Comparative Study on Matching Methods for the Distinction of Building Modifications and Replacements Based on Multi-Temporal Building Footprint Data

Abstract

We compare different matching methods for distinguishing building modifications from replacements based on multi-temporal building footprint geometries from 3D city models. Manually referenced footprints of building changes were used to determine which thresholds are suitable for distinction. In addition, since the underlying LoD1 (Level of Detail 1) data is highly accurate, randomly generated position deviations were added to allow for transferability to less well-matched data. In order to generate a defined position deviation, a novel method was developed. This allows determination of the effects of position deviations on accuracy. Determination of these methods’ suitability for manipulation of data from sources of different levels of generalization (cross-scale matching) is therefore not the focus of this work. In detail, the methods of ‘Common Area Ratio’, ‘Common Boundary Ratio’, ‘Hausdorff Distance’ and ‘PoLiS’ (Polygon and Line Segment based metric) were compared. In addition, we developed an extended line-based procedure, which we called ‘Intersection Boundary Ratio’. This method was shown to be more robust than the previous matching methods for small position deviations. Furthermore, we addressed the question of whether a minimum function at PoLiS and Hausdorff distance is more suitable to distinguish between modification and replacement.

Keywords

• building change detection
• matching algorithms
• vector data
• footprints
• position deviation