Pattern classification approaches to matching building polygons at multiple scales

Pattern classification approaches to matching building polygons at multiple scales

Zhang, X.
Zhao, X.
Molenaar, M.
Stoter, J.
Kraak, M.J.
Ai, T.

OTB Research Institute for the Built Environment

OTB Research

2012-08-25

Matching of building polygons with different levels of detail is crucial in the maintenance and quality assessment of multi-representation databases. Two general problems need to be addressed in the matching process: (1) Which criteria are suitable? (2) How to effectively combine different criteria to make decisions? This paper mainly focuses on the second issue and views data matching as a supervised pattern classification. Several classifiers (i.e. decision trees, Naive Bayes and support vector machines) are evaluated for the matching task. Four criteria (i.e. position, size, shape and orientation) are used to extract information for these classifiers. Evidence shows that these classifiers outperformed the weighted average approach.

Data Matching
Multi-Scale Modeling
Map Generalization
Pattern Classification
Building Feature

http://resolver.tudelft.nl/uuid:c8f77d1b-6fb4-4bca-93b7-ed1069f40c3b

International Society for Photogrammetry and Remote Sensing

ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume I-2, XXII ISPRS Congress, August-September 2012, pp. 19-24

Institutional Repository

conference paper

(c) 2012 Zhang, X
Zhao, X.
Molenaar, M.
Stoter, J.
Kraak M.J.
Ai, T.