منابع مشابه
hypoDD -- A Program to Compute Double-Difference Hypocenter Locations
HypoDD is a Fortran computer program package for relocating earthquakes with the double-difference algorithm of Waldhauser and Ellsworth (2000). This document provides a brief introduction into how to run and use the programs ph2dt and hypoDD to compute double-difference (DD) hypocenter locations. It gives a short overview of the DD technique, discusses the data preprocessing using ph2dt, and l...
متن کاملAppraising Earthquake Hypocenter Location Errors: a Complete, Practical Approach for Single-event Locations by Gary
For conventional single-event, nonlinear, least-squares hypocentral estimates, I show that the total error is expressible as a linear combination of three terms: (1) measurement error; (2) modeling errors caused by inadequacy of the traveltime tables; and (3) a nonlinear term. Errors in calculating travel-time partial derivatives are shown to have no effect, provided a stable solution can be fo...
متن کاملHypocenter location by pattern recognition
[1] A novel approach to hypocenter location is proposed on the basis the concept of pattern recognition. A new data misfit criterion for location is introduced which measures discrepancies between the observed arrival times of an event and those of ‘‘nearby’’ previous events. In the arrival pattern misfit measure, travel times predicted by an Earth model are effectively replaced by information ...
متن کاملEffect of newly refined hypocenter locations on the seismic activity recorded during the 2016 Kumamoto Earthquake sequence
We present the results of relocating 17,544 hypocenters determined from data recorded during the 2016 Kumamoto Earthquake sequence, during the interval between April 14, 2016, and August 31, 2016. For this, we used a doubledifference relocation method to constrain high-resolution hypocenter locations by cross-correlation differential times as well as the NIED Hi-net catalog differential times. ...
متن کاملActivity Recognition in a Dense Sensor Network
A dense sensor network consisting of passive infrared motion detectors was developed and used to record human activity in hallways and rooms in a large campus building. Algorithms were developed that: (a) automatically determine the topology of the network from the sensor data, so that manual mapping is not required, (b) automatically learn patterns of sensor readings in local spatial and tempo...
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ژورنال
عنوان ژورنال: Journal of Physics of the Earth
سال: 1992
ISSN: 1884-2305,0022-3743
DOI: 10.4294/jpe1952.40.313