GeoNet has a wide range of data that are collected for monitoring and researching geohazards in New Zealand. We have built several tutorials to help access this data through data services.
GeoNet's Key Data Services:
The following section links to tutorials describing access to FDSN or FITS data and in some examples correlate these data with DELTA information. These tutorials are written in Python or R programming languages. In order to improve the interaction between the code and users, the tutorials are Jupyter Notebooks, which integrates code and its output into a single document that combines visualisations, narrative text, mathematical equations, and other media.
Please note these examples use Python 3, so the syntax may differ slightly to Python 2.7. We recommend you use Python 3 as it has some important bug fixes.
These notebooks demonstrate simple ways to use the GeoNet FDSN webservices in Python and R to access seismic data.
|Clients tutorial- Python||Demonstrates different ways to manage multiple clients, including the GeoNet archive and near real-time clients.|
|General tutorial - Python||Demostrates how to get waveforms for a specific event using the event ID and utilising information returned from querying event and station services.|
|FDSN Dataselect service tutorial with Python||Examples of using the FDSN dataselect service to request waveform data in Python programming language.|
|FDSN Event service tutorial with Python||Examples of using the FDSN event service to get event information and parse QuakeML in Python programming language.|
|FDSN Station service tutorial with Python||Examples of using the FDSN station service to get station information and parse StationXML in Python programming language.|
|FDSN Station service tutorial in R||Find stations active in a set time frame in a set area.|
|FDSN Dataselect service tutorial with R||Example of using the FDSN dataselect service to request waveform data in R programming language.|
|FDSN Event service tutorial with R||Find all the seismic events that happend in an specific time range using FDSN event service.|
|Overview tutorial in R||Work flow from retrieving the data of the Seismic Event we wish to look at to getting waveform data and metadata on this Seismic Event.|
This tutorial demostrates how to access Coastal Sea Level data (colloquially known as tsunami gauge data) through FDSN.
|Tide gauges tutorial with Python||Examples of how to access the data recorded by GeoNet network of coastal sea level sensors in Python programming language.|
These tutorials demostrate how to retrieve and perform basic task with GNSS Data, mostly using the FITS API and DELTA repository. The tutorials are presented in Jupyter notebooks written in Python and R Programming languages.
|Introduction to GNSS Time Series- Python||Access and retrieve GNSS time series from GeoNet Network in Python programming language.|
|Introduction to GNSS Time Series- R||Access and retrieve GNSS time series from GeoNet Network in Python programming language.|
|Access multiple GNSS sites - R||Produce a map of GNSS stations in an set area, then get the data from the stations in this area.|
|Triming and equipment changes||Identify equipment changes or events in GNSS time series for an specific station.|
These notebooks demonstrate how to retrieve some volcano focused data and metadata from FITS and FDSN in Python and R.
|Volcano Chemistry data using FITS||Retrieve Volcano chemistry data from a set area using Python language.|
|GeoNet's Acoustic Data||Get seismic-acoustic waveform data to study volcanic events.|
|Volcano Chemistry data using FITS||Retrieve Volcano chemistry data from a set area using R language.|