森林蓄积量是林业资源调查的重要内容之一，传统的森林资源调查是一项周期长、任务重、劳动强度大，需大量经费的工作。如何利用3S技术，结合少量地面样地资料，建立监测区域的森林蓄积量估测方程，估测森林蓄积量，最大限度的减少地面野外调查工作量，已成为目前林业上的热点问题。本文在研究过程中，查阅了大量国内外关于森林蓄积量估测方面的文献，结合实例，以TM遥感图像、地形图、森林资源调查资料为基本数据源，采用多元回归估计的方法—岭估计、逐步回归、偏最小二乘回归，初步建立了森林蓄积量与遥感灰度值、GIS信息之间的拟合模型，并对各解算方法得出的估测模型予以了拟合效果比较，探讨了森林蓄积量遥感估测的过程。 本论文的主要内容可以概述如下： 第一部分主要阐述了课题的研究背景、意义以及国内外研究现状。 第二部分详细介绍了森林蓄积量遥感估测的理论，包括森林蓄积量遥感估测的基本思想，实现步骤；如何最优选取影响蓄积量估测的遥感因子和GIS因子；如何抽取建立蓄积量估测的样地。 第三部分介绍了在森林蓄积量遥感估测中经常出现遥感因子和GIS因子之间存在多重相关性现象，介绍了多重相关性的含义以及它在森林蓄积量估测中的危害、如何诊断它们之间的多重相关性，并详细阐述了处理多重相关性的方法：岭估计、逐步回归、偏最小二乘回归。 第四部分，应用实例：在森林蓄积量遥感估测理论的基础上，对云南思茅地区7500 范围内的129个一类调查样地进行了分析，包括影响蓄积量估测18因子的最优因子选择、最优样地的抽取、各种回归方法的拟合实现以及各种方法拟合的比较。

Forest growing stock of forest resources is an important component of the survey, the traditional survey of forest resources is a long task, labor intensive, and require a lot of funding for the work. How to make use of 3S technology, combined with a small amount of ground sample data, the establishment of regional monitoring of forest volume estimation equations to estimate forest reserves, to minimize the workload of the ground field survey has become a hot issue. The paper with examples to TM remote sensing images, topographic maps, survey of forest resources as the basic data sources, using multiple regression methods of estimation - ridge estimation The stepwise regression, partial least-squares regression, the initial establishment of forest reserves and the gray value of remote sensing, GIS information on the fit between the model and calculation method of the estimation model derived from the fitting results to be compared of remote sensing to estimate forest volume process. The main contents of this paper can be summarized as follows: The first part introduced the background of the research, significance and research at home and abroad. The second part introduced the forest stock volume estimation of the theory of remote sensing, including remote sensing estimate of forest stock volume of the basic idea, the realization of these steps; how to select the best estimation of the impact of volume of remote sensing and GIS factor factor; how to extract the establishment of reserves Estimation of the sample. The third part described the meaning of the multiple correlation which appears in forest stock volume estimates between remote sensing and GIS factors and its estimation in the forest reserves of the hazards, how to diagnose their multiple correlation, and elaborated on the relevance of dealing with multiple methods: ridge estimation, stepwise regression, partial least-squares regression. The fourth part, Application: on the basis of Remote Sensing in forest stock volume estimation theory, analyzed the Simao region of Yunnan, 7500 within the scope of the survey for a class of 129 samples, including the impact of volume estimation of the optimal factor of 18 factor choice of optimal sample extraction, fitting a variety of methods to achieve the reunification, as well as comparison of various methods of fitting.