By: Maureen Bishop
EFB 519: Geographic Modeling
Final Project
New Jersey, USA:
1) Social Vulnerability
2) Geophysical Risk
3) Evacuation Assistance Need
4) Compare to FEMA Impact
Map f...
What is a natural disaster?
“...geophysical events, such as
earthquakes, landsliding,
volcanic activity and flooding”
(
nt...
• Floods are most common
natural disaster in the U.S.
(Floodsmart.gov)

www.nj.com

•
•
•
•

Heavy, intense rainfall
Run-o...
• Basis for understanding social, demographic, and
physical aspects of the study site of New Jersey.
• Important to consid...
• Step 1: Use GIS to create Social Vulnerability, Geophysical
Risk, and Evacuation Assistance Need Maps
• Step 2: Quantify...
Vector Analysis:
• Add Field
• Field Calculator
• Feature to Raster

Raster Analysis:
• Reclass
• Slope
• Raster calculato...
Most greatly
impacted areas
are along COAST

Using FEMA Data
Social Vulnerability Assessment Index Variables:
Characteristic

Variable
(All variables are by
county)

Source

Populatio...
CREATING SOCIAL VULNERABILITY FOR
EVACUATION ASSISTANCE INDEX:
NJ Counties Layer with 2000
Census Data

Access to Resource...
CREATING SOCIAL VULNERABILITY FOR
EVACUATION ASSISTANCE INDEX:
Population with Special Evacuation Needs:
Population age 5 ...
CREATING SOCIAL VULNERABILITY FOR
EVACUATION ASSISTANCE INDEX:
Population and Structure:
Population Density Variable

NJ C...
Creating Overall Social Vulnerability by
Summing 5 Variables
CREATING FINAL SOCIAL VULNERABILITY FOR
EVACUATION ASSISTANCE...
CONTROL MAP:
FEMA IMPACT

RESULT: Most Socially Vulnerable
1) Essex County : .84
2) Bergen County : .78
3) Hudson County :...
RESULT:
Top three at-risk areas: All in Northeast New Jersey
1) Essex County (.84) Had a value of 1 for having greatest p...
1)
•
•
•

ELEVATION (meters):
High Risk (3)
= -25.26 – 278.87
Moderate Risk (2) = 278.87 – 717.40
Low Risk (1)
= 717.40 – ...
2) SLOPE (Degrees):
• High Risk (3)
= 0 – 2.58
• Moderate Risk (2) = 2.58 – 8.24
• Low Risk (1)
= 8.24 – 41.36

RECLASS:
3...
3) Land Cover:

• High Risk (3)
= Unconsolidated Shoreline
• Moderate Risk (2) = Developed Area: Highly, Moderately,
and L...
Elevation RECLASSED Slope RECLASSED

+

Land Cover RECLASSED

+

Geophysical Risk

=

Potential Values for Geophysical Ris...
CREATING GEOPHYSICAL RISK INDEX:
Based on Elevation, Slope and Landcover
ELEVATION VARIABLE
ArcToolbox> Spatial Analyst
To...
CONTROL MAP:
FEMA IMPACT

RESULT:
-Elevation plays key role in
deciding spatial distribution
of at-risk areas
-High elevat...
X

NJ Geophysical Risk:

NJ SVEAI:

Very Low

0.37 - 0.39

Low

0.40 - 0.49

Moderately Low

0.50 - 0.57

Moderate
Moderat...
Potential Values for Overlay_Risk = 0-9
SVEAI Index were decimals from 0-1
Geophysical Risk were integers from 3-9
When m...
CONTROL MAP:
FEMA IMPACT

RESULT:
County with LOWEST Need:
Sussex County 96.5% Very Low
• High elevation, less people, an...
Sussex

Passaic
Bergen

Morris

Warren

Hunterdon

Essex
Hudson
Union
Somerset
Middlesex

Mercer

Monmouth

Evacuation Ass...
Quantifying at Risk Areas By
County: Based on Overall Risk
(Overlayed Social and Geophysical
Factors)

SVEAI_Final Feature...
This table shows the output of the % of land per county that falls in the following risk classes:
Very Low, Low, Moderate,...
County

Hurricane
Sandy Impact
Rank

SVEAI Index
(0-1)

Evacuation Assistance Need Index (Overlay of
SVEAI and Geophysical...
• Assessing physical accessibility of at-risk areas
• Calculating average distance of at-risk county to an emergency
servi...
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Assessing Geophysical Risk and Social Vulnerability to Natural Disasters

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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.

