• Sergejs Kodors Rezekne academy of Technologies (LV)



feature selection, LiDAR, remote sensing, urban classification


The proposed research is related with building detection in airborne laser scanning data. The result of geospatial surface segmentation provides a vector layer of unclassified shapes. Geometric features of shapes can be applied to classify urban objects and to detect buildings among them. The goal of this research is to select the appropriate geometric features considering their importance for building recognition. The feature selection is completed using random forest algorithm. The obtained list of features and their influence weights can be used to improve building recognition methods and to filter noise objects.
Supporting Agencies
Author expresses his gratitude to the State Land Service of Latvia and to Latvian Geospatial Information Agency for providing samples for the research purposes.


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How to Cite

S. Kodors, “GEOMETRIC FEATURE SELECTION OF BUILDING SHAPE FOR URBAN CLASSIFICATION”, ETR, vol. 2, pp. 78–83, Jun. 2017, doi: 10.17770/etr2017vol2.2613.