ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Citation
Articles | Volume II-3/W5
https://doi.org/10.5194/isprsannals-II-3-W5-203-2015
https://doi.org/10.5194/isprsannals-II-3-W5-203-2015
19 Aug 2015
 | 19 Aug 2015

TOWARDS A GENERIC METHOD FOR BUILDING-PARCEL VECTOR DATA ADJUSTMENT BY LEAST SQUARES

Y. Méneroux and M. Brasebin

Keywords: Geometric Quality, Constrained Optimization, Least Squares, Minkowski Inner-fit Polygon, Vector Data Conflation

Abstract. Being able to merge high quality and complete building models with parcel data is of a paramount importance for any application dealing with urban planning. However since parcel boundaries often stand for the legal reference frame, the whole correction will be exclusively done on building features. Then a major task is to identify spatial relationships and properties that buildings should keep through the conflation process. The purpose of this paper is to describe a method based on least squares approach to ensure that buildings fit consistently into parcels while abiding by a set of standard constraints that may concern most of urban applications. An important asset of our model is that it can be easily extended to comply with more specific constraints. In addition, results analysis also demonstrates that it provides significantly better output than a basic algorithm relying on an individual correction of features, especially regarding conservation of metrics and topological relationships between buildings. In the future, we would like to include more specific constraints to retrieve the actual positions of buildings relatively to parcel borders and we plan to assess the contribution of our algorithm on the quality of urban application outputs.