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Object recognition and change detection of buildings based on airborne LiDAR
Leading article: 2019. August (MIAU No. 252.)
(Previous article: MIAU No. 251.)
Keywords: LiDAR, building recognition, change detection
Abstract: Nowadays, using modern LiDAR (Light Detection And Ranging) devices, it is
possible to cost-efficiently scan larger areas with high resolution even at
regular intervals, which provides an alternative data source for automated
analyses about the surface and its changes. The results can be directly
applied in various fields, e.g. in case of land use inspections, urban
planning, civil engineering, monitoring of environmental disasters (extent
of flood and waterlogging, earthquake damages), afforestation and
maintaining GIS databases. However, the data volume acquired from the laser
scans requires efficient processing or even the support of distributed
computations. In this study, I present a contour-based method for building
recognition. It provides favorable computer resource (memory and storage
space) requirement compared to other studies, with reasonable execution
time due to the utilization of local features. When comparing epochs of
multitemporal datasets to detect changes in the buildings of the scene, a
novel approach based on possible contour pairings has been worked out with
a limited capability to reconstruct lack or loss of information from the
previous steps. To demonstrate and validate the results, the public Dutch
altimetry archive (AHN), a multitemporal point cloud covering the entire
Netherlands and the governmental TOP10NL building records were used.
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