Automated derivation of urban building density information using airborne LiDAR data and object-based method
作者： Bailang Yu , Hongxing Liu , Jianping Wu , Yingjie Hu , Li Zhang
DOI: 10.1016/J.LANDURBPLAN.2010.08.004
关键词:
摘要: Building density information is fundamentally important for urban design, planning and management environmental studies. This paper demonstrates that Coverage Ratio (BCR), Floor Area (FAR), other building indicators can be numerically automatically derived from high-resolution airborne LiDAR data. An object-based method proposed to process the data information. The consists of a sequence numerical operations: generating normalized Digital Surface Model (nDSM), extracting objects, deriving object attributes, associating objects with corresponding land lots, computing at lot district scales. algorithms these operations have been implemented as an ArcGIS extension module. applied processing over downtown Houston. Various attributes quantify density, physical structure, landscape morphological characteristics area three different spatial
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