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Forest and Grassland Resources Research >

2023 , Vol. 0 >Issue 2: 104 - 110

DOI: https://doi.org/10.13466/j.cnki.lyzygl.2023.02.014

Technical Application

Above-Ground Biomass Prediction of Arbor Forest in Altay Mountain Area Based on High-Resolution Remote Sensing Data

  • Huifang ZHANG ,
  • Yali ZHU ,
  • Jinglu ZHANG ,
  • Jian GAO ,
  • DILIXIATI·Baoerhan
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  • Modern Forestry Research Institute of Xinjiang Academy of forestry,Urumqi 830000,China

Received date: 2023-02-20

  Revised date: 2023-04-24

  Online published: 2023-06-26

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Abstract

In order to accurately and conveniently estimate forest biomass at the regional scale,remote sensing characteristic variables such as vegetation index and texture were extracted based on high-resolution remote sensing data and field survey data,and the nearest neighbor algorithm (k-NN) was used to construct a forest aboveground biomass prediction model.The results showed that using k-NN to quantitatively estimate the biomass of tree forests at the regional scale,when k value was 2 and the characteristics were B1 (band 1),SR (simple vegetation index),NDVI (normalized vegetation index) and B4 (band 4),the forest biomass estimation results were optimal.The above ground biomass was 8 039 000 tons,and the average biomass per unit area was 82.15 t/hm2.When the main age group of arbor forest wasmature forest,its area and biomass ratio werethe highest.The unit biomass of arbor forest was higher in the altitude range of 1 500 ~ 2 400m.

Key words： arbor forest; above-ground biomass; nearest neighbor algorithm (k-NN); remote sensing inversion; feature selection

Cite this article

Huifang ZHANG , Yali ZHU , Jinglu ZHANG , Jian GAO , DILIXIATI·Baoerhan . Above-Ground Biomass Prediction of Arbor Forest in Altay Mountain Area Based on High-Resolution Remote Sensing Data[J]. Forest and Grassland Resources Research, 2023 , 0(2) : 104 -110 . DOI: 10.13466/j.cnki.lyzygl.2023.02.014

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