils Electromagnetic spectrum spectral resolution Species separability within-class variability between-class variability spectrally similar classification spectral unmixing band selection |
| Content Type | Text |
| Resource Type | Article |
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