Insights into Global Earthquake Activity: Analysis of Global Earthquakes in 2023
L. Singh
2024-02-07
Introduction
Earthquakes are natural phenomena that have significant impacts on human societies, infrastructure, and the environment. Understanding the frequency, magnitude distribution, and spatial distribution of earthquakes is crucial for assessing seismic hazards, mitigating risks, and enhancing disaster preparedness and response efforts. This analysis aims to delve into global earthquake data from 2023 put forth by USGS to provide valuable insights into seismic activity worldwide.
Analyzing earthquake data is essential for various aspects of risk assessment, disaster preparedness, scientific understanding, infrastructure resilience, and international collaboration. Earthquakes pose significant risks to communities, infrastructure, and economies worldwide. By analyzing earthquake data, high-risk areas can be identified, vulnerability of regions can be assessed, and mitigation measures can be prioritized to reduce the impact of future seismic events. This knowledge is crucial for disaster preparedness planning, allowing authorities to develop effective response strategies, allocate resources, and educate the public on earthquake safety measures. Furthermore, studying earthquake patterns contributes to our scientific understanding of tectonic processes and geological phenomena, enabling researchers to investigate seismic activity trends, monitor fault movements, and refine earthquake prediction models. In terms of infrastructure resilience, analyzing earthquake data can inform engineers and urban planners about seismic risks, guiding the development of resilient infrastructure and building codes to withstand earthquakes. Thus, earthquake analysis implies many stakeholders and societies on a global level. By conducting detailed analyses of earthquake data, we can enhance our understanding of seismic activity, improve disaster preparedness and response strategies, and ultimately mitigate the impacts of earthquakes on societies and the environment.
Dataset
Data description:
The dataset used for this analysis contains information about earthquakes recorded in 2023 with a magnitude of 4.5 or higher. It includes attributes such as the date and time of occurrence, location coordinates (latitude and longitude), depth, magnitude, magnitude type, and source. (USGS Global Earthquake Catalog)
Findings
Global Earthquake Frequency by Month
The line plot depicts the frequency of earthquakes per month shows variations in seismic activity throughout the year. Peaks and troughs in earthquake occurrence are observed, with certain months experiencing higher activity compared to others. December appears to be a month of increased seismic activity. Later, we will return to investigate the types of earthquakes occuring in the month of December specifically.
#-------------------------Line plot-----------------------------
#---Looking at the structure of time data in the dataset---
##head(df$time)
##str(df$time)
#---Creating a data frame summarizing number of earthquakes per month---
months_df <- df %>%
mutate(month = month(ymd_hms(time))) %>%
group_by(month) %>%
summarise(n = length(time))
#---Creating the x-axis labels (of month) for the plot---
x_axis_labels = min(months_df$month):max(months_df$month)
#---Creating a dataframe to identify the month with the most and least number of recorded earthquakes---
hi_low <- months_df %>%
filter(n == min(n)| n== max(n)) %>%
data.frame()
#---Ensuring the structure of the primary data frame (months_df) is suitable for graphing (i.e. that variables are numberic or integers and not characters)---
##str(months_df)
#---Creating the line plot---
ggplot(months_df, aes(x= month, y=n)) +
geom_line(colour='lightblue', size=0.5) +
geom_point(shape=21, size=2, colour='darkblue', fill='white') +
labs(x="Month", y="Earthquake Count", title = "Global Earthquake Frequency by Month for the Year of 2023", caption="Data specifications: 1/1/23- 12/31/23, minimum of 4.5 magnitude,
Source: United States Geological Survey: https://earthquake.usgs.gov/earthquakes/search/") +
scale_y_continuous(labels=comma) +
theme_light() +
theme(plot.title = element_text(hjust=0.5)) +
scale_x_continuous(labels=x_axis_labels, breaks = x_axis_labels, minor_breaks = NULL) +
geom_point(data=hi_low, aes(x=month, y=n), shape = 21, size=2, fill='red', colour='red') +
geom_label_repel(aes(label = scales::comma(n)), box.padding = 1, point.padding = 1, size = 4, colour = 'grey35', segment.color = 'grey50')
The line graph depicted notes a peak in earthquake activity in December of 2023 where a collective 1,108 earthquakes were recorded globally. Although there does not appear to be literature rationalizing this surge, it is imperative we take note of it. This peak in earthquakes may be indicative of upcoming trends with greater annual earthquake frequency resulting from a multitude of factors. Although “earthquake weather” (or that certain types of weather often precede earthquakes) is ultimately a myth, climate change does appear to have an impact on earthquakes. The complexity of understanding the interactions between climate and seismic activity, still need continued research to unravel these connections. However, preliminary research explores the impact of long-term climate phenomena, such as droughts, on fault stress. NASA, for instance, shows that alternating periods of drought and heavy precipitation can cause significant stress changes in regions like the Sierra Nevada, potentially affecting faults in or near these areas. Additionally, there appears to be an underlying phenomenon of induced seismicity caused by human activities like reservoir filling and wastewater injection (Can Climate Affect Earthquakes, Or Are the Connections Shaky?). Thus, although the peak of December 2023 remains largely unexplained (likely also due to the recency of the data), it does emphasize the need to investigate underlying reasons for the changes in frequency in earthquakes globally as recently as last year.
