本文以云南省森林分区中的六个林区内栎类林为研究对象，以Landsat8

This paper takes the oak forests in six forest areas in the forest division of Yunnan Province as the research object, and takes Landsat8 OLI remote sensing image as the information source. On the basis of it, single-band information, vegetation index and other remote sensing feature factors were extracted; based on the 2016 Yunnan Forest Resources Survey data, an oak single tree biomass model was established to calculate the unit biomass of the oak forest ground, and 3 times the standard deviation was used Random screening of small-scale sample plots where unit biomass meets the research content is divided into model plots and test plots; after correlation analysis of unit biomass and remote sensing feature factors on oak forest land in each study area, according to single-band information and oaks the relationship between the forest biomass unit, determining the biomass oak saturation value of each study area, linear regression models were constructed and the mixed effect model to estimate regional oak forest biomass, results showed that: <br>(1) based Landsat8 OLI Optical remote sensing images determine the saturation value of oak forest biomass in each study area, which can be calculated by:

本文以云南省森林分区中的六个林区内栎类林为研究对象，以Landsat8 OLI遥感影像为信息源，在对影像进行辐射定标、大气校正、地形校正、裁剪及镶嵌等预处理的基础上，提取了单波段信息、植被指数等遥感特征因子；基于2016年云南省森林资源调查数据，建立栎树单木生物量模型计算出栎类林地上单位生物量，并利用3倍标准差随机筛选单位生物量满足研究内容的小班样地，分为建模样地和检验样地；通过各研究区栎类林地上单位生物量与遥感特征因子相关性分析后，根据单波段信息与栎类林单位生物量之间的关系，确定各研究区栎类林生物量饱和值，分别构建线性逐步回归模型和区域混合效应模型来估测栎类林生物量，结果表明：<br>（1）基于Landsat8 OLI光学遥感影像确定各研究区栎类林生物量饱和值，通过计算得出：

In this paper, the oak forest in six forest areas of Yunnan province is taken as the research object, and Landsat8 is taken as the research object The oli remote sensing image is the information source. On the basis of the image preprocessing such as radiometric calibration, atmospheric correction, terrain correction, clipping and mosaic, the single band information, vegetation index and other remote sensing characteristic factors are extracted. Based on the forest resources survey data of Yunnan Province in 2016, the single tree biomass model of oak is established to calculate the unit biomass of oak forest land, and the standard deviation of 3 times is used to follow Based on the correlation analysis between the unit biomass and the remote sensing characteristic factors in each study area, the saturation value of the oak forest biomass in each study area was determined according to the relationship between the single band information and the unit biomass of the oak forest, and the linear stepwise regression model and the regional mixture model were constructed The combined effect model was used to estimate the biomass of Quercus forest<br>(1) Based on Landsat 8 oli optical remote sensing image, the biomass saturation value of oak forest in each study area was determined<br>