Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
8.3
4.2
Journals
Remote Sensing
Special Issues
Use of LiDAR and 3D point clouds in Geohazards
remotesensing-logo
Submit to Remote Sensing Review for Remote Sensing Propose a Special Issue

Journal Menu

► Journal Menu

Journal Browser

► Journal Browser
share announcement

Use of LiDAR and 3D point clouds in Geohazards

A special issue of Remote Sensing (ISSN 2072-4292).

Deadline for manuscript submissions: closed (30 June 2015) | Viewed by 54982

Special Issue Editors

Dr. Antonio Abellan

E-Mail Website
Guest Editor
Institute of Earth Sciences, Faculté des Géosciences et de l'environnement, University of Lausanne, 1015 Lausanne, Switzerland
Interests: 3D point clouds; LiDAR; photogrammetry; ground deformation; rockfalls
Special Issues, Collections and Topics in MDPI journals
Dr. Marc-Henri Derron

E-Mail Website
Guest Editor
Institute of Earth Sciences, Faculté des Géosciences et de l'Environnement, University of Lausanne, 1015 Lausanne, Switzerland
Interests: engineering geology; geohazards; landslides; remote sensing; LiDAR; InSAR
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Michel Jaboyedoff

E-Mail Website
Guest Editor
Institute of Earth Sciences, University of Lausanne, Geopolis 3793, CH-1015 Lausanne, Switzerland
Interests: natural hazards and risks
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The acquisition of dense and accurate terrain information using three-dimensional remote sensing systems (e.g., LiDAR, photogrammetry) has opened up new possibilities for improving our understanding, modeling and prediction capabilities of different Geohazards during the last years. The use of these sensors mounted on various fixed or mobile platforms, including Unmanned Aerial Vehicles (UAV), airborne, helicopter, vessel, etc., is changing classical approaches for investigating hazardous sites. In addition to well-established LiDAR systems, some fast evolving image processing techniques—such as Structure From Motion—make it possible to get 3D point cloud data at low cost by non-specialists. These developments will certainly produce a series of exciting research findings and new applications for Natural Hazards assessment in the forthcoming years.

In spite of recent technological advances, a great challenge remains in the development of new 3D computational procedures for gaining a more accurate knowledge of geological hazards. Further investigation on the development of new algorithms for automatic feature extraction, monitoring and integration of very high quality 3D data with current physical models is still needed.

Contributions aiming to use 3D point clouds for investigating natural phenomena (including ground deformation, landslides, floods, earthquakes, volcanoes, soil erosion, etc.) that pose serious risks to human beings or infrastructures will be much appreciated in this special issue. We aim to put together innovative contributions about novel processing techniques and original applications of three-dimensional techniques in Geohazards. Some examples include, but are not limited to:

  • Novel technologies or procedures for dynamic acquisition of 3D point clouds
  • New computational methods related with the monitoring of natural phenomena
  • Semi-automatic extraction of terrain features related with the characterization of geological hazard
  • Integration of very high quality data for improving the modeling of geohazards
  • Recent case studies: innovative analysis and interpretation of Geohazards
  • Use of three-dimensional systems in laboratory scale experiments (micro scale)
  • Improvements in regional mapping derived from high quality 3D data
  • Pioneering initiatives for the creation of 3D databases, web visualization and data sharing
  • Further related topics.

Authors are required to check and follow specific Instructions to Authors, see https://dl.dropboxusercontent.com/u/165068305/Remote_Sensing-Additional_Instructions.pdf.

 

Dr. Michel Jaboyedoff
Dr. Antonio Abellan
Dr. Marc-Henri Derron
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.


Keywords

  • 3d point clouds
  • geohazards
  • lidar
  • photogrammetry
  • structure-from-motion
  • landslides
  • volcanoes
  • earthquakes
  • floodings
  • soil erosion
  • ground deformation

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue polices can be found here.

Published Papers (6 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Editorial

Jump to: Research

471 KiB  
Editorial
“Use of 3D Point Clouds in Geohazards” Special Issue: Current Challenges and Future Trends
by Antonio Abellan, Marc-Henri Derron and Michel Jaboyedoff
Remote Sens. 2016, 8(2), 130; https://doi.org/10.3390/rs8020130 - 6 Feb 2016
Cited by 70 | Viewed by 9625
Abstract
The fast proliferation of new satellite, aerial and terrestrial remote sensing techniques has undoubtedly provided new technological and scientific opportunities to society during the last few decades. [...] Full article
(This article belongs to the Special Issue Use of LiDAR and 3D point clouds in Geohazards)
►▼ Show Figures