Map of Major Earthquakes Globally in 2023 (classified by a magnitude 7.0 or higher)
This map visualization highlights the locations of major earthquakes (classified by a magnitude 7.0 or higher) recorded in 2023 globally. Investigating major earthquakes proves necessary and significant as this level indicates significant damage to region (see below).
The map provides a spatial perspective of seismic events, indicating regions that experienced significant seismic activity during the year. By examining which areas see greater frequencies of major earthquakes, we can perhaps enact more protective measures to minimize earthquake damage to these regions.
#-------------------------Map-----------------------------
# Filter for earthquakes with magnitude 7.0 or higher (7.0-7.9 = major earthquake, 8.0+ = great earthquake)
df_filtered_major <- df %>%
filter(mag >= 7.0)
#df_filtered_major
# Check the structure to ensure the filtering worked as expected
#str(df_filtered_major$latitude)
#str(df_filtered_major$longitude)
# Create map of major and great earthquakes
m <- leaflet() %>%
addProviderTiles(providers$Esri.WorldImagery)%>%
addMarkers(lng = df_filtered_major$longitude, lat = df_filtered_major$latitude,
popup = paste(df_filtered_major$mag, df_filtered_major$magType),
label = paste(df_filtered_major$place))
mThe majority of large earthquakes based on the map appears concentrated in and around the Pacific Ocean. In fact, literature reveals nearly 80% of large earthquakes occur in region around the edges of the Pacific Ocean known as the Ring of Fire. The Ring of Fire, according to the British Geological Survey os “where the Pacific plate is being subducted beneath the surrounding plate…[and] is the most seismically and volcanically active zone in the world” (Where do earthquakes occur? ). Thus, the map appears to align with existing literature about major seismic activity in the world.
Other areas with recorded major earthquakes also appear to fall along tectonic plate mappings.
In fact, all regions with major earthquakes recorded (near Alaska, the Middle East, and Australia and Indonesia) directly coincide with plate lines and line significant geographical belts (the Pacific belt, the Afroasian belt, and the Eurasian belt). These areas directly align with the lines delineating tectonic plates and correspond to significant geographical belts such as the Pacific belt, the Afroasian belt, and the Eurasian belt. This spatial correlation reinforces the understanding that seismic activity is closely linked to the movement and interaction of Earth’s tectonic plates.
It is important to note in addition to plate boundaries, seismic activity can also occur within plates, often still near fault lines or zones of weakness. For instance, intraplate earthquakes in regions such as Australia and Indonesia are attributed to stress accumulation and release within the plates, leading to localized seismic events. These events though account for less than 10 percent of all earthquakes and seldom exceed magnitude 8 in size. In fact, intraplate earthquakes are typically 100 times smaller than the largest inter-plate earthquakes (Earthquakes: Intra & Inter-plate Events). 2023 appears to be no exception to this general rule of thumb, as we do not see significant intraplate activity (i.e. registering as a major earthquake, 7.0 or greater in magnitude). It is important, however, to examine, holistically, the frequency of earthquakes (inter and intraplate) which is what the next visualization aims to do.
Inter and Intraplate Earthquake Frequency on a Global Scale
The following heatmap displays the spatial density of earthquakes (inter and intraplate), with darker shades indicating areas of higher seismic activity. It helps identify hotspots of earthquake occurrence and provides a visual representation of global seismic patterns.