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Assessing Geophysical Risk and Social Vulnerability to Natural Disasters

  1. 1. By: Maureen Bishop EFB 519: Geographic Modeling Final Project
  2. 2. New Jersey, USA: 1) Social Vulnerability 2) Geophysical Risk 3) Evacuation Assistance Need 4) Compare to FEMA Impact Map from Hurricane Sandy 5) Create a scenario for flooding based on geophysical risk • 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:
  3. 3. What is a natural disaster? “...geophysical events, such as earthquakes, landsliding, volcanic activity and flooding” ( ntara-Ayala, 2002) What is vulnerability? ( ntara-Ayala, 2002) “…a function of the degree of social and self-protection available to potential victims” ( ntara-Ayala, 2002) (Montz, 2001)
  4. 4. • Floods are most common natural disaster in the U.S. (Floodsmart.gov) www.nj.com • • • • 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 www.ibtimes.com (How and Whys of Floods, pbs.org)
  5. 5. • 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.
  6. 6. • 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
  7. 7. Vector Analysis: • Add Field • Field Calculator • Feature to Raster Raster Analysis: • Reclass • Slope • Raster calculator: Addition and Overlay • Tabulate Area
  8. 8. Most greatly impacted areas are along COAST Using FEMA Data
  9. 9. Social Vulnerability Assessment Index Variables: Characteristic Variable (All variables are by county) Source Population and Housing 1) Total Population (2000) 2) Number of Occupied Housing Units (2000) 3) Population below poverty level (2000) Mastering ArcGIS. Maribeth Price, 5th ed. Access to Resources Population with Special Evacuation Needs 4) Percent of population (2000) 5 years of age and under 5) Percent of population (2000)over 65 years of age METHODS: 1) Create all input variables 2) Create standardized version of all variables (0-1 Value) Mastering ArcGIS. Maribeth Price, 5th ed. USDA Economic Research Service 2000 Census Poverty Rate by County Mastering ArcGIS. Maribeth Price, 5th ed. 3) Sum standardized variables and divide by total number of variables (5) (0-1 Value) Mastering ArcGIS. Maribeth Price, 5th ed. (Chakraborty, 2005)
  10. 10. CREATING SOCIAL VULNERABILITY FOR EVACUATION ASSISTANCE INDEX: NJ Counties Layer with 2000 Census Data Access to Resources: Population Below Poverty Level Poverty Field Added to Counties Layer Add New Field: Poverty Edit Mode: Enter Poverty Rates by County Poverty Rates by NJ County Field Sort Poverty Rates Ascending to Identify Max value Essex Cty= 15.6% poverty 2000 Census Poverty Rate by New Jersey Counties: USDA Economic Research Service Add New field Stan_SVI_Pov: For standarized poverty index for NJ Counties Stan_SVI_Pov Field Created in NJ Counties Layer Field Calculator for Stan_SVI_Pov to Create Standarized Variable Among Counties Use Equation SVEAIx= (Rx/Rmax) 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. POVERTY VARIABLE
  11. 11. CREATING SOCIAL VULNERABILITY FOR EVACUATION ASSISTANCE INDEX: Population with Special Evacuation Needs: Population age 5 years and under Variable NJ Counties Layer with 2000 Census Data Add New Field: Stan_SVI_U5: For standarized %U5_Pop Add New Field: %Pop_U5 Stan_SVI_U5 Field Created in NJ Counties Layer U5_Tot_Pop Field Added to Counties Layer Field Calculator to Create Standarized Variable Among Counties Use Equation SVEAIx= (Rx/Rmax) SVEAIu5_tot_pop= U5_Tot_Pop/7.46479 CREATING SOCIAL VULNERABILITY FOR EVACUATION ASSISTANCE INDEX: Field Calculator to Create %Pop under 5: Calculation: Age_Under5/Pop2000 U5_Tot_Pop by NJ County Field Sort U5_Tot_Pop Descending to Identify Max value % Pop. Under 5 VARIABLE Somerset Cty= 7.46479% of Pop. Is below poverty level 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. Population with Special Evacuation Needs: Population age 65 years and over Variable NJ Counties Layer with 2000 Census Data Add New Field: Stan_SVI_Ov65: For Standardized %Ov65_Pop Add New Field: %Pop_Ov65 Ov65_Tot_Pop Field Added to Counties Layer Stan_SVI_Ov65 Field Created in NJ Counties Layer Field Calculator to Create Standarized Variable Among Counties Use Equation SVEAIx= (Rx/Rmax) SVEAIov65_tot_pop= Ov65_Tot_Pop/22.168 Field Calculator to Create %Pop over 65: Calculation: Age_Over65/Pop2000 Ov65_Tot_Pop Field by NJ County Field % Pop. Over 65 VARIABLE Sort Ov65_Tot_Pop Descending to Identify Max value Ocean County = 22.168% of Pop. Is over 65 years 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.
