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Forest and Grassland Resources Research >

2016 , Vol. 0 >Issue 5: 59 - 64

DOI: https://doi.org/10.13466/j.cnki.lyzygl.2016.05.011

Scientific Research

Pixel Mean Variance Parabola Fitting of Pinus densata Abundance Based on Topographic Factors

  • JIANG Shengchang ,
  • ZHANG Jialong ,
  • LU Chi ,
  • XU Hui ,
  • HUANG Chuanxi ,
  • LUO Yunjiang
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  • 1. Faculty of Forestry,Southwest Forestry University,Kunming 650224,Yunnan,China;
    2. 3S Technology and Engineering Research Center in Forestry of the Yunnan Universities,Southwest Forestry University,Kunming 650224,Yunnan,China

Received date: 2016-07-20

  Revised date: 2016-09-08

  Online published: 2020-11-02

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Abstract

Four typical research sample areas which are boundary mixed were selected based on Landsat8 images.The method of slope matching was used to do topographic corrections.The abundance of the Pinus densat was extracted using the method of linear spectral separation(LSU),matched filtering(MF),the minimum energy constraint(CEM),the pixel mean variance parabola(PMVP).The results of the abundance show that the order of the average root mean square error values of the four typical sample areas is:LSU <PMVP<CEM <MF.The PMVP could better separate Pinus densat boundary with a good result.Using PMVP to extract abundance has achieved higher accuracy.It could also explore more suitable curve fitting methods applied to the extraction of forest tree species abundance and land cover classification in the future.

Key words： Pinus densata; mixed pixel unmixing; Shangri-La; Landsat 8; pixel mean variance parabola fitting

Cite this article

JIANG Shengchang , ZHANG Jialong , LU Chi , XU Hui , HUANG Chuanxi , LUO Yunjiang . Pixel Mean Variance Parabola Fitting of Pinus densata Abundance Based on Topographic Factors[J]. Forest and Grassland Resources Research, 2016 , 0(5) : 59 -64 . DOI: 10.13466/j.cnki.lyzygl.2016.05.011

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