assessing geophysical risk and social vulnerability to natural disasters
DESCRIPTION
As a student at SUNY-ESF in Syracuse I completed this final project for my Advanced GIS course. This presentation describes the project which assesses the geophysical and social vulnerability to natural disasters for the counties of New Jersey. My interest in this topic was sparked by the unusual weather patterns seen here during "superstorm" Sandy in October 2012. Researching this topic and completing an assessment in GIS allowed me to better understand the geophysical factors that can make a physical landscape more prone to disasters and the social factors that can create a vulnerable society. My goal is to do more work on this topic to create safer and more prepared communities.TRANSCRIPT
By: Maureen BishopEFB 519: Geographic Modeling Final Project
Creating a Social Vulnerability Index, Geophysical Risk, Evacuation Assistance Need for Flood Risk, and a Flood Scenario: New Jersey, USA
Study Site:
• Compare created risk maps to an actual natural disaster that
occurred: HURRICANE SANDY• Comparing FEMA impact map and
created risk maps shows if variables are indicators of at-risk areas
• NJ can benefit from emergency management plans for future
events
Study Site and Objective:New Jersey, USA:1) Social Vulnerability2) Geophysical Risk3) Evacuation Assistance Need4) Compare to FEMA Impact
Map from Hurricane Sandy5) Create a scenario for flooding
based on geophysical risk
Why New Jersey?
INTRODUCTION:
What is a natural disaster?“...geophysical events, such as earthquakes, landsliding, volcanic activity and flooding” (Alcantara-Ayala, 2002)
What is vulnerability?
“…a function of the degree of social and self-protection available to potential victims” (Alcantara-Ayala, 2002)
(Alcantara-Ayala, 2002)
(Montz, 2001)
Why Assess Flood Risk?
What makes an area susceptible to flooding?
• Heavy, intense rainfall • Run-off when ground is saturated• Frozen soil • High river, stream or reservoir levels caused
by heavy rain• Ice jams in rivers • Urbanization
(How and Whys of Floods, pbs.org)
• Floods are most common natural disaster in the U.S.
(Floodsmart.gov)
www.nj.com
www.ibtimes.com
Why is this Study Important?• Basis for understanding social, demographic, and
physical aspects of the study site of New Jersey.
• Important to consider all these inputs when making management plans such as for emergency preparation.
• Urban planners must be aware of what sites are most susceptible during natural disasters in order to save lives
and minimize damage.
• Studies can contribute to reducing overall damage and instilling a secure plan for populations in at-risk areas.
Methods Overview:• Step 1: Use GIS to create Social Vulnerability, Geophysical
Risk, and Evacuation Assistance Need Maps
• Step 2: Quantify Areas at Risk using Tabulate Area
• Step 3: Use Fortran 90 to develop a scenario for flooding based on geophysical risk map
METHODS:Main Tools Used in GIS Analysis
Vector Analysis:• Add Field• Field Calculator• Feature to Raster
Raster Analysis:• Reclass• Slope• Raster calculator: Addition and
Overlay • Tabulate Area
Control Map:
Most greatly impacted areas are along COAST
Using FEMA Data
Social Vulnerability Assessment Index Variables:
Characteristic Variable (All variables are by county)
Source
Population and Housing 1) Total Population (2000)
Mastering ArcGIS. Maribeth Price, 5th ed.
2) Number of Occupied Housing Units (2000)
Mastering ArcGIS. Maribeth Price, 5th ed.
Access to Resources 3) Population below poverty level (2000)
USDA Economic Research Service 2000 Census Poverty Rate by County
Population with Special Evacuation Needs
4) Percent of population (2000) 5 years of age and under
Mastering ArcGIS. Maribeth Price, 5th ed.
5) Percent of population (2000)over 65 years of age
Mastering ArcGIS. Maribeth Price, 5th ed.