  12. 12. CREATING SOCIAL VULNERABILITY FOR EVACUATION ASSISTANCE INDEX: Population and Structure: Population Density Variable NJ Counties Layer with 2000 Census Data Sort Pop2000 Field Descending to Identify Max value Bergen County = 884118 people POP. DENSITY VARIABLE Add New Field: Stan_SVI_Tot_Pop: For standarized Tot_Pop Stan_SVI_Tot_Pop Field Created in NJ Counties Layer Field Calculator to Create Standarized Variable Among Counties Use Equation SVEAIx= (Rx/Rmax) SVEAIPop2000= Pop2000/884118 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. CREATING SOCIAL VULNERABILITY FOR EVACUATION ASSISTANCE INDEX: NJ Counties Layer with 2000 Census Data Add New Field: Stan_SVI_U5: For standarized OCC_Housing Add New Field: OCC_Housing Stan_SVI_Housing Field Created in NJ Counties Layer OCC_Housing Field Added to Counties Layer Field Calculator to Create Standarized Variable Among Counties Use Equation SVEAIx= (Rx/Rmax) SVEAIHousing= OCC_Housing/330817 Field Calculator to Create OCC_Housing: Calculation: Owner_OCC + Renter_OCC OCC_Housing by NJ County Field Sort OCC_Housing Descending to Identify Max value 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. Bergen Cty= 330817 housing units OCCUPIED HOUSING VARIABLE
  13. 13. Creating Overall Social Vulnerability by Summing 5 Variables 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 Stan_SVI_Pov Field Field Calculator to Create Final Social Vuln. Index SVEAI_Final Field Added in NJ Counties Layer SVEAI= Sum(SVEAIx)/# of variables Stan_SVI_U5 Field Calculation: (Stan_SVI_Pov + Stan_SVI_U5 + Stan_SVI_Ov65 Field Stan_SVI_Ov65 + Stan_SVI_Tot_Pop + Stan_SVI_Housing)/5 Stan_SVI_Tot_Pop 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= .84 2) Bergen County= .78 3) Hudson County= .75 Symbology: Display NJ Counties by SVEAI Field with Green (Low Vuln.) to Red (High Vuln.) Color Ramp Stan_SVI_Housing Social Vulnerability for Evacuation Assistance Index Map: 0= LEAST overall social vulnerability 1= GREATEST overall social vulnerability
  14. 14. CONTROL MAP: FEMA IMPACT RESULT: Most Socially Vulnerable 1) Essex County : .84 2) Bergen County : .78 3) Hudson County : .745
  15. 15. RESULT: Top three at-risk areas: All in Northeast New Jersey 1) Essex County (.84) Had a value of 1 for having greatest poverty rate 2) Bergen County (.78) Had a value of 1 for having greatest number of occupied housing units 3) Hudson County (.75) Had a value of ~1 (.99) for having great poverty rate
  16. 16. 1) • • • ELEVATION (meters): High Risk (3) = -25.26 – 278.87 Moderate Risk (2) = 278.87 – 717.40 Low Risk (1) = 717.40 – 1785.41 RECLASS: 3 classes NJ Elevation NJ Elevation Reclass High : 1785.41 High Elevation (LOW Risk) Low : -25.2622 Mid-Elevation (Moderate Risk) Low Elevation (HIGH Risk)
  17. 17. 2) SLOPE (Degrees): • High Risk (3) = 0 – 2.58 • Moderate Risk (2) = 2.58 – 8.24 • Low Risk (1) = 8.24 – 41.36 RECLASS: 3 classes NJ Slope 0 - 0.810990876 0.810990876 - 2.270774452 2.270774453 - 4.054954379 4.05495438 - 6.325728832 NJ Slope Reclass 6.325728833 - 8.920899634 High Slope (LOW Risk) 8.920899635 - 12.00266496 Medium Slope (MODERATE Risk) 12.00266497 - 15.89542117 Low Slope (HIGH Risk) 15.89542118 - 21.5723573 21.57235731 - 41.36053467
  18. 18. 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 RECLASS: 3 classes NJ Land Cover Highly Developed: >75% Impervious Mod. Developed: 50-75% Impervious Lightly Developed: 25-50% Impervious Lightly Developed-Unwooded: 25-50% NJ Land Cover Reclass Cultivated/Grassland Water/Wetlands/Forest/Bare Land (LOW Risk) Upland Forest Developed Areas (MODERATE Risk) Bare Land Shoreline (HIGH Risk) Unconsolidated Shore Estaurine Wetland Palustrine Wetland Water
  19. 19. Elevation RECLASSED Slope RECLASSED + Land Cover RECLASSED + Geophysical Risk = Potential Values for Geophysical Risk: 3 (Very Low Risk)-9 (Very High Risk) Minimum value would be: 1 + 1 + 1 = 3 Maximum value would be: 3 + 3 + 3 = 9
