Strip Adjustment of Multi-Temporal LiDAR Data—A Case Study at the Pielach River

Author:

Wimmer Michael H.12ORCID,Mandlburger Gottfried1ORCID,Ressl Camillo1ORCID,Pfeifer Norbert1ORCID

Affiliation:

1. TU Wien, Department of Geodesy and Geoinformation, Wiedner Hauptstrasse 8-10, 1040 Wien, Austria

2. BEV—Federal Office of Metrology and Surveying, Schiffamtsgasse 1-3, 1020 Wien, Austria

Abstract

With LiDAR (Light Detection and Ranging) time series being used for various applications, the optimal realization of a common geodetic datum over many epochs is a highly important prerequisite with a direct impact on the accuracy and reliability of derived measures. In our work, we develop and define several approaches to the adjustment of multi-temporal LiDAR data in a given software framework. These approaches, ranging from pragmatic to more rigorous solutions, are applied to an 8-year time series with 21 individual epochs. The analysis of the respective results suggests that a sequence of bi-temporal adjustments of each individual epoch and a designated reference epoch brings the best results while being more flexible and computationally viable than the most extensive approach of using all epochs in one single multi-temporal adjustment. With a combination of sparse control patches measured in the field and one selected reference block, the negative impacts of changing surfaces on orientation quality are more effectively avoided than in any other approach. We obtain relative discrepancies in the range of 1–2 cm between epoch-wise DSMs for the complete time series and mean offsets from independent checkpoints in the range of 3–5 cm. Based on our findings, we formulate design criteria for setting up and adjusting future time series with the proposed method.

Funder

Austrian Science Fund

Publisher

MDPI AG

Reference60 articles.

1. Airborne lidar change detection: An overview of Earth sciences applications;Okyay;Earth-Sci. Rev.,2019

2. Muhadi, N.A., Abdullah, A.F., Bejo, S.K., Mahadi, M.R., and Mijic, A. (2020). The use of LiDAR-derived DEM in flood applications: A review. Remote Sens., 12.

3. LiDAR utility for natural resource managers;Hudak;Remote Sens.,2009

4. 3D urban object change detection from aerial and terrestrial point clouds: A review;Xiao;Int. J. Appl. Earth Obs. Geoinf.,2023

5. Change detection of urban objects using 3D point clouds: A review;Stilla;ISPRS J. Photogramm. Remote Sens.,2023

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