#-------------------------Heat map-----------------------------
# Create heatmap
breaks <- c(0, 50, 100, 150, 200, 250, 300, 350, 400, 450, 500, 550)
ggplot(df, aes(x = longitude, y = latitude)) +
geom_bin2d(bins = 50) + # Create bins based on latitude and longitude to count the frequency of earthquakes within each bin
scale_fill_gradient(low = "lightblue", high = "red", breaks = breaks) + # Adjust color gradient
guides(fill = guide_legend(reverse=TRUE,override.aes = list(color = "black"))) + # Outline legend in black
labs(title = "Global Earthquake Frequency Heatmap",
x = "Longitude",
y = "Latitude",
fill = "Frequency") +
theme_minimal() +
theme(plot.title = element_text(hjust = 0.5))
The heatmap reveals nuanced patterns of seismic activity beyond just major plate boundaries, shedding light on both interplate and intraplate earthquake occurrences. While regions along plate boundaries exhibit elevated seismic activity, as expected, the heatmap also highlights areas with significant intraplate earthquake activity. These intraplate earthquakes, occurring within the interior of tectonic plates, often stem from localized stresses and fault systems unrelated to major plate boundaries.
The presence of intraplate seismicity, particularly in regions like Australia and Indonesia, underscores the complex nature of earthquake dynamics. In these areas, the accumulation and release of stress within the lithosphere give rise to earthquakes, despite the absence of prominent plate boundaries. Such intraplate seismicity can result from factors like ancient fault lines, crustal deformation, or even human activities such as mining or reservoir-induced seismicity (Improved Understanding of Intraplate Earthquakes in the Southeastern USA with Matched Filter Detection). More recent literature suggests “the increasing rate and magnitude of intraplate seismicity, due to industrial activities in the vicinity of continental fault zones, have become a major concern in recent years” (Reactivation of an Intraplate Fault by Mine-Blasting Events). This hypothesis paired with the data implores the need for more research investigating the potential correlation between regions found to have high frequency of intraplate earthquakes and the rates of mining and industrial activites.
Understanding both interplate and intraplate seismic activity is crucial for comprehensive earthquake risk assessment and disaster preparedness. While interplate earthquakes along plate boundaries tend to garner more attention due to their potential for large-scale devastation, intraplate earthquakes can also pose significant risks, especially in regions with dense populations and inadequate seismic infrastructure. Regions impacted by both major and higher frequences of comparatively smaller earthquakes - such as areas in the Ring of Fire - demand the our attention in order to ensure these regions are equipped to the implications of all types and frequencies of earthquakes.
Frequency of Earthquakes by Type
Along with frequency and global distribution, the magnitude type carries important information about earthquakes. The trellis chart below presents the frequency of earthquakes by magnitude type and month in a series of facetted bar charts. This allows for a detailed exploration of earthquake patterns, facilitating comparisons between different magnitude types and their temporal distribution.
#---------Trellis Bar Chart---------
# There is one magnitude type - "ml(texnet)" - which although I believe is the same type as "ml", I decided to omit the row that use this magtype description
texnetrowdrop <- which(df$magType == "ml(texnet)")
df_filteredmagtype <- df[-texnetrowdrop,]
#---Creating a data frame with earthquakes categorized by month and magnitude type---
months_df <- df_filteredmagtype %>%
select(time, magType) %>%
mutate(months = months(ymd_hms(time), abbreviate = TRUE)) %>%
group_by(months, magType) %>%
summarise(n = length(time), .groups = 'keep') %>%
data.frame()
mymonths <- c('Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec')
month_order <- factor(months_df$months, level=mymonths)
# Define custom labels for magnitude types
custom_labels <- c(
"mb (Body-wave magnitude)",
"Mi (Modified Mercalli Intensity)",
"ml (Local magnitude)",
"mw (Moment magnitude)",
"mwb (Body-wave magnitude)",
"mwc (Crustal-wave magnitude)",
"mwp (P-wave magnitude)",
"mwr (Regional magnitude)",
"mww (Moment magnitude)")
# Create the plot with custom labels for the legend
ggplot(months_df, aes(x=month_order, y=n, fill = magType)) +
geom_bar(stat="identity", position="dodge") +
theme_light() +
theme(plot.title = element_text(hjust = 0.5, size = 20),
legend.title = element_text(size = 15), # Increase the size of the legend title
axis.title.x = element_text(size = 15), # Increase the size of the x-axis title
axis.title.y = element_text(size = 15),
legend.text = element_text(size = 12),
strip.text = element_text(size = 15, face = "bold"),
axis.text.x = element_text(angle = 90, hjust = 1, size = 9)) +
labs(title = "Multiple Bar Charts - Frequency of Global Earthquakes 2023 by Type and Month",
x = "Months of the Year",
y = "Frequency",
fill= "Magnitude Type") +
scale_fill_manual(values = brewer.pal(n = 9, name = "Set3"),
labels = custom_labels) +
facet_wrap(~magType, scales = "free_y", ncol = 5, nrow = 2) +
scale_y_continuous(labels = scales::number_format(accuracy = 0.01))
Upon analysis, it is initially evident that certain magnitude types
exhibit higher frequencies compared to others, with notable variations
in temporal distribution.
