Spatial variations of maximum canopy height are key indicators of many ecosystem processes such as aboveground biomass and productivity. With rapid advances in remote sensing techniques, such as airborne laser scanning (ALS), we can now measure canopy height, tree density, and canopy gaps from local to large scales. But these data are yet to be fully exploited for a better understanding of canopy height variations in relation to fine topographical heterogeneities and neighborhood conditions at the landscape level (>100 km2). In this study, we analyzed ALS data to extract spatial variations in canopy height and topographic features for a forest-dominated area of 230 km2 in Kyoto, Japan. The study area spanned an elevational range from 70 to 1000 m a.s.l and included four forest types, i.e., cedar or cypress plantations (PL), natural evergreen needle leaf forests (ENF), deciduous broadleaved forests (DBF), and evergreen broadleaved forests (EBF). PL had a greater mean canopy height than ENF, both of which were taller than DBF and EBF. Canopy height exhibited a hump-shaped relationship with elevation with the peak value at mid-altitude (461-560 m) in all forest types. Canopy height was greater by 5-10 m in the concave valleys than on the convex slopes and ridges. Trees were taller at greater distances from forest gaps and with lower tree density in the neighborhood. Local tree density, distance from the nearest canopy gap, and topographic curvatures were the most significant predictors in the best-fitted model (Random Forest: R2 = 0.41). The analytical approach developed in this study provides a useful tool for planning proper land use and maintaining a healthy forest stand at the regional scale.