Paper Title:
Knowledge-Based Classification Method for Urban Area Objects Feature Extraction Based on LIDAR Points
  Abstract

Laser scanning technology can quickly capture a large area of high-precise 3D spatial data, and get the information of buildings, roads, vegetation and other urban objects from raw data. Based on this information general frame of these objects can be modelling. In this paper, an object-based classification method is proposed for urban objects based on LIDAR points: determine the contents of the objects contained in the scene; extract inherent features of different objects; establish objects feature knowledge database; combine and compare objects’ features and distribution of LIDAR points; derive a set of rule to express the point cloud classification which can be received by computer through fuzzy judgement. The method has been applied to LIDAR points by LYNX. The experiment results show that the proposed classification method is promising and usable.

  Info
Periodical
Chapter
Chapter 5: Model and Optimization and Simulation
Edited by
Zhixiang Hou
Pages
1157-1162
DOI
10.4028/www.scientific.net/AMM.128-129.1157
Citation
H. G. Xu, T. Li, F. Wu, "Knowledge-Based Classification Method for Urban Area Objects Feature Extraction Based on LIDAR Points", Applied Mechanics and Materials, Vols. 128-129, pp. 1157-1162, 2012
Online since
October 2011
Export
Price
$35.00
Share

In order to see related information, you need to Login.

In order to see related information, you need to Login.

Authors: Wen Tao Zou, Huai Qing Zhang, Hong Bo Ju, Hua Liu
Chapter 2: Microwaves Optics and Image
Abstract:Based on the brightness, greenness, humidity indices after Tasseled Cap transformation, NDWI and DEM. Extracting the alpine wetland...
579
Authors: Xiao Liang Shi, Ying Li, Rong Xin Deng
Chapter 2: Microwaves Optics and Image
Abstract:It has become an important means of shelterbelts surveying using high resolution remote sensing image to access the distribution of farmland...
500
Authors: Xiao Dong Zhou, Chun Cheng Yang, Ni Na Meng
Chapter 2: Microwaves Optics and Image
Abstract:In order to overcome the phenomenon of foreign bodies in the same spectrum in remote sensing images, as needs of land-use surveys,...
562
Authors: Hong Mei Li, Lin Gen Yang, Li Hua Zou
Chapter 6: Algorithm Design
Abstract:To make feature subset which can gain the higher classification accuracy rate, the method based on genetic algorithms and the feature...
1497
Authors: Ling Ling Zhang, Ge Ying Lai, Xiang Gui Zeng, Fa Zhao Yi
Chapter 18: Geographic Information and Remote Sensing Science
Abstract:According to the problem that the classification result of shrub and forest land was easy to confuse when used spectrum of Advanced Land...
3606