Three‐dimensional surface displacements and rotations from differencing pre‐ and post‐earthquake LiDAR point clouds

Nissen, Edwin; Krishnan, Aravindhan K.; Arrowsmith, J Ramón; Saripalli, Srikanth

doi:10.1029/2012gl052460

Cited by 84 publications

(98 citation statements)

References 16 publications

(28 reference statements)

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Two more earthquake events, the 2008 M w 6.9 Iwate-Miyagi earthquake and the 2011 M w 7.1 FukushimaHamadori earthquake, were monitored by lidar data acquired before and after the event. Then Nissen et al (2014) estimated the 3-D displacement using the Iterative Closest Point (ICP) algorithm (Nissen et al, 2012). Their results showed a coherent displacement but with high level of noise in the horizontal component.…”

Section: Introductionmentioning

confidence: 99%

Calculation of coseismic displacement from lidar data in the 2016 Kumamoto, Japan, earthquake

Moya

Yamazaki

et al. 2017

Nat. Hazards Earth Syst. Sci.

View full text Add to dashboard Cite

Abstract. The spatial distribution of the coseismic displacements that occurred along the Futagawa fault during the 2016 Kumamoto earthquake of M w 7.0 was estimated using airborne light detection and ranging (lidar) data. In this study, a pair of digital surface models (DSMs) obtained from the high-density lidar data before and after the mainshock on 16 April 2016 were used. A window matching search approach based on the correlation coefficient between the two DSMs was used to estimate the geodetic displacement in the near-field region. The results showed good agreements with the geodetic displacements calculated from strong-motion acceleration records and coincided with the fault line surveyed by the Geological Survey of Japan. IntroductionOn 14 April 2016, an M w 6.2 earthquake struck Kumamoto Prefecture, Japan, at 21:26 JST. The epicenter was located at the end of the Hinagu fault at a shallow depth. After approximately 28 h (at 01:25 on 16 April 2016), another earthquake of M w 7.0 struck the Futagawa fault, which is near the Hinagu fault. The first event was designated as the foreshock and the second one as the mainshock. Both the events occurred in the town of Mashiki (with a population of approximately 33 000), which is located to the east of Kumamoto City (with a population of approximately 735 000). Many aftershocks followed these events, and as of 6 September, 4 months after the foreshock, the total number of aftershocks (larger than M w 3.5) is 272. This number is the largest among the recent inland (crustal) earthquakes in Japan (Japan Meteorological Agency, 2016). This Kumamoto earthquake sequence triggered secondary effects such as landslides and liquefaction and caused extensive damage to lifeline systems, buildings, bridges, and transportation structures. A total of 8550 buildings, mostly in Kumamoto Prefecture, were seriously damaged or collapsed, and 50 human lives were lost, mostly because of landslides or the collapse of buildings (Cabinet Office of Japan, 2016).Soon after the occurrence of the foreshock, various satellites and airborne remote sensing technologies were employed to monitor crustal movements and various damages . The Japan Aerospace Exploration Agency (JAXA) carried out extensive monitoring of the source area using the PALSAR-2 sensor on board ALOS-2 satellite. Interferometric synthetic aperture radar (InSAR) analysis using a pair of imagery data obtained from PALSAR-2 before (pre-event data) and after (postevent data) the mainshock showed the line-of-sight (LOS) displacements to the satellite direction (Geospatial Information Authority of Japan, 2016). Using the pre-event data (30 November 2015, 7 March 2016 and the co-event data (7 March, 18 April 2016) from PALSAR-2, the authors of this paper calculated the spatial coherence values (International Charter, 2016), which could highlight the extensive landslides and severe damages to buildings along the Futagawa fault line.After the Kumamoto earthquake, government agencies and aerial survey companies in Japan conducted several ...

show abstract

Section: Introductionmentioning

confidence: 99%

Calculation of coseismic displacement from lidar data in the 2016 Kumamoto, Japan, earthquake

Moya

Yamazaki

et al. 2017

Nat. Hazards Earth Syst. Sci.

View full text Add to dashboard Cite

show abstract

“…Multi-source, multi-period DTM data are not only a critical tool for research on the mechanism of landslides, but also considered as greatly useful information regarding active faults, earthquake disasters [1][2][3][4], and flooding/river bank erosion [5]. When it comes to the comparison of this type of terrain information, error estimation of data obtained in various periods using various techniques becomes crucial.…”

Section: Introductionmentioning

confidence: 99%

Digital Elevation Model Differencing and Error Estimation from Multiple Sources: A Case Study from the Meiyuan Shan Landslide in Taiwan

Hsieh

Chan

2016

Remote Sensing

View full text Add to dashboard Cite

In this study, six different periods of digital terrain model (DTM) data obtained from various flight vehicles by using the techniques of aerial photogrammetry, airborne LiDAR (ALS), and unmanned aerial vehicles (UAV) were adopted to discuss the errors and applications of these techniques. Error estimation provides critical information for DTM data users. This study conducted error estimation from the perspective of general users for mountain/forest areas with poor traffic accessibility using limited information, including error reports obtained from the data generation process and comparison errors of terrain elevations. Our results suggested that the precision of the DTM data generated in this work using different aircrafts and generation techniques is suitable for landslide analysis. Especially in mountainous and densely vegetated areas, data generated by ALS can be used as a benchmark to solve the problem of insufficient control points. Based on DEM differencing of multiple periods, this study suggests that sediment delivery rate decreased each year and was affected by heavy rainfall during each period for the Meiyuan Shan landslide area. Multi-period aerial photogrammetry and ALS can be effectively applied after the landslide disaster for monitoring the terrain changes of the downstream river channel and their potential impacts.

show abstract

“…In all likelihood, the increased ability to make repeat observations, leverage preexisting data sets (see http:// www . opentopography .org/), and change detection techniques [Aryal et al, 2012;Nissen et al, 2012] will significantly affect the study of previously unobservable or transient processes such as earthquake afterslip [Aagaard et al, 2012] or catastrophic debris flow initiation [Iverson et al, 1997]. Balloon-mounted observations (assuming airspace free of obstacles) would give an overview of the area in question, and backpack-or vehicle-mounted observations would allow researchers to focus on specific features of interest.…”

Section: Mls As a Key Rapid Response Toolmentioning

confidence: 99%

Mobile Laser Scanning Applied to the Earth Sciences

et al. 2013

View full text Add to dashboard Cite

Lidar (light detection and ranging), a method by which the precise time of flight of emitted pulses of laser energy is measured and converted to distance for reflective targets, has helped scientists make topographic maps of Earth's surface at scales as fine as centimeters. These maps have allowed the discovery and analysis of myriad otherwise unstudied features, such as fault scarps, river channels, and even ancient ruins [Glennie et al., 2013b].

show abstract

Three‐dimensional surface displacements and rotations from differencing pre‐ and post‐earthquake LiDAR point clouds

Cited by 84 publications

References 16 publications

Calculation of coseismic displacement from lidar data in the 2016 Kumamoto, Japan, earthquake

Calculation of coseismic displacement from lidar data in the 2016 Kumamoto, Japan, earthquake

Digital Elevation Model Differencing and Error Estimation from Multiple Sources: A Case Study from the Meiyuan Shan Landslide in Taiwan

Mobile Laser Scanning Applied to the Earth Sciences

Contact Info

Product

Resources

About