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Forest and Grassland Resources Research >

2023 , Vol. 0 >Issue 4: 132 - 140

DOI: https://doi.org/10.13466/j.cnki.lyzygl.2023.04.016

Technical Application

Geographic Weighted Regression Model Combined with Remote Sensing for Estimating Forest Aboveground Carbon Storage of Songyang County

  • Weimin ZOU ,
  • Chao CHEN ,
  • Lei HUANG ,
  • Meixuan SONG ,
  • Xuejian LI ,
  • Huaqiang DU
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  • 1. Ecological Forestry Development Center,Songyang,Zhejiang 323400,China
    2. School of Environmental and Resources Science,Zhejiang A & F University,Lin’an,Zhejiang 311300,China

Received date: 2023-06-14

  Revised date: 2023-07-15

  Online published: 2023-10-16

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Abstract

Aboveground carbon(AGC)is an important indicator of the basic characteristics of forest ecosystems and a theoretical basis for evaluating the functional structure and productive potential of forests.As one of the nine key forestry counties in Zhejiang Province,Songyang County has a very important ecological status,so the accurate estimation of forest AGC in Songyang County is an important reference value for the stability evaluation of forest ecosystems and forest management in Songyang County.However,Songyang County is dominated by medium and low hilly areas surrounded by mountains,and how to consider the influence of complex terrain on the temporal and spatial variation of AGC is an urgent problem to be solved to achieve accurate estimation of AGC in mountainous forests.Therefore,based on Landsat TM satellite imagery and forest AGC survey data in Songyang County,a geographically weighted regression model(GWR)combined with spatial variation characteristics was constructed to estimate forest AGC,and compared with the results of ordinary least squares(OLS),finally,the optimal model was selected to predict forest AGC and its spatial distribution in Songyang County.The results were asfollows:Texture information from Landsat TM satellite imagerywas important for predicting forest AGC in Songyang County;The GWR model accurately estimated the AGC and spatial distribution of forests in Songyang County,and improved the accuracy by 9% over the OLS model,with an R2 of 0.71.The total AGC of forests in Songyang County was 3.901×106 Mg,with an average AGC of 23.70 Mg/hm2,accounting for about 10% of the total AGC of forest vegetation in Lishui City,which had a relatively important position in serving regional ecological functions.The study will provide advanced technical tools for accurate estimation of forest AGC in Songyang County,as well as scientific data for evaluating the function of forest carbon sink in Songyang County.

Key words： forest aboveground carbon storage; remote sensing; geographic weighted regression; model; Songyang County

Cite this article

Weimin ZOU , Chao CHEN , Lei HUANG , Meixuan SONG , Xuejian LI , Huaqiang DU . Geographic Weighted Regression Model Combined with Remote Sensing for Estimating Forest Aboveground Carbon Storage of Songyang County[J]. Forest and Grassland Resources Research, 2023 , 0(4) : 132 -140 . DOI: 10.13466/j.cnki.lyzygl.2023.04.016

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