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- W163042985 abstract "In the past decade, airborne based LIght Detection And Ranging (LIDAR) has been recognised by both the commercial and publicsectors as a reliable and accurate source for land surveying in environmental, engineering and civil applications. Commonly, the firsttask to investigate LIDAR point clouds is to separate ground and object points. Skewness Balancing has been proven to be an efficientnon-parametric unsupervised classification algorithm to address this challenge. Initially developed for moderate terrain, this algorithmneeds to be adapted to handle sloped terrain. This paper addresses the difficulty of object and ground point separation in LIDAR datain hilly terrain. A case study on a diverse LIDAR data set in terms of data provider, resolution and LIDAR echo has been carriedout. Several sites in urban and rural areas with man-made structure and vegetation in moderate and hilly terrain have been investigatedand three categories have been identified. A deeper investigation on an urban scene with a river bank has been selected to extend theexisting algorithm. The results show that an iterative use of Skewness Balancing is suitable for sloped terrain." @default.
- W163042985 created "2016-06-24" @default.
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- W163042985 date "2007-01-01" @default.
- W163042985 modified "2023-09-27" @default.
- W163042985 title "Case study: object and ground point separation on a river bank using airborne based LIDAR data" @default.
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