Analysis of 2012 M8.6 Indian Ocean earthquake coseismic slip model based on GPS data

2016 ◽  
Author(s):  
Putra Maulida ◽  
Irwan Meilano ◽  
Endra Gunawan ◽  
Joni Efendi
Keyword(s):  
Indian Ocean ◽  
Gps Data ◽  
Slip Model ◽  
Coseismic Slip ◽  
Model Based

scholarly journals Coseismic slip and afterslip of the 2015 Mw 8.3 Illapel (Chile) earthquake determined from continuous GPS data

2016 ◽  
Vol 43 (20) ◽  
pp. 10,710-10,719 ◽  
Author(s):  
Mahesh N. Shrivastava ◽  
Gabriel González ◽  
Marcos Moreno ◽  
Mohamed Chlieh ◽  
Pablo Salazar ◽  
...  
Keyword(s):  
Gps Data ◽  
Coseismic Slip ◽  
Chile Earthquake ◽  
Continuous Gps

Impact of ionosphere on InSAR observation and coseismic slip inversion: Improved slip model for the 2010 Maule, Chile, earthquake

2021 ◽  
Vol 267 ◽  
pp. 112733
Author(s):  
Bochen Zhang ◽  
Xiaoli Ding ◽  
Falk Amelung ◽  
Chisheng Wang ◽  
Wenbin Xu ◽  
...  
Keyword(s):  
Slip Model ◽  
Coseismic Slip ◽  
Chile Earthquake

Coseismic Slip Model of the 2018 Mw 7.9 Gulf of Alaska Earthquake and Its Seismic Hazard Implications

2018 ◽  
Vol 90 (2A) ◽  
pp. 642-648 ◽  
Author(s):  
Bin Zhao ◽  
Yujie Qi ◽  
Dongzhen Wang ◽  
Jiansheng Yu ◽  
Qi Li ◽  
...  
Keyword(s):  
Seismic Hazard ◽  
Gulf Of Alaska ◽  
Slip Model ◽  
Coseismic Slip ◽  
Alaska Earthquake

A GPS Data Based Monitor Model of Unoccupied Taxis at Transportation Hubs

2014 ◽  
Vol 641-642 ◽  
pp. 767-772
Author(s):  
Xiao Lin Che ◽  
Jian Cheng Weng ◽  
Quan Yu ◽  
Tian Yu Xu
Keyword(s):  
Travel Demand ◽  
Field Investigation ◽  
Gps Data ◽  
Passenger Transport ◽  
Peak Period ◽  
International Airport ◽  
Model Based ◽  
Monitoring Model ◽  
Scientific Analysis

Taxis account for a large percent of urban public passenger transport. This research proposes a monitor model of analyzing unoccupied taxis at a defined area. By scientific analysis of taxi GPS data precision and quality, 16,255 valid taxis in register list were filtered, and two coefficients were introduced to correct the taxi monitoring model. Based on the location reports of valid taxis, the number of unoccupied taxi which was able to dispatch to meet passengers’ demands can be predicted. Take the terminal 3 of Beijing Capital International Airport as a case study, the field investigation results show that the precision of model reached 87.25%. It provides reliable systematic support and alert for a low taxi number when there comes up large taxi travel demand during the peak period or under severe weathers.

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