Social Vulnerability for Evacuation Assistance:Index Variables
METHODS:1) Create all input
variables2) Create standardized
version of all variables (0-1 Value)
3) Sum standardized variables and divide by total number of variables (5) (0-1 Value)
(Chakraborty, 2005)
2000 Census Poverty Rate by New Jersey Counties:
USDA Economic Research Service
Add New Field: Poverty
Poverty Field Added to Counties Layer
Edit Mode: Enter Poverty Rates by
CountyPoverty Rates by NJ
County Field
Access to Resources: Population Below
Poverty Level
NJ Counties Layer with 2000 Census Data
Field Calculator for Stan_SVI_Pov to Create
Standarized Variable Among Counties
Use Equation SVEAIx= (Rx/Rmax)à
SVEAIpoverty= Poverty/15.6
Stan_SVI_Pov Field Created With Values from 0-1.0= LEAST poverty vulnerability.1= MOST poverty vulnerability
Result: Essex County is most vulnerable in terms of poverty rates.
Sort Poverty Rates Ascending to
Identify Max value
Add New field Stan_SVI_Pov: For standarized poverty
index for NJ Counties
Essex Cty= 15.6% poverty
Stan_SVI_Pov Field Created in NJ Counties
Layer
CREATING SOCIAL VULNERABILITY FOR EVACUATION ASSISTANCE INDEX:
Social Vulnerability for Evacuation Assistance:Flow Map
POVERTY VARIABLE
Add New Field: %Pop_U5
U5_Tot_Pop Field Added to Counties
Layer
NJ Counties Layer with 2000 Census Data
U5_Tot_Pop by NJ County Field
Population with Special Evacuation Needs:Population age 5 years and under Variable
Field Calculator to Create Standarized
Variable Among Counties
Use Equation SVEAIx= (Rx/Rmax)à
SVEAIu5_tot_pop= U5_Tot_Pop/7.46479
Stan_SVI_U5 Field Created With Values from 0-1.0= LEAST under 5 pop. vulnerability.1= MOST under 5 pop. vulnerability
Result: Somerset County is most vulnerable in terms of % of Pop. Under 5 years of age.
Sort U5_Tot_Pop Descending to
Identify Max value
Field Calculator to Create %Pop under 5:
Calculation: Age_Under5/Pop2000
Population with Special Evacuation Needs:Population age 65 years and over Variable
Add New Field: %Pop_Ov65
Ov65_Tot_Pop Field Added to Counties
Layer
Field Calculator to Create Standarized
Variable Among Counties
Use Equation SVEAIx= (Rx/Rmax)à SVEAIov65_tot_pop= Ov65_Tot_Pop/22.168
Stan_SVI_Ov65 Field Created With Values from 0-1.0= LEAST over 65 pop. vulnerability.1= MOST over 65 pop. vulnerability
Result: Ocean County is most vulnerable in terms of % of Pop. Over 65 years of age.
Sort Ov65_Tot_Pop Descending to Identify
Max value
Field Calculator to Create %Pop over 65:
Calculation: Age_Over65/Pop2000
Ov65_Tot_Pop Field by NJ County Field
Add New Field:Stan_SVI_U5: For
standarized %U5_Pop
Add New Field:Stan_SVI_Ov65: For
Standardized %Ov65_Pop
Somerset Cty= 7.46479% of Pop. Is below poverty level
CREATING SOCIAL VULNERABILITY FOR EVACUATION ASSISTANCE INDEX:
Stan_SVI_U5 Field Created in NJ Counties
Layer
CREATING SOCIAL VULNERABILITY FOR EVACUATION ASSISTANCE INDEX:
NJ Counties Layer with 2000 Census Data
Ocean County = 22.168% of Pop. Is over 65 years
Stan_SVI_Ov65 Field Created in NJ
Counties Layer
% Pop. Under 5 VARIABLE
% Pop. Over 65 VARIABLE
Population and Structure:Population Density Variable
Field Calculator to Create Standarized
Variable Among Counties
Use Equation SVEAIx= (Rx/Rmax)à
SVEAIPop2000= Pop2000/884118
NJ Counties Layer with 2000 Census Data
Stan_SVI_Tot_Pop Field Created With Values from 0-1.0= LEAST total population vulnerability.1= MOST total population vulnerability
Result: Bergen County is most vulnerable in terms of population density.
