Integration of mobile laser scanning and aerial imagery data for generating digital surface models

Author:

Altyntsev M. A.,

Abstract

Aerial photography and mobile laser scanning are some of the most efficient methods of surveying, which allow creating digital surface models of the area with high accuracy and detail. Both of these methods allow gathering information about the area in the form of point clouds. However, due to the fact that the aerial survey data are obtained from the air, and the MLS ones from the ground, point clouds obtained by different methods display the same territory with different detail. For example, the roofs of buildings are well recognized from aerial data, and their walls – from MLS ones. The necessity of combined use of heterogeneous data through their integration is appeared. In this case, it is necessary to solve a number of tasks, such as registration of point clouds, assessing visibility zones depending on the survey territory, saving in the final combined point cloud only those points in the over-lapping areas that most accurately and fully describe the shapes of the terrain objects, filtering false measurements. The main tasks that arise during data integration are discussed. The technique of integrating mobile laser scanning and aerial photography data for generating a single digital surface model is proposed. This technique consists in recognizing the separated objects of the territory or their parts. The study results of the developed technique based on the data of Novosibirsk are presented.

Publisher

Siberian State University of Geosystems and Technologies

Subject

General Medicine

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3