H
Haazzaarrdd V
Vuullnneerraabbiilliittyy ttoo P
Peeooppllee aanndd P
Prrooppeerrttyy iinn tthhee
Sims Bayou Watershed of Houston, Texas
April 2015
by
*Philip Berke, Professor, Director, Institute of Sustainable Coastal
Communities
*Chi Huang, Doctoral Student
*Jaekyung Lee, Doctoral Student
*Galen Newman, Assistant Professor
0
Acknowledgements: Produced by Resiliency and Climate Change Cooperative Project,
Institute of Sustainable Coastal Communities, Texas A&M University.
Table of Contents
Why Study Physical Vulnerability?
2
Why Study Sims Bayou?
2
Study Objectives
3
Next Steps: Neighborhood Involvement
3
What is Hazard Vulnerability?
3
Appendix A: Methodology
5
Appendix B: Maps
See attachment
References
22
1
Hazard Vulnerability to People and Property in the
Sims Bayou Watershed of Houston, Texas
Why Study Social and Physical Vulnerability?
Vulnerability of populations and built environments to hazards significantly influences
the ability of communities to anticipate, respond, resist, and recover from hazard events.
Vulnerability to hazards is not equal among different population groups. Communities
with limited resources often sustain higher levels of loss and their households have
limited ability to repair or replace damaged homes and other property. Households
without reliable transportation face challenges evacuating to safer areas. Many are forced
to seek shelter in facilities that are unsafe and ill-equipped. More vulnerable residents are
forced to flee to distant locations and can face a difficult and prolonged recovery due to
the dissolution of social networks, extended periods of unemployment, and a complicated
federal aid process.
Why Study Sims Bayou?
The Sims Bayou watershed drains an area of 94 square miles that is highly vulnerable to
hazards (see Figure 1). It contains many of the vulnerabilities associated with flooding in
the Houston metropolitan area. The Sims Bayou channel serves as a major run-off
drainage channel for Houston, one of several channels in the Houston area suffering from
flooding and pollution problems as a result of the metropolitan area's unusually rapid
growth during the 1970s. Despite flood control programs, the impact of flooding along
the bayou is expected to increase as population and economic growth continue in an area
characterized by clay soils and flat coastal terrain.
Figure 1: Sims Bayou Watershed*
*The Sims Bayou watershed covers about 94 square miles.
Approximately 83 percent of the watershed is within Harris
County and 17 percent is within Fort Bend County. The Harris
County portion of the bayou lies within the southeastern part of
Houston, Texas.
2
Objectives
Study objectives for the Sims Bayou watershed:



Identify key areas exposed to flood hazards and future sea level rise;
Determine the level of social vulnerability of people and physical vulnerability of
buildings in the watershed and compare vulnerability with the rest of the city; and
Create maps that show differences in social vulnerability and physical
vulnerability in the watershed to determine the variability in capacity to cope with
hazards.
Appendix A includes a detailed explanation of the methods used to: a) identify land in the
Sims Bayou watershed exposed to current flood hazards areas and future sea level rise;
and b) determine vulnerability of people and vulnerability of buildings in the Sims Bayou
watershed. Appendix B includes a series of maps that visually show the current flood
hazards and future areas exposed to sea level rise, and the vulnerability of people and
property in the watershed.
Next Steps: Neighborhood Involvement
We anticipate that information generated by this assessment will represent an initial step
in helping communities understand the social and physical context within which a
disaster occurs. We expect this study will be used to supplement the preparation of
neighborhood-based vulnerability assessments that involve local people affected by
hazards in their neighborhoods. Incorporation of experiential knowledge of people who
have lived through disasters and who understand how such hazards make them vulnerable
can ensure that the assessment is relevant to those who are most vulnerable. Also,
meaningful community involvement will help raise awareness of the risks and motivate
community members and organizations to act.
What is Hazard Vulnerability?
Hazard vulnerability includes two core dimensions:


Hazard exposure is the potential to coverage of the geographic extent and severity of
a hazard in urban areas as illustrated on floodplain maps.
Vulnerability comprises the social and physical susceptibility of a community to loss
from hazards:
o Social vulnerability considers the social and economic characteristics,
such as poverty, race/ethnicity, age, and gender of households that will
impact their ability to prepare for, anticipate, cope with, and recover from
hazard events. For example, age affects vulnerability of an individual.
There are many reasons why the elderly are more vulnerable to a disaster,
including, …”physical limitations that influence their inability or
unwillingness to comply with mandatory evacuation orders; post-disaster
psychological stress that impairs recovery and increases the need for
additional social services; declining cognitive abilities to process hazard
information necessitating specially targeted risk communication or
warning messages; and fewer economic resources to repair damaged
3
homes, especially by elderly residents on fixed incomes. Thus, the greater
the proportion of elderly in a community, the more vulnerable it is and the
longer it will take for the community to fully recover from the disaster’s
aftermath” (Cutter and Finch 2008, p. 2301).
o Physical vulnerability characteristics of the built environment are those
local structures that are threatened by hazards. The type, number and
improved value of structures that serve as community assets are indicators
of vulnerability.
