Results 31 to 40 of about 1,018,711 (376)
Traveltimes for global earthquake location and phase identification
, 1991 SUMMARY Over the last three years, a major international effort has been made by the Sub-Commission on Earthquake Algorithms of the International Association of Seismology and the Physics of the Earth's Interior (IASPEI) to generate new global ...
B. Kennett, E. Engdahl
semanticscholar +1 more source
CRED: A Deep Residual Network of Convolutional and Recurrent Units for Earthquake Signal Detection [PDF]
Scientific Reports, 2018 Earthquake signal detection is at the core of observational seismology. A good detection algorithm should be sensitive to small and weak events with a variety of waveform shapes, robust to background noise and non-earthquake signals, and efficient for ...
Mostafa Mousavi +3 more
semanticscholar +1 more source
Retrospective Evaluation of the Five-Year and Ten-Year CSEP-Italy Earthquake Forecasts [PDF]
, 2010 On 1 August 2009, the global Collaboratory for the Study of Earthquake Predictability (CSEP) launched a prospective and comparative earthquake predictability experiment in Italy.
CSEP-Italy Working Group +4 more
core +4 more sources
Earth, Planets and Space, 2020 On January 19, 2020, an M w 6.0 earthquake occurred in Jiashi, Xinjiang Uygur Autonomous Region of China. The epicenter was located at the basin-mountain boundary between the southern Tian Shan and the Tarim Basin.
Pengfei Yu +7 more
doaj +1 more source
MOWLAS: NIED observation network for earthquake, tsunami and volcano
Earth, Planets and Space, 2020 National Research Institute for Earth Science and Disaster Resilience (NIED) integrated the land observation networks established since the 1995 Kobe earthquake with the seafloor observation networks established since the 2011 Tohoku earthquake and ...
S. Aoi +9 more
semanticscholar +1 more source
THE DETERMINATION METHOD OF EXTREME EARTHQUAKE DISASTER AREA BASED ON THE DUST DETECTION RESULT FROM GF-4 DATA [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2018 The remote sensing has played an important role in many earthquake emergencies by rapidly providing the building damage, road damage, landslide and other disaster information. The earthquake in the mountains often caused to the loosening of the mountains
A. Dou, L. Ding, M. Chen, X. Wang
doaj +1 more source
Rapid prediction of earthquake ground shaking intensity using raw waveform data and a Convolutional Neural Network [PDF]
1st Croatian Conference on Earthquake Engineering, 2020 This study describes a deep convolutional neural network (CNN) based technique to predict intensity measurements (IMs) of earthquake ground shaking. The input data to the CNN model consists of multistation, 3C acceleration waveforms recorded during the
Dario Jozinović +3 more
semanticscholar +1 more source