Tuesday, 28 April 2015

Downloading and Visualizing Seismic Events from USGS

The unlucky events that took place in Nepal have flooded the web with visualization of the earthquakes from USGS. They normally visualize earthquakes with a colour scale that depends on the age of the event and a marker size that depends on magnitude. I remembered that some time ago I tested ways for downloading and visualizing data from USG in the same way in R. So I decided to take those tests back, clean them up and publish them. I hope this will not offend anyone, I do not want to disrespect the tragedy, just share my work.

The USGS provides access to csv files for seismic events recording in several time frames: past hour, past day, past week, and in the past 30 days. For each of these, several choices of significance are provided, user can download all the events in the time frame or limit their request to events with magnitude higher than: 1.0, 2.5, 4.5 and significant events. The data are provided in csv files with standard names so that they are always accessible and updated every 15 minutes with new data.
USGS provides the csv files in links with standard names. For example in this case we are downloading all the data in the last month, so the csv file’s name is: all_month.csv. If we wanted to download only the earthquakes in the last day and with a magnitude above 4.5, we would have used the file name: 4.5_day.csv. The links to all the csv provided by USGS are available here: http://earthquake.usgs.gov/earthquakes/feed/v1.0/csv.php

For this experiment we need the following packages: sp, plotrix, and raster
In R we can easily import the data by simply calling the read.table function and reading the csv file from the server:
URL <- "http://earthquake.usgs.gov/earthquakes/feed/v1.0/summary/all_month.csv"
Earthquake_30Days <- read.table(URL, sep = ",", header = T)

This will download all the seismic events in the past 30 days.
Now we can transform the data, which are stored in a data.frame, into a spatial object using the following two lines:

The first line transforms the object Earthquake_30Days into a SpatialPointsDataFrame. The second gives it its proper projection, which is a geographical projection like Google Maps.
At this point I want to download the borders of all the countries in the world so that I can plot the seismic events with some geographical references:
polygons <- shapefile("TM_WORLD_BORDERS_SIMPL-0.3.shp")

These three lines can download the border shapefile from the web, unzip it into the working directory and load it.
In this example I will visualize the earthquakes using the same technique used by the USGS, with a colour that varies with the age of the event and a size that depends on magnitude. So the first thing to do is take care of the time. If we check the format of the time variable in the USGS file we see that it is a bit uncommon:
[1] 2015-04-28T12:20:43.410Z

For this reason I created a function to transform this format into something we can use:
conv.time <- function(vector){
split1 <- strsplit(paste(vector),"T")
split2 <- strsplit(split1[[1]][2],"Z")
fin <- paste0(split1[[1]][1],split2[[1]][1])

If I apply this function to the previous example I obtain the following:
[1] "2015-04-28 12:20:43"

Now I can create a new variable in the object with this time-stamp:
DT <- sapply(Earthquake_30Days$time,FUN=conv.time)
Earthquake_30Days$DateTime <- as.POSIXlt(DT)

Now we can start the tricky part. For plotting the events with a custom colour scale and a custom size scale, we first need to create them. Moreover, we also need to create the thresholds needed for the legend.
For the colour scale we can do all that using the following lines:
days.from.today <- round(c(Sys.time()-Earthquake_30Days$DateTime)/60,0)
colour.scale <- color.scale(days.from.today,color.spec="rgb",extremes=c("red","blue"),alpha=0.5)
colors.DF <- data.frame(days.from.today,color.scale(days.from.today,color.spec="rgb",extremes=c("red","blue")))
colors.DF <- colors.DF[with(colors.DF, order(colors.DF[,1])), ]
colors.DF$ID <- 1:nrow(colors.DF)
breaks <- seq(1,nrow(colors.DF),length.out=10)

In the first line I calculate the age of the event as the difference between the system time and the event time-stamp. In the second line I create the colour scale with the function in plotrix, from red to blue and with a certain transparency.
Then I need to create the thresholds for the legend. I first create a data.frame with age and colours, then I order it by age and insert an ID column. At this point I can create the thresholds by simply using the seq function.
I do the same thing with the size thresholds:
size.DF <- data.frame(Earthquake_30Days$mag,Earthquake_30Days$mag/5)
size.DF <- size.DF[with(size.DF, order(size.DF[,1])), ]
size.DF$ID <- 1:nrow(size.DF)
breaks.size <- seq(0,max(Earthquake_30Days$mag/5),length.out=5)

Then I can plot the whole thing:

tiff(filename="Earthquake_Map.tif",width=7000,height=4000, res=300)

plot(Earthquake_30Days, col= colour.scale, cex=Earthquake_30Days$mag/5, pch=16, add=T)

#Title and Legend
title("Earthquakes in the last 30 days",cex.main=3)
legend.pos <- list(x=-28.52392,y=-20.59119)
rect(xleft=legend.pos$x-5, ybottom=legend.pos$y-30, xright=legend.pos$x+30, ytop=legend.pos$y+10, col="white", border=NA)
legendg(legend.pos,legend=c(round(colors.DF[colors.DF$ID %in% round(breaks,0),1],2)),fill=paste(colors.DF[colors.DF$ID %in% round(breaks,0),2]),bty="n",bg=c("white"),y.intersp=0.75,title="Age",cex=0.8) 


I divided the magnitude by 5, so that the bubbles are not too big. The position of the legends is something that depends of the image, if you decrease the area plotted on the map their location will change and you can use geographical coordinates to change it.
The result is the following image:
Download the image here: Earthquake_Map.jpg

The full script is available here: Script