Article

VR-based visual analytics of LIDAR data for cliff erosion assessment

Authors:

Falko KuesterAuthors Info & Claims

VRST '07: Proceedings of the 2007 ACM symposium on Virtual reality software and technology

Pages 249 - 250

https://doi.org/10.1145/1315184.1315244

Published: 05 November 2007 Publication History

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Abstract

The ability to explore, conceptualize and correlate spatial and temporal changes of topographical records, is needed for the development of new analytical models that capture the mechanisms contributing towards sea cliff erosion. This paper presents a VR-centric approach for cliff erosion assessment from light detection and ranging (LIDAR) data, including visualization techniques for the delineation, segmentation, and classification of features, change detection and annotation. Research findings are described in the context of a sea cliff failure observed in Solana Beach in San Diego county.

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Kraus MFuchs JSommer BKlein KEngelke UKeim DSchreiber F(2021)Immersive Analytics with Abstract 3D Visualizations: A SurveyComputer Graphics Forum10.1111/cgf.1443041:1(201-229)Online publication date: 9-Dec-2021
https://doi.org/10.1111/cgf.14430
Chang Y(2012)High-performance visual analytics of terrestrial light detection and ranging data on large display wallJournal of Applied Remote Sensing10.1117/1.JRS.6.0615026:1(061502)Online publication date: 3-Apr-2012
https://doi.org/10.1117/1.JRS.6.061502
Lin MChen MHsieh TChang Y(2012)Parallel and Distributed Processing of Remote Sensing Data on Large DisplaysProceedings of the 2012 IEEE 18th International Conference on Parallel and Distributed Systems10.1109/ICPADS.2012.143(873-878)Online publication date: 17-Dec-2012
https://dl.acm.org/doi/10.1109/ICPADS.2012.143
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Information & Contributors

Information

Published In

VRST '07: Proceedings of the 2007 ACM symposium on Virtual reality software and technology

November 2007

259 pages

ISBN:9781595938633

DOI:10.1145/1315184

Conference Chairs:
Aditi Majumder
UC Irvine
,
Larry Hodges
UNC - Charlotte
,
Daniel Cohen-Or
Tel Aviv University
,
Editor:
Stephen N. Spencer
University of Washington

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 05 November 2007

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VRST07

Sponsor:

VRST07: The ACM Symposium on Virtual Reality Software and Technology

November 5 - 7, 2007

California, Newport Beach

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Overall Acceptance Rate 66 of 254 submissions, 26%

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Cited By

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Kraus MFuchs JSommer BKlein KEngelke UKeim DSchreiber F(2021)Immersive Analytics with Abstract 3D Visualizations: A SurveyComputer Graphics Forum10.1111/cgf.1443041:1(201-229)Online publication date: 9-Dec-2021
https://doi.org/10.1111/cgf.14430
Chang Y(2012)High-performance visual analytics of terrestrial light detection and ranging data on large display wallJournal of Applied Remote Sensing10.1117/1.JRS.6.0615026:1(061502)Online publication date: 3-Apr-2012
https://doi.org/10.1117/1.JRS.6.061502
Lin MChen MHsieh TChang Y(2012)Parallel and Distributed Processing of Remote Sensing Data on Large DisplaysProceedings of the 2012 IEEE 18th International Conference on Parallel and Distributed Systems10.1109/ICPADS.2012.143(873-878)Online publication date: 17-Dec-2012
https://dl.acm.org/doi/10.1109/ICPADS.2012.143
Olsen MJohnstone EAshford SDriscoll NYoung AHsieh TKuester F(2012)Rapid Response to Seacliff Erosion in San Diego County, California Using Terrestrial LIDARSolutions to Coastal Disasters 200810.1061/40968(312)52(573-583)Online publication date: 26-Apr-2012
https://doi.org/10.1061/40968(312)52

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