ASSESSING THE LOCAL EARTHQUAKE RISK

Justin Czarka, Lehman College, CUNY – May 2013

Agung Swastika/AFP/Getty Images

Purpose of Presentation

To compare datasets for assessing earthquake risk using ArcMap

Various factors must be considered when assessing local areas at risk from earthquakes.

Accurate use of earthquake data could determine future use of risk mitigation funding allocations

Earthquake Effects

Ground rupture Shaking Liquefaction Tsunamis Landslides Fires Disease

Fire as aftermath from 1906 San Francisco Earthquake

Obtaining Essential Data

Required Data:Earthquake data:

magnitude, epicenters, and locations

Population data: who lives where?

Geographic data: administrative boundaries

United States Geological Survey (USGS): Locating Earthquake Data

United States Geological Survey (USGS): Locating Earthquake Data

Earthquake datasets from United States Geological Survey (USGS)

Utilized archived collection of earthquake data from the “Global Earthquake Search” based on a rectangular area search

Parameters: Complete Catalog from 1/1/1973 through

4/25/13 Magnitudes 2-10 Depth 1-100 km

Data Website: http://earthquake.usgs.gov/earthquakes/eqarchives/epic/

United States Census Data: Locating Geographic and Population Data

United States Census Data: Locating Geographic and Population Data

United States Census Bureau Tiger Products

2010 Census Demographic Profile 1- Shapefile Format

Provides Population Distribution at the individual county level

Data Website: http://www.census.gov/geo/maps-data/data/tiger.html

GRUMP Data: Locating Population Data

Global Rural-Urban Mapping Project (GRUMP)

Global Rural-Urban Mapping Project Located at NASA’s Socioeconomic Data and

Application Center (SEDAC) GRUMP allows one to more accurately

represent population distribution over a particular administrative unit.

Utilizes nighttime lights as indicator of population density and population distribution.

Access at: http://sedac.ciesin.columbia.edu/data/collection/grump-v1

Spatial Join: USGS and Census Data

Allows individual earthquakes to be quantified within each county

Overlays earthquake locations within each county administrative unit

Creates a simplistic earthquake risk map

Problem with General U.S. Census Data

U.S. Census Data assumes a theoretical uniform distribution of population across the geographic extent of the county.

Actual county population tends to be concentrated- in urban areas, suburbs, towns, and villages.

Based on geographic (mountains, streams, etc.) and economic reasons (location of jobs, housing, etc.)

Problem with General U.S. Census Data

Visualizing U.S. Census data fails to effectively reflect population distribution with a county. The only data available: 1) total population in the county, and 2) the county size/area. Thusone can only determine a uniform population distribution.

Population By U.S. County

“DP0010001" is the short name for the data table containing total population.

Case Study: Albany County, New York

•Albany County Population: 304,204

•20 >M2 earthquakes since 1973

Albany County, New York

U.S. Census vs GRUMP Population Case Study: Albany County, New York

Census Population Map Describes: Number of Earthquakes Magnitude of Earthquakes Uniform Population Distribution within the

county (administrative unit) Mapping of Probable Fault Line

Census Population Map Fails to Describe: Accurate distribution of population within the

county Depict earthquake risk for population centers

Case Study: Albany County, New York

GRUMP Population Density Grid, Vol. 1 Allows: Distribution of county population based on economic

activity A likely indicator where the population lives

Detailed view of population most at risk for earthquake Based on proximity to fault and historical local

earthquakes

In ArcGIS, Use GRUMP Population Data to: Form a zone of proximity surrounding the fault/epicenter

I.e. a buffer zone Develop population statistics within the buffer zone

I.e. population density

ArcGIS: Create Shapefile to Create Buffer Zone

Albany County, New York

Created a shapefile to represent “epicenter” of earthquakes.

ArcGIS: Develop Buffer Zones

5 km and 10 km buffer zones surrounding the epicenter

More damage closer to the epicenter

ArcGIS: Zonal Statistics as Table

•Able to determine the population density within a given area (buffer).

Attempting a Buffer Zone Using Census Data

•U.S. Census data depicting earthquake risk using population density.

•Data only allows for county population density, shown here in shapes of green (lighter green represents higher density).

Using GRUMP Data With Buffer Zone

•GRUMP data depicting earthquake risk using population density within buffer zones.

•Data allows for population density devised through zonal statistics, shown here as brown (5km) and tan (10km) buffer zones.

Limitations

Depth of earthquakes not considered

Magnitude of earthquakes not considered

US Census (vector) data not analyzed below county level

Conclusions

GRUMP data can be very effective at determining the population at risk from earthquakes.

GRUMP data can be flexible enough to analyze population density risk within various formal and informal administrative units

GRUMP Population Density 2000 Map Layer

(http://sedac.ciesin.columbia.edu/data/set/grump-v1-population-

density)

Citations

United States Census Bureau http://www.census.gov/geo/maps-data/data/tiger.html

United States Geological Survey http://earthquake.usgs.gov/earthquakes/eqarchives/epic/

Global Rural-Urban Mapping Project (GRUMP) http://sedac.ciesin.columbia.edu/data/collection/gpw-v3

“Potential for Global Mapping of Development Via A Nightsat Mission.”

Global http://ngdc.noaa.gov/eog/pubs/Nightsat_GeoJ_2007.pdf “Earthquakes May Endanger New York More Than Thought,

Says Study.” The Earth Institute at Columbia University. August 21, 2008.

http://www.earth.columbia.edu/articles/view/2235