A Big Data Approach for 3D Building Extraction from Aerial Laser Scanning
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|Title:||A Big Data Approach for 3D Building Extraction from Aerial Laser Scanning||Authors:||Aljumaily, Harith
Laefer, Debra F.
|Permanent link:||http://hdl.handle.net/10197/7450||Date:||May-2016||Abstract:||This paper proposes a Big Data approach to automatically identify and extract buildings from a digital surface model created from aerial laser scanning data. The approach consists of two steps. The first step is a MapReduce process where neighboring points in a digital surface model are mapped into cubes. The second step uses a non-MapReduce algorithm first to remove trees and other obstructions and then to extract adjacent cubes. According to this approach, all adjacent cubes belong to the same object and an object is a set of adjacent cubes that belong to one or more adjacent buildings. Finally, an evaluation study is presented for a section of Dublin, Ireland to demonstrate the applicability of the approach resulting in a 92% quality level for the extraction of 106 buildings over 1 km2 including buildings that had more than 10 adjacent components of different heights and complicated roof geometries. The proposed approach is notable not only for its Big Data context but its usage of vector data.||Funding Details:||European Research Council
Science Foundation Ireland
|Type of material:||Journal Article||Publisher:||American Society of Civil Engineers||Copyright (published version):||2016 American Society of Civil Engineers||Keywords:||Building extraction;MapReduce;Big data;LiDAR;Digital surface model;Aerial laser scanning||DOI:||10.1061/(ASCE)CP.1943-5487.0000524||Language:||en||Status of Item:||Peer reviewed|
|Appears in Collections:||Earth Institute Research Collection|
Civil Engineering Research Collection
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