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Research Of Foliar Dust Content Estimation By Reflectance Spectroscopy Of Euonymus Japonicus Thunb | 50303

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Research of foliar dust content estimation by reflectance spectroscopy of Euonymus japonicus Thunb

7th Annual Global Pharma Summit

Xuefeng Wang and Chunyan Wu

Chinese Academy of Forestry, China

ScientificTracks Abstracts: Clin Pharmacol Biopharm

DOI: 10.4172/2167-065X.C1.019

Abstract
To seek effective protective measures for fog and haze weather to establish an inversion model for leaf dust content based on spectrum data, 120 leaf samples of Euonymus japonicus were collected in 12 regions with uniform distribution in Beijing City. The variation characteristics of reflectance spectra of Euonymus japonicus and foliar dust content were noted and the differences of leaf reflectance and first derivative spectrum between leaves with and without dust were analyzed. The correlation between foliar dust content and leaf spectral reflectance were established. The results suggest that foliar dust increased the reflectance in specific ranges of the visible light spectrum, decreased the reflectance at near infrared regions and had no change in red edge position, blue edge slope and yellow and blue edge area. Furthermore, the yellow edge position and yellow edge slope were decreased while the blue edge position and red edge slope and red edge area were increased. This research calculated leaf surface dust content inversion models with the model fitting only within spectral parameters and foliar dust content. This study led to the discovery that the fitting index of the area of red edge as a variable is relatively high and grading the foliar dust content to obtain a variety of model fitting with four spectral parameters enabled the conclusion that model is the final relatively good inversion model of Euonymus japonicus foliar dust content.
Biography

Xuefeng Wang is the Researcher of Chinese Academy of Forestry. He has completed his PhD and researches in computer vision and its application in forestry.

Email: xuefeng@ifrit.ac.cn

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