Sort Pop2000 Field Descending to
Identify Max value
Add New Field:Stan_SVI_Tot_Pop:
For standarized Tot_Pop
Bergen County = 884118 people
Stan_SVI_Tot_Pop Field Created in NJ
Counties Layer
CREATING SOCIAL VULNERABILITY FOR EVACUATION ASSISTANCE INDEX:
Add New Field: OCC_Housing
OCC_Housing Field Added to Counties
Layer
NJ Counties Layer with 2000 Census Data
OCC_Housing by NJ County Field
Field Calculator to Create Standarized
Variable Among Counties
Use Equation SVEAIx= (Rx/Rmax)à
SVEAIHousing= OCC_Housing/330817
Stan_SVI_Housing Created With Values from 0-1.0= LEAST housing units vulnerability.1= MOST housing units vulnerability
Result: Bergen County is most vulnerable in terms of number of housing units.
Sort OCC_Housing Descending to
Identify Max value
Field Calculator to Create OCC_Housing:
Calculation: Owner_OCC + Renter_OCC
Add New Field:Stan_SVI_U5: For
standarized OCC_Housing
Bergen Cty= 330817 housing units
Stan_SVI_Housing Field Created in NJ Counties
Layer
CREATING SOCIAL VULNERABILITY FOR EVACUATION ASSISTANCE INDEX:
POP. DENSITY VARIABLE
OCCUPIED HOUSING VARIABLE
CREATING FINAL SOCIAL VULNERABILITY FOR EVACUATION ASSISTANCE INDEX:
NJ Counties Layer with 2000 Census Data
Add New Field:SVEAI_Final: For
Final Social Vulnerability Calculation
SVEAI_Final Field Added in NJ Counties
Layer
Field Calculator to Create Final Social Vuln.
Index
SVEAI= Sum(SVEAIx)/# of variablesà
Calculation:
(Stan_SVI_Pov + Stan_SVI_U5 +
Stan_SVI_Ov65 + Stan_SVI_Tot_Pop +
Stan_SVI_Housing)/5
SVEAI_Final Field Created in NJ Counties
Layer
Sort SVEAI_Final Descending to
Identify Max Social
Vulnerability
Top 3 Socially Vulnerable Counties:1) Essex County= .842) Bergen County= .783) Hudson County= .75
Stan_SVI_Pov Field
Stan_SVI_U5 Field
Stan_SVI_Ov65 Field
Stan_SVI_Tot_Pop
Stan_SVI_Housing Symbology: Display NJ
Counties by SVEAI Field with
Green (Low Vuln.) to Red (High Vuln.) Color Ramp
Social Vulnerability for Evacuation Assistance Index
Map:0= LEAST overall social
vulnerability1= GREATEST overall social
vulnerability
Creating Overall Social Vulnerability by Summing 5 Variables
RESULT: Social Vulnerability Index:
CONTROL MAP:FEMA IMPACT
RESULT: Most Socially Vulnerable1) Essex County : .842) Bergen County : .783) Hudson County : .745
RESULT:Top three at-risk areas: All in Northeast New Jersey1) Essex County (.84) Had a value of 1 for having greatest poverty rate2) Bergen County (.78) Had a value of 1 for having greatest number of occupied
housing units3) Hudson County (.75) Had a value of ~1 (.99) for having great poverty rate
Social Vulnerability Attribute Table:
Geophysical Risk Index Variables1) ELEVATION (meters):• High Risk (3) = -25.26 – 278.87 • Moderate Risk (2) = 278.87 – 717.40• Low Risk (1) = 717.40 – 1785.41
NJ Elevation
High : 1785.41
Low : -25.2622
RECLASS: 3 classes
NJ Elevation Reclass
High Elevation (LOW Risk)
Mid-Elevation (Moderate Risk)
Low Elevation (HIGH Risk)