Among the magnitude types, “mww” (Moment magnitude), “mb” (Body-wave magnitude), and “mwr” (Regional magnitude) earthquakes consistently appear to be the most frequent across multiple months. These magnitude types demonstrate a broad temporal distribution, indicating a relatively steady occurrence throughout the year.
“Mmw” classifications, though, clearly are the most commonly reported earthquake for which there may be several reasons. “Mww” earthquakes are characterized by their ability to capture the full spectrum of seismic energy released during an earthquake. This magnitude type is considered to be more accurate and reliable for measuring the size of larger earthquakes, especially those that occur along tectonic plate boundaries or within deep subduction zones. “Mww” earthquakes often result from significant tectonic activity, such as the movement of tectonic plates along fault lines. These earthquakes are commonly associated with subduction zones, where one tectonic plate is forced beneath another, or with the rupture of large faults in regions of high seismicity. “Mww” earthquakes can also encompass a wide range of magnitudes, from moderate to very large. Thus, the frequency count may be capturing a higher amount of comparably smaller magnitude earthquakes which still count within the “mmw” range. “Mww” earthquakes also tend to occur worldwide and are not limited to specific geographic regions. While they may be more prevalent in seismically active areas such as the Ring of Fire, they can also occur in intraplate regions and other tectonic settings. Lastly, there may be reporting bias involved with “mmw” earthquake capture where advances in seismic monitoring technology and the establishment of global seismic networks have continually improved the detection and recording of “mww” earthquakes. This enhanced monitoring capability may allow seismologists to capture a larger number of classifiable events, including those with lower magnitudes or occurring in remote regions.
In contrast, magnitude types such as “Mi” (Modified Mercalli Intensity), “mwc” (Crustal-wave magnitude), and “mwp” (P-wave magnitude) exhibit more sporadic occurrences based on the graph - with each appearing in only one month throughout the analyzed period. This intermittent temporal distribution may initially suggest to viewers that seismic events associated with these magnitude types may be influenced by specific environmental or geological conditions prevalent during those particular months. However, further investigation reveals that in fact these magnitude types are often derived from different measurement methodologies compared to more commonly used magnitudes like “Mw” (Moment Magnitude) or “mb” (Body-wave magnitude). For instance, “Mi” is based on the intensity of ground shaking observed at specific locations, while “mwc” and “mwp” are specific to certain types of seismic waves (The Modified Mercalli Intensity Scale) (see figure below). Thus, these alternative measurements may not be as widely utilized or applicable in all seismic monitoring contexts, resulting in fewer recorded earthquakes of these types (Measuring Earthquakes: Scales).
Overall, the trellis chart highlights the complex interplay between magnitude types and their temporal distribution, underscoring the multifaceted nature of seismic activity. This nuanced understanding of earthquake patterns is essential for robust analysis investigating unique characteristics of each magnitude type and temporal dynamics.
Magnitude Types Observed December 2023
Lastly, we return to the month of December which saw the greatest number of earthquakes globally. The donut chart provides specific insights into the distribution of earthquake magnitudes by type for the month of December. It reveals the relative proportions of different magnitude types, allowing for an understanding of the composition of earthquakes during that period.
