LiDAR SIGNATURES TO UPDATE JAPANESE BUILDING INVENTORY DATABASE

摘要

Developing an efficient method to quickly update the building inventory database of dense urban areas is our focus of interest. Disaster mitigation requires an up-to-date and reliable building inventory database for damage assessment. However, it has been slowly updated through conventional procedure comprising the compiling aerial photographs, manually or semiautomatic updating GIS database and manually inputting attributes from submitted documents. LiDAR providing very dense point clouds with X, Y, Z coordinates and pulse intensity is proposed as primary data for a better flowchart of updating. This study developed a comprehensive method to detect and classify the buildings from LiDAR data based on sizes and height. Testing with data acquired over Roppongi area of Tokyo, Japan demonstrated the capability of the proposed method. It inferred that promising results derived by an automatic processing LiDAR data seems to be a better solution to update building inventory database in dense urban areas. Elevation and intensity distribution of the laser points will be integrated in further improvement.