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FOREST RESOURCES WANAGEMENT ›› 2021, Vol. 0 ›› Issue (6): 90-96.doi: 10.13466/j.cnki.lyzygl.2021.06.015

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Estimation of Leaf Nitrogen of Betula Platyphylla in Burned Area of Daxing'anling,Inner Mongolia

YANG Xiaoyu(), WANG Bing(), ZHANG Pengjie   

  1. Forestry College,Inner Mongolia Agricultural University,Hohhot 010019,China
  • Received:2021-09-03 Revised:2021-09-22 Online:2021-12-28 Published:2022-01-12
  • Contact: WANG Bing E-mail:905018620@qq.com;wbingbing2008@126.com

Abstract:

Taking the burned areas in Daxing'anling of Inner Mongolia in 1987 and 2003 as the study area and Betula Platyphylla leaves as the research object,the spectral bands with strong correlation with the nitrogen content were selected,and the optimal prediction model of nitrogen content was constructed by multiple stepwise regression and nonlinear regression methods. The results showed that: 1) the nitrogen content of Betula platyphylla leaves in burned areas of 1987 and 2003 were 25.22 and 17.23 g/kg,respectively. The trend of leaf spectral curves in two areas was consistent,and the difference was only reflected in the "green peak" and "red edge". 2) According to the correlation coefficients between leaf nitrogen content and measured spectrum and its first derivative,67 bands (1987) and 40 bands (2003) were selected. 3) The multiple stepwise regression model and nonlinear regression model of nitrogen content of Betula platyphylla leaves were established by using the high correlation bands as independent variables. The prediction effect of multiple stepwise regression model was better than that of nonlinear regression model. The change of nitrogen content will affect the spectral sensitivity of plants. The more nitrogen content,the lower the spectral reflectance at green band and near infrared band was;The multiple stepwise regression model can be used to predict the nitrogen content of Betula platyphylla leaves in the burned area of Daxing'anling.

Key words: Betula platyphylla, leaf nitrogen, spectral characteristics, prediction model

CLC Number: