Abstract
Light detection and ranging (LiDAR) technology has become a standard tool for three-dimensional mapping because it offers fast rate of data acquisition with unprecedented level of accuracy. This study presents an approach to accurately extract and model building in three-dimensional space from airborne laser scanning data acquired over Universiti Putra Malaysia in 2015. First, the point cloud was classified into ground and non-ground xyz points. The ground points was used to generate digital terrain model (DTM) while digital surface model (DSM) was produced from the entire point cloud. From DSM and DTM, we obtained normalise DSM (nDSM) representing the height of features above the terrain surface. Thereafter, the DSM, DTM, nDSM, laser intensity image and orthophoto were combined as a single data file by layer stacking. After integrating the data, it was segmented into image objects using Object Based Image Analysis (OBIA) and subsequently, the resulting image object classified into four land cover classes: building, road, waterbody and pavement. Assessment of the classification accuracy produced overall accuracy and Kappa coefficient of 94.02% and 0.88 respectively. Then the extracted building footprints from the building class were further processed to generate 3D model. The model provides 3D visual perception of the spatial pattern of the buildings which is useful for simulating disaster scenario for emergency management.
Highlights
From visualization to functional solution goal oriented use, the need for three-dimensional (3D) building geometry has continued to grow over the last 3 decades
It was segmented into image objects using Object Based Image Analysis (OBIA) and subsequently, the resulting image object classified into four land cover classes: building, road, waterbody and pavement
As a result of this, 3D city modelling has been a subject of research interest to geographic information system (GIS) and remote sensing community for a range of applications such as urban planning, 3D cadastre, utilities and telecommunication facility management, architecture, safety, marketing, et cetera, using different approaches and data sources (Biljecki et al 2015)
Summary
From visualization to functional solution goal oriented use, the need for three-dimensional (3D) building geometry has continued to grow over the last 3 decades. Spatial information of buildings can be obtained from several sources, land surveying, airborne and space-borne platforms (Cheng et al 2011; Sampath & Shan 2007), the accuracy varies and this explains why it is still a subject of intensive research the years. Satellite image provides excellent source from which building footprints can be derived over wide coverage; small to medium scale geospatial enterprise may find the cost of high resolution satellite imagery prohibitive for their projects. Photogrammetric method has the benefit of medium to large aerial coverage, manoeuvrability in terms of time and weather and fast processing, but, the 3D data generated of low vertical accuracy (Mitchell & Macnabb 2010)
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