Spectral reflectance differences of Alnus subcordata, Quercus castaneifolia and Parrotia persica leaves based on nitrogen content using PLS regression
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Abstract:
Remote sensing systems، especially hyperspectral remote sensing require fundamental knowledge of spectral reflectance of desired tree species for recognizing tree species and mapping forest type. Field spectrometry as a field of remote sensing، dealing with determination of these spectral characteristics tries to provide the spectral libraries for different objects. The objectives of this study were 1) investigating the relationship between spectral reflectance and nitrogen content and 2) investigate the species spectral separability of alder، oak and ironwood leaves based on nitrogen varying in species and to define the best wavelength for this aim، the partial least square (PLS) analysis was used. In this study the spectral fingerprint of the most important forest tree species of the northern forest of Iran namely Alder (Alnus subcordata)، Oak (Quercus castaneifolia) and Ironwood (Parrotia persica)، were acquired. This has been carried out using a full range spectrometer during the summer 2007. A total of 330 leaf ‘pile’ spectral curves of illuminated and shaded leaves were acquired of 55 trees in altitude range between 250 and 2200 m (asl.) under a clear and cloudless sky. Following the measurements، nitrogen of the mentioned leaves was extracted in laboratory. The value of vegetation indices of illuminated leaves was more than shaded ones and the differences were significant in all species. This result has been proved by statistical results obtained by nitrogen data in lab. Based on the Partial Least Square (PLS) results it proved that nitrogen variable has the ability to discriminate species. These results showed that there was the most distinct separation between Ironwood and both Alder and Oak. There were less distinct separation between Alder and Oak. Based on the result obtained by PLS regression we could conclude that the best wavelength region for spectral separability of species is in red edge region.
Language:
Persian
Published:
Journal of Forest and Wood Products, Volume:64 Issue: 4, 2012
Page:
399
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