ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume III-3
https://doi.org/10.5194/isprs-annals-III-3-169-2016
https://doi.org/10.5194/isprs-annals-III-3-169-2016
03 Jun 2016
 | 03 Jun 2016

CLASSIFICATION OF AIRBORNE LASER SCANNING DATA USING GEOMETRIC MULTI-SCALE FEATURES AND DIFFERENT NEIGHBOURHOOD TYPES

R. Blomley, B. Jutzi, and M. Weinmann

Keywords: ALS, LiDAR, Point Cloud, Features, Multi-Scale, Classification

Abstract. In this paper, we address the classification of airborne laser scanning data. We present a novel methodology relying on the use of complementary types of geometric features extracted from multiple local neighbourhoods of different scale and type. To demonstrate the performance of our methodology, we present results of a detailed evaluation on a standard benchmark dataset and we show that the consideration of multi-scale, multi-type neighbourhoods as the basis for feature extraction leads to improved classification results in comparison to single-scale neighbourhoods as well as in comparison to multi-scale neighbourhoods of the same type.