中文摘要：

借助SPSS统计软件和ERDAS IMAGINE9.0/ArcGIS9.2的建模及空间分析工具,采用TM影像和1∶100000地形图作为数据源,从TM影像提取野外GPS采样点缓冲区内6个波段的灰度值及其线性和非线性组合等遥感因子,从地形图提取海拔、坡度、坡向等GIS因子,以各遥感因子和GIS因子作为自变量,以GPS野外调查样点缓冲区内的蓄积量作为因变量建立多元线性回归模型。样本数据筛选采用标准差法,因子变量筛选采用主成分因子分析法、多元线性回归的逐步回归和强行进入法等方法,建立的多元回归模型预测总体精度达到87.35%。用2006年山东省TM影像提取的有林地掩膜模型中各因子变量灰度图,得到各因子变量的掩膜图层。将各因子变量的掩膜图层代入多元回归模型进行复合运算,得到有林地蓄积量灰度图像。经蓄积量灰度图像属性表统计得到山东省的有林地总蓄积量为6203.53万m3,为快速、准确地对大面积的森林蓄积量估测提供一种有效的途径和方法。

英文摘要：

Recurring to the SPSS and the model building and spatial analysis tools of ERDAS IMAGINE9.0 ＆amp; ArcGIS9.2,this paper adopted TM images and 1∶100 000 relief map as the data source,extracted RS factors such as pixel value of six wave bands and theirs linear ＆amp; non-linear combination from TM images using the buffer area of GPS points,and extracted GIS factors such as elevation,slope and aspect from relief map. RS factors ＆amp; GIS factors were set as independent variables and field investigated forest volume data were set as dependent variable to build the multi-regression model. Sample data were selected by standard deviation law and factor variables were selected by the method of principal components analysis, stepwise and enter regression analysis. The forecast precision of the model is 87.35 %. The grey images of each variable in themodel were masked by the forest land extracted from the TM images of Shandong Province and got the masking image of each variable. The paper calculated the total forest volume of Shandong Province by the complicated operation of all the masking images using the multiregression model. The result shows that the total forest volume of Shandong Province is 62 035 300 m3 . The study provided an effective way to estimate the forest volume of large area.