Post on 01-Apr-2015
Geocoding African Disasters
Jesse Brinkman
Mentor: Pam Cowher
Project Overview
Data Prep Gather Data Organize Data Geocode the Data
Analysis What effect do El Nino/La Nina years have on
droughts in Africa? What role do development indicators play in the
severity of disasters?
What is Geocoding?
Geocoding is a way to give something a reference point on a map. Address Latitude/Longitude Other grid systems
Pacific Disaster Center 1305 N Holopono St # 2Kihei, HI 96753
Gather the Data Obtain the data from the Centre for Research on the Epidemiology of
Disasters’ (CRED) Emergency Events Database (EMDAT)
Organize the Data
Using the locations provided by EMDAT assign latitude and longitude information to each disaster.
Re-format the data to be easily inserted into the GIS software.
Geocode the Data
Observations/Trends 1,580 Disasters recorded from 1981-2007 Epidemics and Floods account for 71%
585 and 532 respectively
37.03%
33.67%9.56%
8.92%
3.73%
2.53%
1.39%1.27%
0.76%0.63%0.32%0.19%
Epidemic
Flood
Drought
Wind Storm
Insect Infestation
Earthquake
Slides
Wild Fire
Volcano
Extreme Temperature
Wave/Surge
Complex
Observations/Trends cont.
Increase in disasters in recent years
Total Disasters by Year
0
20
40
60
80
100
120
140
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
# of disasters
0
10
20
30
40
50
60
70
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
Flood Epidemic
Floods and Epidemics by Year
Disaster Density 1981 - 1990
Disaster Density 1991 - 2000
Total Deaths by Year 1988 - 2007
0
2,000
4,000
6,000
8,000
10,000
12,000
14,000
16,000
18,000
1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
# of Deaths
Analysis
What effects do El Nino/La Nina years have on droughts in Africa?
What role do development indicators play in the loss of life associated with disasters?
El Nino/La Nina
Hypothesis: There are more droughts during El Nino years, and less during La Nina years.
Methods: Gather the list of years that El Nino/La Nina
occurred. Look for an increase in drought occurrence.
Inse
ct I
nfes
tatio
n
Com
plex
Dis
aste
r
Wild
Fire
Ext
rem
e T
empe
ratu
re
Wav
e/S
urge
Slid
es
Vol
cano
Win
d S
torm
Ear
thqu
ake
Flo
od
Epi
dem
ic
Dro
ught
0
100,000
200,000
300,000
400,000
500,000
600,000
InsectInfestation
Wild Fire Wave/Surge Volcano Earthquake Epidemic
# of Deaths by Disaster
# of Deaths
Conclusions
No apparent correlation between # of droughts and El Nino/La Nina years
Sensitivity to Disasters
Hypothesis: Indicators such as infant mortality, literacy, and government corruption contribute to the amount of deaths per disaster.
Methods: Take the average infant mortality, literacy,
corruption perception, water stress, digital access, and human development rates.
Compare with average death/disaster
Conclusions There is no strong correlation between the two.
Sensitivity Rate vs Avg Death
R2 = 0.2153
0
50
100
150
200
250
0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00
Sensitivity Rate
Ave
rag
e K
ille
d
Future Work Possibilities
Do specific regional analysis on the El Nino/La Nina years, as opposed to Africa as a whole.
Improve the sensitivity analysis/map Better Scale Disaster by type
Individual factors which may affect particular disaster types.
Explain the increase in disasters.
Acknowledgements Pam Cowher Colin Lindeman Rich Nezelek Centre for Research on the
Epidemiology of Disasters (CRED)
Emergency Events Database (EMDAT)
The Akamai Internship Program is funded by the Center for Adaptive optics through it’s National Science Foundation Science and Technology Center grant (#AST-987683) and by grants to the Akamai Workforce Initiative from the National Science Foundation and Air Force Office of Scientific Research (both administered by NSF, #AST-0710699) and from the University of Hawaii
Lani LeBron Lisa Hunter Lynne Raschke Scott Seagroves