2) SLOPE (Degrees):• High Risk (3) = 0 – 2.58• Moderate Risk (2) = 2.58 – 8.24• Low Risk (1) = 8.24 – 41.36
NJ Slope
0 - 0.810990876
0.810990876 - 2.270774452
2.270774453 - 4.054954379
4.05495438 - 6.325728832
6.325728833 - 8.920899634
8.920899635 - 12.00266496
12.00266497 - 15.89542117
15.89542118 - 21.5723573
21.57235731 - 41.36053467
RECLASS: 3 classes
NJ Slope Reclass
High Slope (LOW Risk)
Medium Slope (MODERATE Risk)
Low Slope (HIGH Risk)
NJ Land Cover
Highly Developed: >75% Impervious
Mod. Developed: 50-75% Impervious
Lightly Developed: 25-50% Impervious
Lightly Developed-Unwooded: 25-50%
Cultivated/Grassland
Upland Forest
Bare Land
Unconsolidated Shore
Estaurine Wetland
Palustrine Wetland
Water
RECLASS: 3 classes
NJ Land Cover Reclass
Water/Wetlands/Forest/Bare Land (LOW Risk)
Developed Areas (MODERATE Risk)
Shoreline (HIGH Risk)
3) Land Cover:• High Risk (3) = Unconsolidated Shoreline• Moderate Risk (2) = Developed Area: Highly, Moderately,
and Lightly Developed• Low Risk (1) = Forest, Water, Wetland Areas
+ + =
Potential Values for Geophysical Risk: 3 (Very Low Risk)-9 (Very High Risk) Minimum value would be: 1 + 1 + 1 = 3Maximum value would be: 3 + 3 + 3 = 9
Geophysical Risk IndexElevation RECLASSED Slope RECLASSED Land Cover RECLASSED Geophysical Risk
CREATING GEOPHYSICAL RISK INDEX: Based on Elevation, Slope and Landcover
NJ 100 DEM: NJ Dept of
Environmental Protection
ELEVATION VARIABLEArcToolbox> Spatial Analyst
Tools> Reclass> RECLASSIFY DEM: Lower Elevations Should
have a Higher Risk-Used Natural Breaks, 3 classes-Invert Reclass Values b/c LOW values should have HIGH risk
DEM Reclass Layer:3: -25.262161 – 278.87443 meters2: 278.87443 – 717.396957 meters
1: 717.396957 – 1785.411499 meters
SLOPE VARIABLE
NJ 100 DEM: NJ Dept of Environmental
Protection
ArcToolbox> Spatial Analyst Tools> Surface>
SLOPENJ Slope Layer
ArcToolbox> Spatial Analyst Tools> Reclass> RECLASSIFY
SLOPE: Lower Slope Should have a Higher Risk
-Used Natural Breaks, 3 classes-Invert Reclass Values b/c LOW values should have HIGH risk
SLOPE Reclass Layer:3: 0 – 2.585033 degrees
2: 2.585033 – 8.239794 degrees1: 8.239794 – 41.360535 degrees
LAND COVER VARIABLE
2001 Level 1 Landsat 7 ETM+ Satellite Image Land Cover Classification of New Jersey
ArcToolbox> Spatial Analyst Tools> Reclass> RECLASSIFY LAND COVER: Shoreline and Developed Areas have higher
risk
Land Cover Reclass Layer:3 (High Risk) : 200 Grid Code (Unconsolidated Shoreline)
2 (Moderate Risk) : 111, 112, 113, 114 Grid Code (Developed Land)1 (Low Risk) : 120,140,160 Grid Code (Water and Wetlands- Low
Risk b/c people will not reside there)
GEOPHYSICAL RISK CREATION
DEM Reclass Layer:DEM_Risk
SLOPE Reclass Layer:Slope_Risk
Land Cover Reclass Layer:Land_Risk
ArcToolbox>Spatial Analyst Tools>Map Algebra> RASTER
CALCULATOR:DEM_Risk + Slope_Risk +
Land_Risk
GEOPHYSICAL RISK INDEX:Given an output of values from 3-9.
