Building Footprint and Height Information Extraction from Airborne LiDAR and Aerial Imagery

Building footprint and height information is critical for urban studies and applications. Subsequently, urban planning or development departments dedicate a large amount of time and money to develop and maintain a database for building footprint and height. Currently, many methods exist for building footprint and height information extraction. However, it is still an expensive, time-consuming, and labor-intensive process to obtain this information. Recent advances in remote sensing, such as airborne LiDAR, high-spatial resolution aerial photography, and object-based image analysis (OBIA) techniques, provide new methods to accurately and rapidly extract building footprint and height information at a low cost. This study used airborne LiDAR data to extract objects such as buildings and trees. Then color-infrared aerial photos were used to remove trees from the detected objects. Subsequently, OBIA was used to delineate building footprints, while zonal statistics was used to extract building height information. The extracted building footprint and height data were compared to the ground-truth data, and the results revealed that color-infrared aerial photos provide important and irreplaceable information to effectively remove trees that being false positively detected as buildings, OBIA can be used to accurately delineate building footprint, while zonal statistics can be used to extract building height information.