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