您好，欢迎访问北京市农林科学院 机构知识库！
北京市农林科学院机构知识库

全部

  • 全部
  • 标题
  • 学者
  • 机构
  • 关键词

An Image-Segmentation-Based Urban DTM Generation Method Using Airborne Lidar Data

文献类型： 外文期刊

作者： Chen, Ziyue 1 ; Xu, Bing 2 ; Gao, Bingbo 3 ;

作者机构： 1.Beijing Normal Univ, Coll Global Change & Earth Syst Sci, Beijing 100875, Peoples R China

2.Tsinghua Univ, Ctr Earth Syst Sci, Beijing 100084, Peoples R China

3.Beijing Acad Agr & Forestry Sci, Beijing Res Ctr Informat Technol Agr, Beijing 100097, Peoples R China

关键词： Digital terrain model (DTM);image segmentation;light detection and ranging (Lidar);urban

期刊名称：IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING （ 影响因子：3.784； 五年影响因子：3.734 ）

ISSN： 1939-1404

年卷期： 2016 年 9 卷 1 期

页码：

收录情况： SCI

摘要： DTM generation using airborne Light detection and ranging (Lidar) data is the fundamental issue of Lidar data processing and has been massively studied. However, DTM generation is still challenging in urban areas, due to the existence of densely distributed urban features and very large buildings. Different from most point-based DTM generation algorithms, this research proposes an image-segmentation-based method for urban DTM generation. First, image segmentation is conducted using the DSM image. Next, a seed ground segment is set for each cell. Following the order of the nearest segment pair, each unclassified segment is examined by comparing the spatial correlation between the candidate segment and its nearest ground segment. This process continues until no unclassified segment remains. Based on classified ground segments, all ground points can thus be extracted and the output DTM can be obtained through postinterpolation. This method was experimented in the central Cambridge. The accuracy assessment and comparison with other Lidar-processing methods proved that the segmentation-based method produces urban DTMs with a small mean bias and limited large errors. This methodology has the potential to be applied to other areas and terrain situations. In addition to an original DTM generation method, this research works as an example that mature methods from other subjects can be employed to extend the category of Lidar-processing algorithms.

  • 相关文献

[1]An Object-Based Method for Urban Land Cover Classification Using Airborne Lidar Data. Chen, Ziyue,Chen, Ziyue,Gao, Bingbo. 2014

[2]On-line Analysis for Agricultural Production Image Data. Gao, Ronghua,Wu, Huarui,Gao, Ronghua,Wu, Huarui,Gao, Ronghua,Wu, Huarui,Gao, Ronghua,Wu, Huarui. 2016

[3]Segmentation of Cotton Leaves Based on Improved Watershed Algorithm. Niu, Chong,Niu, Yuguang,Niu, Chong,Li, Han,Zheng, Wengang,Niu, Chong,Li, Han,Zheng, Wengang,Zhou, Zengchan,Bu, Yunlong. 2016

[4]Micron-scale phenotyping quantification and three-dimensional microstructure reconstruction of vascular bundles within maize stalks based on micro-CT scanning. Du, Jianjun,Zhang, Ying,Guo, Xinyu,Ma, Liming,Shao, Meng,Pan, Xiaodi,Zhao, Chunjiang.

作者其他论文 更多>>
置顶
购物车
反馈

© 京ICP备09089781号-29 主办单位：北京市农林科学院

学术资源： 中国农业科学院 农业专业知识服务系统 农科联盟资源共建共享平台 中国农业科技文献与信息服务平台 中国农业期刊集成服务平台