Automatic Building Change Detection Using Multi-Temporal Airborne Lidar Data

R. C. dos Santos, M. Galo, A. C. Carrilho, G. G. Pessoa, R. A. R. de Oliveira
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引用次数: 8

Abstract

The automatic detection of building changes is an essential process for urban area monitoring, urban planning, and database update. In this context, 3D information derived from multi-temporal airborne LiDAR scanning is one effective alternative. Despite several works in the literature, the separation of change areas in building and non-building remains a challenge. In this sense, it is proposed a new method for building change detection, having as the main contribution the use of height entropy concept to identify the building change areas. The experiments were performed considering multi-temporal airborne LiDAR data from 2012 and 2014, both with average density around 5 points/m2. Qualitative and quantitative analyses indicate that the proposed method is robust in building change detection, having the potential to identify small changes (larger than 20 m2). In general, the change detection method presented average completeness and correctness around 97% and 71%, respectively.
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基于多时相机载激光雷达数据的楼宇变化自动检测
建筑物变化的自动检测是城区监控、城市规划和数据库更新的重要环节。在这种情况下,从机载激光雷达扫描中获得的三维信息是一种有效的选择。尽管在文献中有一些工作,建筑和非建筑的变化区域的分离仍然是一个挑战。在此基础上,提出了一种新的建筑变化检测方法,其主要贡献是利用高度熵的概念来识别建筑变化区域。实验采用2012年和2014年多时段机载LiDAR数据,平均密度均在5个点/m2左右。定性和定量分析表明,所提出的方法在建筑变化检测方面是稳健的,具有识别小变化(大于20平方米)的潜力。总体而言,变更检测方法的平均完整性和正确性分别在97%和71%左右。
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