Value 3 (Very Low Risk) : Value of 1 existed for each variable (1+1+1= 3)
Value of 9(Very High Risk): Value of 3 existed for each variable (3+3+3=9)3= Very High Risk
4= Low Risk5 = Moderately Low Risk
6= Moderate Risk7= Moderately High Risk
8= High Risk 9= Very High Risk
Geophysical Risk Index Map
Geophysical Risk: Flow Map
RESULT:-Elevation plays key role in deciding spatial distribution of at-risk areas-High elevations in Northern Jersey have a low risk-Low elevations along the coast and in Southern Jersey have a higher risk
RESULT: Geophysical Risk Index
CONTROL MAP:FEMA IMPACT
Evacuation Assistance Need: Social *Geophysical Variables
NJ SVEAI:
0.37 - 0.39
0.40 - 0.49
0.50 - 0.57
0.58 - 0.75
0.76 - 0.84
X
NJ Geophysical Risk:
Very Low
Low
Moderately Low
Moderate
Moderately High
High
Very High
NJ EvacuationAssistance Need:
Very Low
Low
Moderate
High
Very High
CREATING OVERLAYED RISK MAP: SOCIAL VULNERABILITY * GEOPHYSICAL RISK
TO ASSESS AREAS WITH GREATEST POTENTIAL EVACUATION ASSISTANCE NEED
SVEAI_Final Layer Created in Social Vuln.
Flow Map
Converting SVEAI_Final Layer to be used in Raster
Calculator: ArcToolbox>Conversion
Tools> To Raster> FEATURE TO RASTER
SVEAI_Final Raster Created
Geophysical Risk Raster
ArcToolbox> Spatial Analyst Tools> Math Algebra> Raster
Calculator:Calculation=
SVEAI_Rast * Geo_Risk(Had to make sure both
rasters were in same projection for this calculation
to work)
Overlay_Risk Created
ArcToolbox> Spatial Analyst Tools> Reclass>RECLASSIFY
-Used Natural Breaks, 5 classes
Overlay_Risk Reclassed:1= 1.12 – 2.39à Very Low Risk
2= 2.39 – 3.45à Low Risk3= 3.45 – 4.36à Moderate Risk
4= 4.36 – 5.33à High Risk5= 5.33 – 7.58à Very High Risk
· Potential Values for Overlay_Risk = 0-9à · SVEAI Index were decimals from 0-1· Geophysical Risk were integers from 3-9· When multiplied the minimum value that can be attained is 0 (0
SVEAI * 3 Geo_Risk) and the maximum value that can be attained is 9 (1 SVEAI * 9 Geo_Risk).
Overlay_Risk Map Showing Product of Social Vulnerability and Geophysical Risk
Symbology:Display Overlay_Risk with Green (Very Low
Risk) to Red (Very High Risk) Color Map
Evacuation Assistance Need: Flow Map
RESULT:County with LOWEST Need:Sussex County 96.5% Very Low• High elevation, less people, and
forested areaCounty with GREATEST Need:Bergen County 77.4% Very High• High poverty rate, low elevation
and slope, and dense population
RESULT: Evacuation Assistance Need:
CONTROL MAP:FEMA IMPACT
Population Densityand Evacuation
Assistance Need
OceanBurlington
Sussex
Morris
Atlantic
Salem
Cumberland
Monmouth
Hunterdon
Warren
Bergen
Somerset
Gloucester
Mercer
Middlesex
Passaic
Camden
Cape May
Essex
UnionHudson
Evacuation AssistanceNeed: New Jersey
NJ Cities
Very Low
Low
Moderate
High
Very High
Overlay Cities with Evacuation Assistance NeedRESULT: High risk areas have many cities
Quantifying Output: Flow MapQuantifying at Risk Areas By
County: Based on Overall Risk (Overlayed Social and Geophysical
Factors)
Tabulate Area:Input Raster=
Overlay_ReclassZone Field= Count of pixelsInput Feature= SVEAI_FinalClass Field= County Name
Area_Risk Table Showing Area for Each Risk Level For
Each County
Add New Field: Risk_Class-Edit Mode
RowID 1= Very LowRowID 2= Low
RowID 3= ModerateRowID 4= High
RowID 5= Very High
Risk_Class Field Within Area_Risk Table to Keep track of which rows correspond to which
