A novel algorithm for regularization of building footprints using raw LiDAR point clouds

Abstract

This study proposes an automatic building outline regularization approach (ABORE) that produces two-dimensional orthogonal building boundaries from irregular building footprint polygons with building edge points using raw LiDAR point cloud data. The proposed approach was evaluated on the combinations of single, double, and multiple buildings from seven LiDAR datasets with different point density. The accuracy of the building edge geometries regularized by the ABORE method was compared with the reference data without requiring any additional data. Test results showed that the mean completeness (Cp), correctness (Cr), and quality (Q) values for single buildings were estimated as 98.96, 99.32, 98.30% and for multiple buildings as 99.55, 99.74, 99.29%, respectively. These results indicate superior performance (by about 5% F-score improvement) in comparison to state-of-the-art methods with a higher correctness rate in building boundary regularization. ABORE was also found effective in the delineation of complex buildings with many corners and short edges.

Keywords:

• Regularization
• building boundary
• building footprint
• point cloud
• LiDAR

Disclosure statement

No potential conflict of interest was reported by the author(s).

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.