Graphical abstract

Research

Jump to: Editorial

1266 KiB  
Article
Quantifying Effusion Rates at Active Volcanoes through Integrated Time-Lapse Laser Scanning and Photography
by Neil Slatcher, Mike R. James, Sonia Calvari, Gaetana Ganci and John Browning
Remote Sens. 2015, 7(11), 14967-14987; https://doi.org/10.3390/rs71114967 - 10 Nov 2015
Cited by 30 | Viewed by 8368
Abstract
During volcanic eruptions, measurements of the rate at which magma is erupted underpin hazard assessments. For eruptions dominated by the effusion of lava, estimates are often made using satellite data; here, in a case study at Mount Etna (Sicily), we make the first [...] Read more.
During volcanic eruptions, measurements of the rate at which magma is erupted underpin hazard assessments. For eruptions dominated by the effusion of lava, estimates are often made using satellite data; here, in a case study at Mount Etna (Sicily), we make the first measurements based on terrestrial laser scanning (TLS), and we also include explosive products. During the study period (17–21 July 2012), regular Strombolian explosions were occurring within the Bocca Nuova crater, producing a ~50 m-high scoria cone and a small lava flow field. TLS surveys over multi-day intervals determined a mean cone growth rate (effusive and explosive products) of ~0.24 m3·s−1. Differences between 0.3-m resolution DEMs acquired at 10-minute intervals captured the evolution of a breakout lava flow lobe advancing at 0.01–0.03 m3·s−1. Partial occlusion within the crater prevented similar measurement of the main flow, but integrating TLS data with time-lapse imagery enabled lava viscosity (7.4 × 105 Pa·s) to be derived from surface velocities and, hence, a flux of 0.11 m3·s−1 to be calculated. Total dense rock equivalent magma discharge estimates are ~0.1–0.2 m3·s−1 over the measurement period and suggest that simultaneous estimates from satellite data are somewhat overestimated. Our results support the use of integrated TLS and time-lapse photography for ground-truthing space-based measurements and highlight the value of interactive image analysis when automated approaches, such as particle image velocimetry (PIV), fail. Full article
(This article belongs to the Special Issue Use of LiDAR and 3D point clouds in Geohazards)
►▼ Show Figures

Graphical abstract

1654 KiB  
Article
Lateral Offset Quality Rating along Low Slip Rate Faults: Application to the Alhama de Murcia Fault (SE Iberian Peninsula)
by Marta Ferrater, Ramon Arrowsmith and Eulàlia Masana
Remote Sens. 2015, 7(11), 14827-14852; https://doi.org/10.3390/rs71114827 - 6 Nov 2015
Cited by 9 | Viewed by 6580
Abstract
Seismic hazard assessment of strike-slip faults is based partly on the identification and mapping of landforms laterally offset due to fault activity. The characterization of these features affected by slow-moving faults is challenging relative to studies emphasizing rapidly slipping faults. We propose a [...] Read more.
Seismic hazard assessment of strike-slip faults is based partly on the identification and mapping of landforms laterally offset due to fault activity. The characterization of these features affected by slow-moving faults is challenging relative to studies emphasizing rapidly slipping faults. We propose a methodology for scoring fault offsets based on subjective and objective qualities. We apply this methodology to the Alhama de Murcia fault (SE Iberian Peninsula) where we identify 138 offset features that we mapped on a high-resolution (0.5 × 0.5 m pixel size) Digital Elevation Model (DEM). The amount of offset, the uncertainty of the measurement, the subjective and objective qualities, and the parameters that affect objective quality are independent variables, suggesting that our methodological scoring approach is good. Based on the offset measurements and qualifications we calculate the Cumulative Offset Probability Density (COPD) for the entire fault and for each fault segment. The COPD for the segments differ from each other. Tentative interpretation of the COPDs implies that the slip rate varies from one segment to the other (we assume that channels with the same amount of offset were incised synchronously). We compare the COPD with climate proxy curves (aligning using the very limited age control) to test if entrenchment events are coincident with climatic changes. Channel incision along one of the traces in Lorca-Totana segment may be related to transitions from glacial to interglacial periods. Full article
(This article belongs to the Special Issue Use of LiDAR and 3D point clouds in Geohazards)
►▼ Show Figures

Graphical abstract

8189 KiB  
Article
A 4D Filtering and Calibration Technique for Small-Scale Point Cloud Change Detection with a Terrestrial Laser Scanner
by Ryan A. Kromer, Antonio Abellán, D. Jean Hutchinson, Matt Lato, Tom Edwards and Michel Jaboyedoff
Remote Sens. 2015, 7(10), 13029-13052; https://doi.org/10.3390/rs71013029 - 1 Oct 2015
Cited by 74 | Viewed by 10785
Abstract
This study presents a point cloud de-noising and calibration approach that takes advantage of point redundancy in both space and time (4D). The purpose is to detect displacements using terrestrial laser scanner data at the sub-mm scale or smaller, similar to radar systems, [...] Read more.
This study presents a point cloud de-noising and calibration approach that takes advantage of point redundancy in both space and time (4D). The purpose is to detect displacements using terrestrial laser scanner data at the sub-mm scale or smaller, similar to radar systems, for the study of very small natural changes, i.e., pre-failure deformation in rock slopes, small-scale failures or talus flux. The algorithm calculates distances using a multi-scale normal distance approach and uses a set of calibration point clouds to remove systematic errors. The median is used to filter distance values for a neighbourhood in space and time to reduce random type errors. The use of space and time neighbours does need to be optimized to the signal being studied, in order to avoid smoothing in either spatial or temporal domains. This is demonstrated in the application of the algorithm to synthetic and experimental case examples. Optimum combinations of space and time neighbours in practical applications can lead to an improvement of an order or two of magnitude in the level of detection for change, which will greatly improve our ability to detect small changes in many disciplines, such as rock slope pre-failure deformation, deformation in civil infrastructure and small-scale geomorphological change. Full article
(This article belongs to the Special Issue Use of LiDAR and 3D point clouds in Geohazards)
►▼ Show Figures

