Font Size:  Small  Medium  Large

Enhancing building footprints with squaring operations

Imran Lokhat, Guillaume Touya

Abstract


Whatever the data source, or the capture process, the creation of a building footprint in a geographical dataset is error prone. Building footprints are designed with square angles, but once in a geographical dataset, the angles may not be exactly square. The almost-square angles blur the legibility of the footprints when displayed on maps, but might also be propagated in further applications based on the footprints, e.g., 3D city model construction. This paper proposes two new methods to square such buildings: a simple one, and a more complex one based on nonlinear least squares. The latter squares right and flat angles by iteratively moving vertices, while preserving the initial shape and position of the buildings. The methods are tested on real datasets and assessed against existing methods, proving the usefulness of the contribution. Direct applications of the squaring transformation, such as OpenStreetMap enhancement, or map generalization are presented.

Full Text: PDF

Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.