Fault Displacement of the 2011 Mw 6.6 Fukushima-ken Hamadori Earthquake Based on a 3D Crustal Deformation Model Constructed Using Differential InSAR–Lidar

Author(s):  
Yasuhira Aoyagi ◽  
Mitsukazu Kageshima ◽  
Takumi Onuma ◽  
Shinichi Homma ◽  
Sakae Mukoyama

ABSTRACT 3D coseismic deformation detected by remote sensing yields essential information for estimating the geometry and slip distribution of the causative fault. However, it is often difficult to be obtained by a single observation method due to data acquisition constraints. This study constructs a 3D coseismic deformation model of the 2011 Fukushima-ken Hamadori earthquake by integrating Differential Interferometric Synthetic Aperture Radar (DInSAR), and differential light detection and ranging (Dlidar) analyses. Both horizontal and vertical movements observed are almost consistent with those of the theoretical dislocation model of normal faulting. The fault displacements measured within ±45 m of the rupture based on the 3D deformation model is also in good agreement with the possible maximum field displacements. Fault dips and lateral displacement components are also harmonious with the field survey measurements. Dlidar detects full 3D motion, whereas the DInSAR detects deformations too small for the light detection and ranging (lidar). Combining the two products is helpful to produce a more robust 3D displacement field than possible from the lidar alone.


2009 ◽  
Vol 24 (2) ◽  
pp. 95-102 ◽  
Author(s):  
Hans-Erik Andersen

Abstract Airborne laser scanning (also known as light detection and ranging or LIDAR) data were used to estimate three fundamental forest stand condition classes (forest stand size, land cover type, and canopy closure) at 32 Forest Inventory Analysis (FIA) plots distributed over the Kenai Peninsula of Alaska. Individual tree crown segment attributes (height, area, and species type) were derived from the three-dimensional LIDAR point cloud, LIDAR-based canopy height models, and LIDAR return intensity information. The LIDAR-based crown segment and canopy cover information was then used to estimate condition classes at each 10-m grid cell on a 300 × 300-m area surrounding each FIA plot. A quantitative comparison of the LIDAR- and field-based condition classifications at the subplot centers indicates that LIDAR has potential as a useful sampling tool in an operational forest inventory program.



Wind Energy ◽  
2012 ◽  
Vol 16 (3) ◽  
pp. 353-366 ◽  
Author(s):  
Knud A. Kragh ◽  
Morten H. Hansen ◽  
Torben Mikkelsen


2021 ◽  
pp. 1-1
Author(s):  
Chul-Soon Im ◽  
Sung-Moon Kim ◽  
Kyeong-Pyo Lee ◽  
Seong-Hyeon Ju ◽  
Jung-Ho Hong ◽  
...  


2012 ◽  
Vol 51 (8) ◽  
pp. 083609-1 ◽  
Author(s):  
Hajin J. Kim ◽  
Charles B. Naumann ◽  
Michael C. Cornell


2009 ◽  
Vol 77 ◽  
pp. 1-27 ◽  
Author(s):  
Rachel Opitz

La città romana di Falerii Novi e quella pre-romana di Falerii Veteres vengono riviste in questo articolo attraverso la combinazione di dati da ricognizione lidar (light detection and ranging) e geofisica. La ricognizione lidar fornisce per la prima volta infomiazioni dettagliate sui bordi topograficamente complessi di questi siti e ha permesso di identificare un certo numero di nuove strutture. Osservando tali strutture nel contesto dei dati topografici e geofisici, sono state esplorate le aree urbane periferiche sia come zone per movimento sia come facciate. Tramite questi esempi vengono considerati i potenziali contributi forniti dal lidar alla comprensione generale dell'urbanismo pre-romano e romano.



Author(s):  
Vinicius Conti da Costa ◽  
Bruno Ziegler Haselein ◽  
Filipe Barbosa Veras ◽  
Manoel Kolling Dutra ◽  
Tiago Pinto


2021 ◽  
Vol 92 (12) ◽  
pp. 121501
Author(s):  
A. Leoni ◽  
P. Esposito ◽  
V. Stornelli ◽  
G. Saggio ◽  
G. Ferri


2019 ◽  
Vol 433 ◽  
pp. 678-689 ◽  
Author(s):  
Michael J. Joyce ◽  
John D. Erb ◽  
Barry A. Sampson ◽  
Ron A. Moen


2013 ◽  
Vol 22 (6) ◽  
pp. 988-1001 ◽  
Author(s):  
Wenguang Hou ◽  
Xuewen Wang ◽  
Caixian Zhang ◽  
Zheng Ji ◽  
Xuming Zhang


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