因人类社会目前正面临着巨大的生态环境危机，如何强化森林资源经营管理，以便 实现林业的可持续发展，已经成为越来越多国家的共识。森林蓄积量是林业资源调查的 重要方面之一，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，建立监测区域森林蓄积量估测方 程，估测森林蓄积量，最大限度的减少野外调查工作量，已成为目前国内外林业遥感科 技工作者关注和研究的热点问题。 本论文以森林蓄积量遥感定量估测理论研究成果为的基础，利用C#语言在ArcGIS Engine9.3 平台上开发一套 “森林蓄积量遥感定量估测系统”。以便根据监测区域一、 二类地面样地调查资料及遥感图像，选择影响蓄积量估测的主要遥感和GIS 因子；用影 响蓄积量的估测的主要因子刻画样地，对监测区样地进行分类；在分类的基础上，抽取 能够代表监测区域森林资源分布状况的样地；根据所抽样地建立以样地大小为单位的蓄 积量估测模型；将遥感图像分割为以样地大小为单位的图像，借助监测区域的DEM 数据， 林班、小班分布图，获取监测区域以样地大小为单位，影响蓄积量估测的主要遥感和GIS 因子的值；求解监测区蓄积量总体分布图；估测监测区域的总蓄积量、林班和小班的蓄 积量。 最后，利用云南省思茅地区7500 2 km 范围内的81 个一类调查样地、监测区分辨率 为2.5m 的SPOT5 遥感影像、分辨率为25m 的DEM 数据和林班分布图，对“森林蓄积量 遥感定量估测系统”进行有效性验证。验证结果表明，监测区模型预报精度达到85.21%， 能满足森林资源调查的精度要求。

As human society is now facing great crisis of ecological environment. Strengthen the management of forest resources, to achieve the sustainable development of forestry has become more and more national consensus. The forest stock volume is one of an important part of forestry resource survey, the traditional survey of the forest resources is a cycle long, the task is heavy, large labor intensity, and requires a large number of funds work. How to use 3S technology, combined with a small amount of ground sample information, to establish the estimation equation of the forest volume in the monitoring regions to estimation of the forest stock volume, maximum reduction of field survey work, which has always been a concern of by the domestic and foreign forestry remote sensing science and technology workers. This research developed a computer system via C# and ArcGIS Engine9.3, which based on the theory of forest stock volume quantitative estimation by remote sensing. The system would selects the best impact of remote sensing factors and GIS factors from the forestry survey data and remote sensing image of the monitoring area; depicts sample plots by the best impact of factor, classifies those sample plots; extract the establishment of reserves Estimation of sample plots. The next step is establishing the volume estimation model by the extracted sample plots, converts remote sensing image cell size to the size of a sample plot; getting the values of main remote sensing and GIS factors with DEM and survey data of the monitoring regional; creating the forest volume distribution map for the monitoring area and the system would compute the volume the total stock volume of the monitoring regional or the stock volume of any compartment or sub compartment. Finally, I text “the system of forest volume quantitative estimation by remote sensing” by Yunnan province Simao 7500 areas within the 81 sample plots, the monitoring area of high resolution of 2.5m SPOT5 remote sensing image、resolution of 25m DEM data and the Sub-compartment distribution map. The results show that the monitoring area of the volume estimation model accuracy reached 85.21%, to meet the precision requirement of forestry production.