intraplate-seismicity

An exploration of intraplate seismicity in the northeast USA.

####Table of contents:

• Catalog Sources
• Installation and Setup
• Execution
• Updating
• Troubleshooting
• Directory Structure
• How to Add a Dataset
• How to Modify a Dataset

####Catalog Sources:

• NEIC data set (includes historic and event until 2012): data.neic <- data/NEIC_HM_2014.csv
• ANSS data set (all magnitudes from 2013-2015): data.anss <- data/ANSS_2013.csv
• IRIS stations data: stations.iris <- data/all_stn_metadata_oct15"
• ISC small magnitude data (1975-2012 with mag <2.5): data.small_mag <- data/small_mag.txt
• ANF data import: data.anf <- data/ANF_06_15.txt
• ISC arrivals data: data.arrivals <- data/isc_all_arrivals_no_restriction.txt

#####Magnitude Conversions:

Magnitude conversions where requred on data from ANSS_2013. This was the methodology used.

Where the "dashed line" is the function: f(lat) = -0.45*lon + 3

####Installation and Setup:

• Download and install R
• Download and install RStudio
• If Mac: Download and install XQuartz

•      Open Terminal (/Applications/Utilities/Terminal)
  

•      Type `git clone https://github.com/don4of4/intraplate-seismicity.git`
  

•      Enter Github User and Password
  

• If PC: Download and install Github Desktop

•      Enter Github User and Password
  

•      Clone the repository: https://github.com/don4of4/intraplate-seismicity.git
  

####Execution:

• Open RStudio
• File/Open File...
• Navigate to intraplate-seismicity/app.Rproj (just added via Github)
• Within RStudio, under Files, click import.R, highlight the entire contents of the file, and press Run
• If needed, open server.R and press Run App

####Updating:

• Open Terminal
• Navigate to intraplate-seismicity
• type 'git pull' without the quotes

####Troubleshooting

• Error: There is no package called ShinyRGL → This error is indicative that XQuartz is not installed on Mac. If you just installed it, restart your R session. You should not recieve this error on PC.
• Error: object ‘dataset’ not found → This error is indicative that you have not executed your import.R file. Stop the program execution, highlight contents of import.R, and execute the program.

####Directory Structure:

intraplate-seismicity
├──  data/
│   ├──  //Data sources here
├──  docs/
│   ├──  ExceptionReport.docx
├──  app.Rproj
├──  import.R
├──  LICENSE
├──  README.md
├──  server.R
├──  stations_completeness_validation.R
├──  stations_date_validation.R
├──  ui.R
├──  util.R

####How to use the software: First, follow the instructions listed under “Installation & Setup” and “Execution.” Following these instructions are pertinent to using the dataset’s visual interface. An overview of the application and its functions are below:

General Functions: The application allows the user to manipulate each visual representation through time. Simply utilize the “Time” slider at the top, or the “Set Time Range” feature under “Additional Functions.” This allows the user to manipulate the date-time range and thus influence each of the tabbed plots (listed below as items 1 thru 5).

Under “Additional Functions”, the user can utilize the “Min Slider Value” in order to influence the “Time” slider’s start date. The user can select a rectangular dataset with regard to latitude and longitude by using the “Set Region” function. The user can also use the “Download Data” function in order to download the selected data.

1. Stations Plot The stations plot is a two-dimensional graph of seismometers over time. Seismometers are plotted in accordance with their longitude and latitude and are placed on a map of the East coast U.S.A.

2. Earthquakes Plot The earthquakes plot is a two-dimensional graph of earthquakes over time. Each imported catalog is aggregated and presented in this graph in accordance with moment magnitude, which can be visualized through an associated color key.

3. Density Plot (dbscan) The density plot is a three-dimensional clustering of earthquakes over time. It aggregates earthquakes over latitude, longitude, and depth by use of DBSCAN, a density-based spatial clustering of applications with noise. The DBSCAN plot allows for manipulation of two variables: EPS (size of the epsiolon neighborhood), and MinPts (the minimum number of points in the EPS region). The user is welcome to manipulate the default settings in attempts to better cluster the data. More details on DBSCAN can be found here.

