Classification of LiDAR point clouds in urban areas based on the analysis of regional multi-return density

doi:10.6046/gtzyyg.2015.02.05

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Abstract

A new strategy for the classification of raw LiDAR points in urban areas, which is based on the comprehensive utilization of echo features of different object types and terrain information, is proposed in this paper according to a regional multi-return density analysis. The main procedure of the classification of the off-terrain points begins with the construction of Triangulated Irregular Network (TIN), and then the region of each object is captured by the contours clustering based on the topological relations of various contours traced from the TIN. Finally, the type of the object is recognized by the statistical analysis of the regional multi-return density through the significant difference between the building region and the vegetation region. This method not only makes good use of the difference in echo features between different objects such as buildings and trees but also confirms the existence of the multi-returns on the edges of the building. At the same time, the adaptive region determination of the objects is accomplished following the contours clustering. So the proposed method can dramatically increase the classification accuracy and overcome the weakness of the traditional methods, thus being more useful to the study and application of such aspects as building reconstruction and parameters estimation of the trees. Experiments prove that the new algorithm can get an effective classification.

Keywords net primary productivity (NPP) carnegie-ames-stanford approach(CASA) model remote sensing Beijing

:	TP181
	TP79

Issue Date: 02 March 2015

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	YIN Kai
	TIAN Yichen
	YUAN Chao
	ZHANG Feifei
	YUAN Quanzhi
	HUA Lizhong

Cite this article:

YIN Kai,TIAN Yichen,YUAN Chao, et al. Classification of LiDAR point clouds in urban areas based on the analysis of regional multi-return density[J]. REMOTE SENSING FOR LAND & RESOURCES, 2015, 27(2): 29-35.

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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2015.02.05 OR https://www.gtzyyg.com/EN/Y2015/V27/I2/29

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