Semi-Automatic Classification of Building From Low-Density Lidar Data and Worldview-2 Images Through OBIA Technique

In this paper, an in-depth study is presented regarding an innovative methodology on which the authors have invested several months of research, as evidenced by their recent references on similar topics. A semi-automatic classification of the buildings in urban area is analyzed, when Light Detection And Ranging (LiDAR) data are combined to Very High Resolution (VHR) WorldView-2 (WV-2) images and an Object-Based Image Analysis (OBIA) technique is used. The aim of the data fusion from different sensor types is to realize an effective and limited-cost product for protection and management of environmental and natural resources, to meet the needs of many institutions, such as municipalities, provinces and regions, and for applications in the context of risk analysis, territorial planning and local development. This procedure may be extended to large areas of the territory, resulting into a reduction of the processing time for the building detection, with respect to a human visual or manual photointerpretation. Interesting results and further implications will be presented and discussed.