Since the past decades, geodetic techniques are widely used to gain important information for the monitoring and modeling of the deformation of the Earth at different length and time scales. Although the GNSS (mainly GPS in this proposal) derived estimates of the Earth crust velocity are becoming more and more reliable, advanced data analysis techniques are needed to recognize geophysical features in the GNSS time series, e.g., non-linear behaviors, discontinuities in the signal and in its derivative, i.e., in the velocity. Unfortunately these phenomena are often hidden in the time-series noise, therefore external information, such as seismic events, are not always known. Furthermore, geodesy is, like other areas of science, entering in the era of “Big Data” with the increasing amount of data permanently recorded by satellites and terrestrial- based arrays such as GPS networks. Processing frequently vast amount of data makes it virtually impossible to inspect every time series visually. Motivated by the above mentioned reasons, this proposal main focuses on the automatic detection of signal discontinuities or offsets in Taiwan continuous GPS time series through the use of some advanced analysis techniques such as Hector. We will statistically analyze and document the results that can be an important database for some Taiwan organizations and institutes who have installed and maintained these GPS networks.
|Effective start/end date||1/08/21 → 31/10/22|
UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This project contributes towards the following SDG(s):
- GPS time series
- color noise
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