Welcome to visit Scientia Silvae Sinicae,Today is

Scientia Silvae Sinicae ›› 2015, Vol. 51 ›› Issue (3): 49-56.doi: 10.11707/j.1001-7488.20150307

Previous Articles     Next Articles

Effect of Different Foliar Dust Contents on Reflectance Spectroscopy of Euonymus japonicus

Wu Chunyan, Wang Xuefeng   

  1. Research Institute of Forest Resources Information Techniques, CAF Beijing 100091
  • Received:2014-05-16 Revised:2014-09-25 Online:2015-03-25 Published:2015-04-10

Abstract:

【Objective】The dust on the surface of the leaves of trees can reflect the around environmental pollution in a certain extent. With the increasing of the degree of atmospheric pollution, the harm of haze weather becomes more severe. Therefore, haze becomes a high-profile word in modern society. Haze is mainly formed by atmospheric particles floating and crowding in the air. Atmospheric particles fall on the leaf surfaces through dry or wet deposition. After that, the foliar dust formed. The foliar dust has an impact on the spectra reflection of the leaves of trees and the plant physiological ecology. In this paper, we explored the relationship between foliar dust contents and reflection spectra of Euonymus japonicas. The prevention control strategy of haze and the correct remote sensing inversion were also introduced.【Method】The leaves of Euonymus japonicus growth at the academy of forestry were used as raw materials. The collecting leaves were fresh-keeping and took to indoors quickly. The weight of the leaves before and after cleaning was tested using a 1/10 000 high precision electronic analytical balance. The differences of the weight are the weight of the foliar dust. The reflection spectrum of the leaves before and after cleaning was measured using a FieldSpec3 Portable NIR spectrometer produced by the company of ASD (Analytical Spectral Device) of USA. The differences of the reflection spectrum were compared and analyzed. The differences of leaf reflectance before and after cleaning, and the first derivative spectrum and red edge parameter characteristics were compared and analyzed. The differences of leaf spectral reflectance between different amounts of dust was also compared, The relation model between foliar dust content and leaf spectral reflectance was established.【Result】Spectral reflectance of leaves before and after cleaning the dust is different. In the range of 520-560 nm, the leaf reflectance of dust leaves was higher than that of clean leaves. While in the range of 760-850 nm, the leaf reflectance of dust leaves was less than that of clean leaves. The reflectance spectra of different foliar dust content is difference. The results suggest that the leaf spectral reflectance of Euonymus japonicus increased with the increasing of foliar dust content in visible band. However, the spectral reflectance decreased in near infrared region. No changes were found in red and yellow edge position, blue edge slope, and blue edge area. Compared with the clean leaves, the blue edge position of the dust leaves increased, the slope of yellow and red edge of the dust leaves decreased, the area of yellow and red edge of the dust leaves decreased. The R2 value of prediction model of foliar dust content being built with red edge index is the largest (0.716). A certain relationship between foliar dust content and spectrum were existed.【Conclusion】The foliar dust increased the reflectance in visible light wave band, but decreased the reflectance at near infrared region. Certain correlation with leaves internal structure may exist. We can predict leaf surface dust content in a certain precision range by taking red edge index (SDr) as parameter. Simple ratio index is positively correlated with the content of foliar dust. The interference of spectrum detection by foliar dust has been preliminary quantitative discussed in this paper, which supplied a reference method for the future evaluation of foliar dust impact on the spectral reflectance and establish a modified model.

Key words: haze, foliar dust, spectral reflectance, Euonymus japonicas

CLC Number: