Boundaries between different forest types in Changbai Mountain Eastern China are results from complex interactions between forest ecosystems, topography, and geomorphology. Detecting and quantifying the transitional zones are highly important since high environmental heterogeneity and biodiversity are often found within these zones. In this study, we used GIS and multivariate statistics techniques(PCA and MSWA) to analyze data from Landsat TM satellite imageries and quantitatively determined the positions and widths of the landscape boundary between mountain birch and evergreen coniferous forests in the northern slope of Changbai Mountain. The results showed that the widths of the landscape boundary ranges from 30—50m while using the MSWA or/and PC method. Such detected widths are consistent with field transect data that suggests a 50m transitional zone width. The results further suggest that TM data can be used in combination with GIS and statistical techniques in determining forest landscape boundaries; MSWA is more reliable than PCA, while PCA can also be used to determine the landscape boundary when transects are properly located. Boundaries between different forest types in Changbai Mountain Eastern China are results from complex interactions between forest ecosystems, topography, and geomorphology. Detecting and quantifying the transitional zones are highly important since high environmental heterogeneity and biodiversity are often found within these zones. In this study, we used GIS and multivariate statistics techniques (PCA and MSWA) to analyze data from Landsat ™ satellite imageries and quantitatively determined the positions and widths of the landscape boundary between mountain birch and evergreen coniferous forests in the northern slope of Changbai Mountain. The results said that the widths of the landscape boundary ranges from 30-50m while using the MSWA or / and PC method. The detected widths are consistent with field transect data that suggests a 50m transitional zone width. The results further suggest that TM data can be used in combination with GIS and statistical techniques in determining forest landscape boundaries; MSWA is more reliable than PCA, while PCA can also be used to determine the landscape boundary when transects are properly located.