risk level
Reclassed Overlayed Risk Map:
-1.12- 2.39 = 1-2.39- 3.45 = 2-3.45- 4.36 = 3-4.36- 5.33 = 4-5.33- 7.58 = 5
*Has an output table
Add New Field: Passaic_Risk
*Will be used to Calculate % of Land in
Each risk Level
Passaic_Risk Field Within Area_Risk
Table
Statistics for Passaic Field which Summarizes all areas for this County
TOTAL Area of Passaic County = 516,111,634 m^2
Field Calculator:(Passaic/
516,111,634)*100
% of land in Each Risk Level for Passaic
County, NJ
Add New Field: Bergen_Risk
*Will be used to Calculate % of Land in
Each risk Level
Bergen_Risk Field Within Area_Risk
Table
Statistics for Bergen Field which Summarizes all areas for this County
TOTAL Area of Bergen County = 633,837,828 m^2
Field Calculator:(Bergen/
633,837,828 )*100
% of land in Each Risk Level for Bergen County,
NJ
Add New Field: Sussex_Risk
*Will be used to Calculate % of Land in
Each risk Level
Sussex_Risk Field Within Area_Risk
Table
Statistics for Sussex Field which Summarizes all areas for this County
TOTAL Area of Sussex County =
1,368,826,003.10912 m^2
Field Calculator:(Sussex/
1368826003.10912)*100
% of land in Each Risk Level for Sussex County,
NJ
SVEAI_Final Feature Layer
Geophysical Risk Raster
Tabulate Area: Used to quantify the land area in each county classified under each risk level
Field calculator: Used to quantify the percentage of land area in each risk level for each county i.e. very low risk area/total area) * 100. **Done for ALL 21 Counties of New Jersey
Quantifying Output: Result
This table shows the output of the % of land per county that falls in the following risk classes:
Very Low, Low, Moderate, High, and Very High. The highest % value is boxed in red.
Highest VERY LOW Risk: Sussex County 99.6% of land
Highest VERY HIGH Risk: Bergen County 77.4% of land
County Hurricane Sandy Impact Rank
SVEAI Index (0-1)
Evacuation Assistance Need Index (Overlay of SVEAI and Geophysical Risk)-Highest Percentage of Risk Level Classification
Highest Risk level Found in NJ County
Percentage of High Risk Level Found
Atlantic Very High .56 Moderate 82.23Bergen Very High .78 Very High 77.35Burlington High .55 Moderate 79.09Camden High .67 Very High 50.44Cape May Very High .49 Low 81.62Cumberland High .55 Moderate 83.76Essex Very High .84 Very High 76.61Gloucester High .48 Low 67.24Hudson Very High .75 High 57.08Hunterdon Moderate .37 Very Low 71.03Mercer High .57 Moderate 47.17Middlesex Very High .71 High 50.41Monmouth Very High .65 High 92.90Morris High .55 Low 48.96Ocean Very High .72 High 75.42Passaic High .71 Moderate 37.92Salem High .45 Low 85.63Somerset High .48 Low 70.07Sussex Moderate .39 Very Low 96.55Union Very High .66 High 87.53Warren Moderate .43 Very Low 60.80
Comparing Results to Control Map
Very High in Both!
Low in Both!
Further Study:• Assessing physical accessibility of at-risk areas
• Calculating average distance of at-risk county to an emergency service or evacuation route
• Using different and/or additional variables in risk maps• Social vulnerability:
• Disabled population• No access to phone or car
• Geophysical Risk:• Storm surge• Flood probability
• Using study findings to develop an emergency management plan for a particular at-risk county i.e Essex County
• Creating a flood scenario with more detailed wind patterns
http://www.stpaul.gov/index.aspx?nid=97