文章基本信息

标题：Automated 3d Mapping of Trees and Buildings and It's Application to Risk Assessment of Domestic Subsidence in The London Area
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作者：J. P. Muller ; J. R. Kim ; J. Kelvin 等
期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2004
卷号：XXXV Part B2
页码：826-831
出版社：Copernicus Publications
摘要：Very high resolution images (e.g. IKONOS) and airborne lidar have been used for the automated 3D mapping of individual tree and building locations in a large test area in East London of some 8 x 8km extent with many tens of thousands of buildings and trees. Initial results of the building and tree detection algorithm for small area assessments were given in Kim & Muller (2002). In this work we report on the extension of the algorithm to the full area and the refinement of the algorithm to extract tree height. Also shown will be the building detection's quantitative assessment using the OS. MasterMap. (Parish et al., 2003, submitted) and the random sample assessment of tree locations using higher resolution digitised aerial photography from different commercial suppliers. Overall the detection efficiency is greater than 75% even though the buildings have a huge range in floorplan, height, age and type. Tree detection efficiency is based on a visual assessment of the degree of overstorey crown overlap but has similarly high values
关键词：IKONOS; LIDAR; Vision;DEM/DTM;Urban; Vegetation; GIS; Geology; Subsidence risk assessment