As illustrated in Figures 1a, 1b, and 1c, vulnerability can be described as the extent to
which social vulnerability and physical vulnerability overlap hazard exposure (areas A,
B, and C). A reduction in vulnerability is represented by smaller overlaps that with the
area exposed to hazards. The aim of local planning and actions should be to reduce the
overlap as illustrated in Figure 1b.
The framework to guide our study of vulnerability is based on the concept of community
resiliency. Resilience is “the ability to prepare and plan for, absorb, recover from, and
more successfully adapt to adverse events” (NRC 2012, p. 1). Resiliency emphasizes a
proactive approach to managing coastal hazards, rather than the more dominant reactive
approach.
Figure 2: Community Hazard Vulnerability
4
Appendix A: Methodology
Three major tasks were undertaken to achieve the study objectives: 1) delineate hazard
zones; 2) estimate vulnerability based on geospatial indicators; and 3) mapping
vulnerability scores.
Task 1: Delineate Hazard Zones
Initially, we focused on delineation of hazard zones based on the National Flood
Insurance Program (NFIP) flood maps and sea level rise. While there are other coastal
hazards (shoreline erosion, historical hurricane events, precipitation driven stormwater
floods), we focused on NFIP flood zones given their salience in national policy and
nationwide availability of data linked to these hazards. Delineation of NFIP flood hazard
zones is based on the probability of experiencing a flood as defined by the Digital Flood
Insurance Rate Map (DFIRM) 100-year (1% occurrence probability per year) floodplain
boundaries. The 100-year floodplains are widely used in local hazard mitigation policy
formulation to administer and enforce federal policy goals under the NFIP.
Next, we delineated areas exposed to sea level rise. Recent advances in down-scaling the
effects of global climate change on sea level rise have made it possible to make such
delineations (Climate Central 2014). We use the widely applicable data derived from the
U.S. Army Corps of Engineer’s (USACE) “Sea Level Rise Calculator” that provides
alternative scenarios in 10-year increments up 2100 for relative local sea level rise along
the U.S. coast (USACE 2014).1 The data from USACE provides five potential sea level
rise scenarios recorded by the National Oceanic and Atmospheric Administration
(NOAA) tide gauges: low, intermediate low, intermediate, intermediate high and high sea
level change projections. The Sea Level Rise Calculator provides relative sea level
change projections in ten year increment using the five different scenarios and was used
to project possible scenarios. For this research, the intermediate high scenario (6-foot rise
by in 2100, relative to 2014) projected by NOAA for the Galveston area is utilized. In
order to delineate the temporal and spatial sea level changes on the map, we use the
USGS digital elevation model (DEM) data (source: The Houston-Galveston Area
Council), to forecast sea level rise contained within a 6-foot elevation change relative to
existing sea level conditions.
Task 2: Estimate Vulnerability Based on Geospatial Indicators
The next task was to identify geospatial indicators of physical and social vulnerability.
Building tax values for 2010 are used as a straightforward measure of physical
Sea level rise experienced by an observer on land is referred to as "relative" sea level rise. “Relative” sea
level rise is a function of changes in eustatic sea level as well as shifts in the elevation of the land. Eustatic
sea level rise is the increase in the volume of the oceans that results primarily from the thermal expansion
of sea water as heat is transferred from the atmosphere and from the melting of glaciers, ice caps, and the
Greenland and West Antarctic ice sheets. Relative sea level rise is eustatic sea level adjusted for the local
rate of vertical land movement.
1
5
vulnerability and can be readily converted to a standardized measure (e.g., U.S.$/square
foot).2
Social vulnerability was measured using variables from the Social Vulnerability for
Disaster Management project developed by the U.S. Centers for Disease Control (CDC)
using data from the 2010 U.S. Census at the census tract and block group level (Flanagan
et al. 2011). The project involved organizing social vulnerability into four domains –
socioeconomic status, household composition, minority status, and housing/transportation
– represented by 15 demographic variables selected based on evidence derived from a
comprehensive review of the hazards vulnerability literature. However, 12 indicators
were used since the 2010 Census did not include data for three indicators (see Table A1).
Table A1: US Census 2010 Variable Definitions*
Domain
Socioeconomic
Status
Household
Composition
Minority
Status
Variable
2010
Census
Table
Variable(s)
Censu
s
Level
Description
Percent individuals
below poverty
T117
Block
Group
Individuals below poverty=”under .50” +“.50 to .74” +
“.75 to .99.” Percent of persons below federally defined
poverty line, a threshold that varies by the size and age
composition of the household. Denominator is total
population where poverty status is checked.
Per capita income in
2010
T83
Block
Group
Mean income computed for every person in census block
group. (In <DollarYear> inflation adjusted dollars)
Percent persons
with less than high
school diploma
T25
Block
Group
Percent of persons 25 years of age and older, with less than
a 12th grade education (including individuals with 12
grades but no diploma).
