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Forest and Grassland Resources Research >

2017 , Vol. 0 >Issue 4: 59 - 68

DOI: https://doi.org/10.13466/j.cnki.lyzygl.2017.04.010

Scientific Research

Assessing the Impacts of Forest Background Reflectance on Estimating Aboveground Biomass—a case study of forest area in Great Khingan

  • Xiaoman LU ,
  • Guang ZHENG ,
  • Weimin JU ,
  • Shengpei DAI ,
  • Lun GAO
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  • International Institute for Earth System Science,Nanjing University,Nanjing 210023,China

Received date: 2017-04-22

  Revised date: 2017-06-06

  Online published: 2020-09-24

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Abstract

Remote sensing technology is of great importance to estimating large-scale forest canopy leaf characteristics dynamically,and there is a good statistical relationship between forest aboveground biomass (AGB) and leaf biomass.It is feasible to estimate leaf biomass and then AGB based on canopy effective leaf area index (LAIe) estimated from remotely sensed data.However,the forest background information,such as understory vegetation,has a negative influence on LAIe and AGB retrieval by this way.Therefore,this paper focused on exploring the impacts of forest background reflectance on LAIe and AGB inversion in the Great Khingan forest area using moderate resolution imaging spectroradiometer (MODIS) data and a four scale model.The results showed that both LAIe and AGB were sensitive to the forest background reflectance.The determinate coefficient (R2) between MODIS-and Landsat thematic mapper (TM)-based LAIe increased from 0.32 (n=25,p<0.1) to 0.48 (n=25,p<0.01) when eliminating the influence of background reflectance on LAI inversion.Also,the AGB estimates were more related to the national forest inventory (NFI)-based AGB after considering the effects of forest background (R2=0.86,n=10,p<0.01).Forest LAI and AGB overestimation could be put right in this research.

Key words： background reflectance; LAI; foliage biomass; forest AGB

Cite this article

Xiaoman LU , Guang ZHENG , Weimin JU , Shengpei DAI , Lun GAO . Assessing the Impacts of Forest Background Reflectance on Estimating Aboveground Biomass—a case study of forest area in Great Khingan[J]. Forest and Grassland Resources Research, 2017 , 0(4) : 59 -68 . DOI: 10.13466/j.cnki.lyzygl.2017.04.010

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