#-------------------------Donut chart-----------------------------
# There is one magnitude type - "ml(texnet)" - which although I believe is the same type as "ml", I decided to omit the row that use this magtype description
texnetrowdrop <- which(df$magType == "ml(texnet)")
#texnetrowdrop
df_filteredmagtype <- df[-texnetrowdrop,]
#dim(df_filteredmagtype)
#unique(df_filteredmagtype$magType)
#---Creating a data frame with earthquakes in December categorized by magnitude type---
decmagnitude_df <- df_filteredmagtype %>%
select(magType, time) %>%
filter(month(ymd_hms(time)) == 12) %>%
mutate(month = month(ymd_hms(time)),
month_label = month.abb[month]) %>%
group_by(month_label, magType) %>%
summarise(n = n(), .groups = 'keep') %>%
data.frame()
#decmagnitude_df
#---Donut chart for above data frame---
plot_ly(decmagnitude_df, labels = ~magType, values = ~n) %>%
add_pie(hole=0.4) %>%
layout(title="Types of Magnitude of Global Earthquakes in December 2023") %>%
layout(annotations = list(text = paste0("Total December \n Earthquake Count: \n", scales::comma(sum(decmagnitude_df$n))),
"showarrow"=F))Among the 1,108 earthquakes recorded during this period, the chart illustrates the relative proportions of each magnitude type, shedding light on the composition of seismic activity during that time frame. The overwhelming majority of earthquakes in December, comprising 85% of the total, were classified as “mb” (Body-wave magnitude). This magnitude type typically measures the amplitude of seismic waves recorded on seismographs, providing crucial information about the energy release and magnitude of the earthquake. The high frequency of “mb” earthquakes suggests that a significant portion of seismic activity during December was associated with events characterized by body waves, or seismic waves that travel through the Earth’s interior.
In contrast, “mww” (Moment magnitude) earthquakes accounted for 12.5% of the total earthquakes in December. Moment magnitude is a modern scale used to quantify the size of an earthquake, taking into account the total energy released during the seismic event (Moment magnitude, Richter scale). “mww” earthquakes are often associated with larger, more significant seismic events, indicating that a notable portion of the recorded earthquakes in December were relatively powerful in terms of their energy release and, thus too, their potential impact.
Lastly, “mwr” (Regional magnitude) earthquakes constituted a smaller fraction, comprising only 1.9% of the total earthquakes in December. Regional magnitude typically refers to earthquakes that are localized to specific regions or areas, often associated with tectonic activity along fault lines or geological structures (Magnitude Types). The relatively low frequency of “mwr” earthquakes suggests that while localized seismic events occurred during December, they were less prevalent compared to other magnitude types. Ultimately, this chart depicts the dominance of certain magnitude scales and offers clues about the nature and characteristics of seismic activity during the month of December and beyond.
Conclusion
In conclusion, the analysis of earthquake data from 2023 provided valuable insights into seismic activity worldwide, shedding light on various aspects of earthquake occurrence, distribution, and characteristics. Through the exploration of earthquake frequency, magnitude distribution, and spatial patterns, several key findings emerged, each contributing to a deeper understanding of seismic hazards and their implications for human societies and infrastructure.
The line plot revealed temporal variations in earthquake occurrence throughout the year, with December standing out as a month of heightened seismic activity. While the exact reasons for this surge remain to be fully elucidated, potential factors such as long-term climate phenomena and human-induced seismicity warrant further investigation. Climate change, in particular, may play a role in influencing seismic activity, highlighting the interconnectedness of Earth’s systems and the need for interdisciplinary research to comprehend these complex dynamics.
The map visualization pinpointed regions experiencing major earthquakes, with a concentration observed along tectonic plate boundaries, particularly the Pacific Ring of Fire. This spatial correlation underscores the fundamental relationship between seismic activity and tectonic processes, emphasizing the importance of plate tectonics in shaping global seismic patterns.
The heatmap provided a nuanced depiction of earthquake spatial density, revealing both interplate and intraplate seismic activity. The presence of intraplate earthquakes highlights the multifaceted nature of earthquake dynamics and underscores the need for comprehensive risk assessment and preparedness strategies.
Moreover, the trellis chart showcased the temporal distribution of earthquakes by magnitude type, offering insights into the prevalence of different seismic measurement methodologies and their respective contributions to earthquake monitoring and analysis. This detailed exploration underscored the complex interplay between magnitude types and temporal dynamics, enriching our understanding of earthquake patterns and characteristics.
Lastly, the donut chart offered specific insights into the distribution of earthquake magnitudes by type for the month of December, depicting the composition of seismic activity during the month with the highest frequency of earthquaekes. The dominance of certain magnitude scales, such as “mb” and “mww,” highlighted the prevalence of seismic events characterized by body waves and significant energy release, respectively.
Ultimately, though, the analysis of earthquake data from 2023 provides a comprehensive overview of seismic activity worldwide, highlighting the multifaceted nature of earthquakes and their implications for disaster risk reduction and resilience efforts. By leveraging insights from earthquake analysis, stakeholders can better assess seismic hazards, mitigate risks, and enhance preparedness and response strategies, ultimately safeguarding communities and infrastructure against the impacts of earthquakes. Continued research and collaboration across disciplines are essential for advancing our understanding of seismic activity and improving our ability to mitigate the risks posed by earthquakes in an ever-changing world.