关键词: 哑变量, 香格里拉高山松, 森林蓄积量, 线性回归模型中

Abstract:

Based on Landsat TM and field survey data,two strategies were adopted to construct shangri-la Pinus Densata stock volume inversion model:conventional linear regression model and linear regression model with dummy variable,and the inversion model was validated.According to the research,correlation coefficients of conventional linear regression with simple regression and multiple regression were 0.280 and 0.365 respectively,while the linear regression model with dummy variable had a correlation coefficient of 0.602;Comparing with test sample data,the prediction accuracies of conventional linear regression model were 61.1% and 74.9% respectively,while the accuracy of linear regression model with dummy variable was 80.3%.It was proven that applying dummy variable could certainly raise the prediction accuracy and provide a reliable reference for forest stock volume inversion via dummy variable in remote sensing to some extent.

Key words: dummy variable, Shangri-la Pinus Densata, forest volume, linear regression model