Abstract
Building footprint geometry is a basic layer of information required by government institutions for a number of land management operations and research. LiDAR (light detection and ranging) is a laser-based altimetry measurement instrument that is flown over relatively wide land areas in order to produce digital surface models. Although high spatial resolution LiDAR measurements (of around 1 m horizontally) are suitable to detect aboveground features through elevation discrimination, the automatic extraction of buildings in many cases, such as in residential areas with complex terrain forms, has proved a difficult task. In this study, we developed a method for detecting building footprint from LiDAR altimetry data and tested its performance over four sites located in Austin, TX. Compared to another standard method, the proposed method had comparable accuracy and better efficiency.
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Silván-Cárdenas, J.L., Wang, L. (2011). Extraction of Buildings Footprint from LiDAR Altimetry Data with the Hermite Transform. In: Martínez-Trinidad, J.F., Carrasco-Ochoa, J.A., Ben-Youssef Brants, C., Hancock, E.R. (eds) Pattern Recognition. MCPR 2011. Lecture Notes in Computer Science, vol 6718. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21587-2_34
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DOI: https://doi.org/10.1007/978-3-642-21587-2_34
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