The use of woody biomass from forest is becoming of interest in Japan, its amount and availability should be discussed in a spatial manner. Airborne laser scanning (ALS) technology enables three-dimensional information of objects on the ground to be obtained, and such data can provide valuable information for forest management that can contribute to biomass utilization planning. This study examines the use of such ALS data for classifying vegetation types in a forest in Kyoto city, Japan. Training sample plots were established based on five different vegetation type classes; five variables were then calculated from each plot’s ALS data, and the effectiveness of the variables was quantified. Of the five variables, the coefficient of variation (CV) and the only fraction (OF) were the most effective, and consequently were used in the classification analysis to generate a map of vegetation types across the study area. The accuracy assessment yielded a kappa coefficient of agreement of 0.79. This study demonstrates that ALS data can be successfully used to discriminate between different vegetation types of forests in urban area that have good potential for biomass utilization.