Urban and transportation planning require land-use inventory (2D and 3D city models) to support the visualization and analysis of land-use patterns in the context of existing and future situations. These patterns impact travel behaviour, resulting in traffic volume and travel mode alteration. Thereby, identifying different land uses is crucial to transportation/urban planning studies. In particular, buildings as the “containers” of socio-economic activities are among the most important objects as they are constantly subjected to construction and destruction. On the other hand, providing precise building information such as floor space data is a vital input for integrated landuse transportation models (ILUTM). Moreover, a more cost-effective building information collection method is required to replace traditional ground survey techniques or estimation methods practiced in transportation related studies. Airborne laser scanning commonly referred to as LiDAR is an established technology which can collect the location and elevation of the reflecting surfaces of large areas. Building extraction from LiDAR data is a delicate process only available in high-end extraction solution software. By utilizing a normal LiDAR analysis program, this paper attempts to compare the accuracy of building information (e.g. building footprints and height) extracted from LiDAR data with the ground truth information at several zonal levels, e.g., Census block or tract, from the south side of the City of Fredericton. The accuracy of building information extracted from LiDAR data is quantified, and its applicability for land use and transportation is verified. Study results show that LiDAR technology is a timely and cost-effective approach for extracting building/land use information, and it can be considered as a valuable tool for sustainable urban/transportation planning