کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
556042 | 1451348 | 2006 | 10 صفحه PDF | دانلود رایگان |
This paper presents an algorithm for the segmentation of airborne laser scanning data. The segmentation is based on cluster analysis in a feature space. To improve the quality of the computed attributes, a recently proposed neighborhood system, called slope adaptive, is utilized. Key parameters of the laser data, e.g., point density, measurement accuracy, and horizontal and vertical point distribution, are used for defining the neighborhood among the measured points. Accounting for these parameters facilitates the computation of accurate and reliable attributes for the segmentation irrespective of point density and the 3D content of the data (step edges, layered surfaces, etc.) The segmentation with these attributes reveals more of the information that exists in the airborne laser scanning data.
Journal: ISPRS Journal of Photogrammetry and Remote Sensing - Volume 60, Issue 2, April 2006, Pages 71–80