4. 3D Plot The 3D plot clusters earthquake data with regard to three-dimensional kernel density estimation. The plot graphically clusters each earthquake in accordance with the kernel smoothing function. More details can be found here and here.

5. Statistics The statistics graphs can be found by clicking on the "Statistics" tab, then by selecting an option below "Generate Statistics" under "Additional Functions." Each graph accurately displays an association between two factors, and some include a key with valuable information as well:

• Cumulative Events & Magnitude is a distrubtion of frequency on magnitude, with the loess curve (span 0.7 and 0.6) listed, as well as the first derivative.
• Cumulative Events & Time is a simple graph of cumulative number of events over time.
• Stations vs. Year is a distrubution of the number of stations over time.
• Num. of Events vs Depth accurately depicts the events that occured at given depths, clearly skewed right due to the significant number of recorded events without magnitude.
• Num. of Events vs Magnitude lists the recorded events for each magnitude in one half increments from 0.5 to 6.

####How to Add a Dataset: To add a catalog, follow the steps below:

• Open import.R (for directions on how to do this, see the "Execution" section of the README).
• Note the commented text, prefaced by a #. This will outline each existing dataset, their file location, and the labeling of the dataset's columns and source. To add a dataset, follow the syntax below:

# NAME data set
data.NAME <- read.table("data/SRC", header = TRUE, sep = ",")
colnames(data.NAME) <- c("C1","C2","C3","C4",...)
data.NAME$src <- 'LABEL'
data.NAME$declustered <- TRUE|FALSE

• For NAME, choose a short variable name that will easily convey the dataset you are creating.
• For SRC, you must first acquire a new CSV, TXT, or other file and place it in the data/ folder. SRC should then be replaced with the name of the file.
• For C1, C2, C3, etc., choose names for each column your SRC provides. If, for example, you are implementing station data for another region, you will most likely have "lat","lon","elev","depth", etc. Be sure each label directly corresponds to the data in the given column. For example, if latitidue is listed in the third column, replace "C3" with "lat".
• Label the source of the data (choose more detailed syntax for LABEL).
• Indicate whether the data is declustered (TRUE indicates YES, FALSE indicates NO).
• If necessary, follow the syntax below # Date formatting in order to standardize your new dataset's date-time information. Add your dataset to data.neic$datetime <- ISOdatetime(..) (utilizing the ISOdatetime conversion, or format according using a POSIX conversion. Feel free to use the existing conversions as a guide.
• If necessary, you might need to utilize the #Magnitude conversion section in order to standardize your data's magnitudes to Moment Magnitude.
• That's it! Once you test and ensure that your code runs smoothly, be sure to git commit --all and git push in order to save your work. You should do this via the command line (Terminal for Mac) or via Github Desktop.

####How to Modify a Dataset: To modify a dataset:

• Find the dataset you wish to modify in the /data/ directory.
• Add the new dataset to this folder. For example, add NEIC_HM_2016.csv into the directory.
• Go to import.R and modify the line of code data.neic <- read.table("data/NEIC_HM_2016.csv", header = TRUE, sep = ",")
  • For directions on how to navigate to import.R, see the "Execution" section of the README
  • Note that we are now pointing to NEIC_HM_2016.csv.
• Open the new CSV and verify that the column names directly associate with last year's data
  • E.g. c("emw","lon","lat","depth","y","m","d", "h", "m.1", "s", "mwsig", "nstar","comment")
• If they do not, simply manipulate the above line in order to match the new column format. For example, if "emw" is now listed last, simply re-order in order to reflect the change.
• That's it! Once you test and ensure your code runs smoothly, be sure to git commit --all and git push in order to save your work. You should do this via the command line (Terminal for Mac) or via Github Desktop.

Project by: Dean J. Kroker, Donald H. Scott IV, and Andrea Stiffelman.