  20. 20. CREATING GEOPHYSICAL RISK INDEX: Based on Elevation, Slope and Landcover ELEVATION VARIABLE ArcToolbox> 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 NJ 100 DEM: NJ Dept of Environmental Protection DEM Reclass Layer: 3: -25.262161 – 278.87443 meters 2: 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> SLOPE NJ 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 degrees 1: 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 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 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 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 Risk 5 = Moderately Low Risk 6= Moderate Risk 7= Moderately High Risk 8= High Risk 9= Very High Risk Geophysical Risk Index Map
  21. 21. CONTROL MAP: FEMA IMPACT 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
  22. 22. X NJ Geophysical Risk: NJ SVEAI: Very Low 0.37 - 0.39 Low 0.40 - 0.49 Moderately Low 0.50 - 0.57 Moderate Moderately High 0.58 - 0.75 0.76 - 0.84 High Very High NJ Evacuation Assistance Need: Very Low Low Moderate High Very High
  23. 23. Potential Values for Overlay_Risk = 0-9 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). 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 ArcToolbox> Spatial Analyst Tools> Reclass>RECLASSIFY -Used Natural Breaks, 5 classes SVEAI_Final Raster Created Geophysical Risk Raster Overlay_Risk Reclassed: 1= 1.12 – 2.39 Very Low Risk 2= 2.39 – 3.45 Low Risk 3= 3.45 – 4.36 Moderate Risk 4= 4.36 – 5.33 High Risk 5= 5.33 – 7.58 Very High Risk 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) Symbology: Display Overlay_Risk with Green (Very Low Risk) to Red (Very High Risk) Color Map Overlay_Risk Created Overlay_Risk Map Showing Product of Social Vulnerability and Geophysical Risk
  24. 24. CONTROL MAP: FEMA IMPACT RESULT: County with LOWEST Need: Sussex County 96.5% Very Low • High elevation, less people, and forested area County with GREATEST Need: Bergen County 77.4% Very High • High poverty rate, low elevation and slope, and dense population
  25. 25. Sussex Passaic Bergen Morris Warren Hunterdon Essex Hudson Union Somerset Middlesex Mercer Monmouth Evacuation Assistance Need: New Jersey NJ Cities Very Low Burlington Camden Gloucester Ocean Low Moderate High Salem Very High Atlantic Cumberland Cape May Overlay Cities with Evacuation Assistance Need RESULT: High risk areas have many cities
  26. 26. Quantifying at Risk Areas By County: Based on Overall Risk (Overlayed Social and Geophysical Factors) SVEAI_Final Feature Layer Geophysical Risk Raster Reclassed Overlayed Risk Map: Tabulate Area: Input Raster= Overlay_Reclass Zone Field= Count of pixels Input Feature= SVEAI_Final Class Field= County Name -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 Area_Risk Table Showing Area for Each Risk Level For Each County Add New Field: Risk_Class -Edit Mode RowID 1= Very Low RowID 2= Low RowID 3= Moderate RowID 4= High RowID 5= Very High Risk_Class Field Within Area_Risk Table to Keep track of which rows correspond to which risk level 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 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 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: (Passaic/ 516,111,634)*100 Field Calculator: (Bergen/ 633,837,828 )*100 Field Calculator: (Sussex/ 1368826003.10912) *100 % of land in Each Risk Level for Passaic County, NJ % of land in Each Risk Level for Bergen County, NJ % of land in Each Risk Level for Sussex County, NJ 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
  27. 27. 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
  28. 28. 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 Very High in Both! Low in Both! Atlantic Bergen Burlington Camden Cape May Cumberland Essex Gloucester Hudson Hunterdon Mercer Middlesex Monmouth Morris Ocean Passaic Salem Somerset Sussex Union Warren Very High Very High High High Very High High Very High High Very High Moderate High Very High Very High High Very High High High High Moderate Very High Moderate .56 .78 .55 .67 .49 .55 .84 .48 .75 .37 .57 .71 .65 .55 .72 .71 .45 .48 .39 .66 .43 Percentage of High Risk Level Found Moderate Very High Moderate Very High Low Moderate Very High Low High Very Low Moderate High High Low High Moderate Low Low Very Low High Very Low 82.23 77.35 79.09 50.44 81.62 83.76 76.61 67.24 57.08 71.03 47.17 50.41 92.90 48.96 75.42 37.92 85.63 70.07 96.55 87.53 60.80
  29. 29. • 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
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