Graphical abstract

2555 KiB  
Article
To Fill or Not to Fill: Sensitivity Analysis of the Influence of Resolution and Hole Filling on Point Cloud Surface Modeling and Individual Rockfall Event Detection
by Michael J. Olsen, Joseph Wartman, Martha McAlister, Hamid Mahmoudabadi, Matt S. O’Banion, Lisa Dunham and Keith Cunningham
Remote Sens. 2015, 7(9), 12103-12134; https://doi.org/10.3390/rs70912103 - 18 Sep 2015
Cited by 32 | Viewed by 7654
Abstract
Monitoring unstable slopes with terrestrial laser scanning (TLS) has been proven effective. However, end users still struggle immensely with the efficient processing, analysis, and interpretation of the massive and complex TLS datasets. Two recent advances described in this paper now improve the ability [...] Read more.
Monitoring unstable slopes with terrestrial laser scanning (TLS) has been proven effective. However, end users still struggle immensely with the efficient processing, analysis, and interpretation of the massive and complex TLS datasets. Two recent advances described in this paper now improve the ability to work with TLS data acquired on steep slopes. The first is the improved processing of TLS data to model complex topography and fill holes. This processing step results in a continuous topographic surface model that seamlessly characterizes the rock and soil surface. The second is an advance in the automated interpretation of the surface model in such a way that a magnitude and frequency relationship of rockfall events can be quantified, which can be used to assess maintenance strategies and forecast costs. The approach is applied to unstable highway slopes in the state of Alaska, U.S.A. to evaluate its effectiveness. Further, the influence of the selected model resolution and degree of hole filling on the derived slope metrics were analyzed. In general, model resolution plays a pivotal role in the ability to detect smaller rockfall events when developing magnitude-frequency relationships. The total volume estimates are also influenced by model resolution, but were comparatively less sensitive. In contrast, hole filling had a noticeable effect on magnitude-frequency relationships but to a lesser extent than modeling resolution. However, hole filling yielded a modest increase in overall volumetric quantity estimates. Optimal analysis results occur when appropriately balancing high modeling resolution with an appropriate level of hole filling. Full article
(This article belongs to the Special Issue Use of LiDAR and 3D point clouds in Geohazards)
►▼ Show Figures

Graphical abstract

2117 KiB  
Article
Does HDR Pre-Processing Improve the Accuracy of 3D Models Obtained by Means of two Conventional SfM-MVS Software Packages? The Case of the Corral del Veleta Rock Glacier
by Álvaro Gómez-Gutiérrez, José Juan De Sanjosé-Blasco, Javier Lozano-Parra, Fernando Berenguer-Sempere and Javier De Matías-Bejarano
Remote Sens. 2015, 7(8), 10269-10294; https://doi.org/10.3390/rs70810269 - 11 Aug 2015
Cited by 37 | Viewed by 10524
Abstract
The accuracy of different workflows using Structure-from-Motion and Multi-View-Stereo techniques (SfM-MVS) is tested. Twelve point clouds of the Corral del Veleta rock glacier, in Spain, were produced with two different software packages (123D Catch and Agisoft Photoscan), using Low Dynamic Range images and [...] Read more.
The accuracy of different workflows using Structure-from-Motion and Multi-View-Stereo techniques (SfM-MVS) is tested. Twelve point clouds of the Corral del Veleta rock glacier, in Spain, were produced with two different software packages (123D Catch and Agisoft Photoscan), using Low Dynamic Range images and High Dynamic Range compositions (HDR) for three different years (2011, 2012 and 2014). The accuracy of the resulting point clouds was assessed using benchmark models acquired every year with a Terrestrial Laser Scanner. Three parameters were used to estimate the accuracy of each point cloud: the RMSE, the Cloud-to-Cloud distance (C2C) and the Multiscale-Model-to-Model comparison (M3C2). The M3C2 mean error ranged from 0.084 m (standard deviation of 0.403 m) to 1.451 m (standard deviation of 1.625 m). Agisoft Photoscan overcome 123D Catch, producing more accurate and denser point clouds in 11 out 12 cases, being this work, the first available comparison between both software packages in the literature. No significant improvement was observed using HDR pre-processing. To our knowledge, this is the first time that the geometrical accuracy of 3D models obtained using LDR and HDR compositions are compared. These findings may be of interest for researchers who wish to estimate geomorphic changes using SfM-MVS approaches. Full article
(This article belongs to the Special Issue Use of LiDAR and 3D point clouds in Geohazards)
►▼ Show Figures

Graphical abstract

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-6
Back to TopTop