Percent persons 65
years of age or older
T7
Block
Group
Percent persons 17
years of age or
younger
T7
Block
Group
B09002
Block
Group
“Other family: male householder, no wife present, with
own children under 18 years” + “Other family: female
householder, no husband present, with own children under
18 years
Block
Group
Total of the following:
“black or African American alone” + “American Indian
and Alaska Native alone” + “Asian alone” + “Native
Hawaiian and other Pacific Islander alone” + “some other
race alone” + “two or more races” + “Hispanic or Latino white alone.”
Percent male or
female householder,
no spouse present,
with children under
18
Percent Minority
T13
2
Data Source: Harris County Appraisal District (HCAD) Real & Personal Property
Database: http://pdata.hcad.org/download/
6
Percent persons 5
years of age or older
who speak English
less than “well”
Housing /
Transportation
B16004
Block
Group
For all age groups and all languages - the total of persons
who speak English “not well” or “not at all.”
Percent multi-unit
structure
T97
Block
Group
Percent housing units with 10 or more units in structure.
Percent mobile
homes
T97
Block
Group
Percent housing units that are mobile homes.
Crowding
B25014
Block
Group
At household level, more people than rooms. Percent total
occupied housing units (i.e., households) with more than
one person per room.
No vehicle available
B25044
Block
Group
Percent households with no vehicle Available.
* The Flanagan et al. (2011) model used 15 variables. However, 3 variables were excluded (percent persons
more than 5 years old with a disability, percent persons in group quarters, percent unemployed) because the
2010 Census did not include this data.
Source: ACS 2006-2010 (5 Year Estimates)
Each social indicator, except for per capita income, was ranked from highest to lowest
across all census block groups in Houston (N = 1,451). Per capita income was ranked
from lowest to highest since, unlike the other indicators, a higher value means lesser
vulnerability. A percentile rank was then calculated for each block group for each of the
indicators.3
To identify the most vulnerable population for each indicator we identified block groups
with percentile ranks of 25 or higher. These block groups were then identified and
illustrated on a set of maps (see Appendix B).
Task 3: Mapping Vulnerability
The next stage of the process involves mapping the distribution of the physical
vulnerability (i.e., building tax value scores) and most socially vulnerable populations in
hazard zones of land policy districts. Both sets of indicators were originally represented
in a GIS as vector polygons. Such polygons contain large uncertainty in how the
percentile rank values of social vulnerability and physical vulnerability (i.e., building tax
values) are distributed inside each individual census block (population) or parcel
(building tax). Vector representation is problematic when only a portion of a polygons
intersect a boundary of a hazard zone within each land policy district, because it is not
possible to discern the physical vulnerability and percentile rank values that are located
inside the hazard areas of land policy districts.
3
A percentile rank is defined at the proportion of scores in a distribution that a specific score is greater than
or equal to. Percentile ranks were calculated by using the formula:
Percentile Rank = (Rank-1) / (N-1)
Where N = the total number of data points, and all sequences of ties are assigned the smallest of the
corresponding ranks.
7
This spatial distribution problem was addressed for each type of vulnerability. For social
vulnerability, LandScan data was used to distribute the percentile rank vulnerability
values at a finer resolution than the Census block groups. LandScan is a national
population distribution model developed at Oak Ridge National Laboratory (ORNL
2013) that that estimates the number of people within 90-meter cells for both residential
and daytime populations to a higher degree of accuracy compared to other population
distribution models (Patterson and Doyle 2010, Sabesan et al. 2007).4
Using LandScan data, each block group polygon was divided into 90-meter cells (see
Figure 3). The percentile rank value for a given block group was then assigned to each
cell. If a cell had zero population count, it was assigned a percentile rank value of zero.
Figure 3: Application of LandScan
Application of LandScan
LandScan"(90"m"x"90m)"
Census"block"group"
Example:"
There"18"people"in"the"2"cells"
of"LandScan"data"(about"
0.006844"sq"mile)."Based"on"
areal"weighted"method,"there"
are"about"9.56"people"in"it."
Source: U.S. Census (2010) and ORNL (2010).
In order to calculate physical vulnerability, improvement values of structures for 2010 are
used. The Harris County Appraisal District (HCAD) provides not only 2010 real estate
and personal property value data, but also physical parcel boundary data. After sorting
and organizing the data for the Sims Bayou watershed, we standardized the values by
each census block group (e.g., U.S.$/square foot). Additionally, the hazard zones (100year floodplain and 2100 sea level rise boundaries) in Sims Bayou watershed are overlaid
on each parcel and the standardized improved parcel value of each block group in the
hazard zones are calculated. Based on the standardized value for each block group, we
classify the values into three categories with an equal number of units in each category
(e.g., low, medium and high standardized values) and map the scores.
4
For this study nighttime population estimates were used since this data represents the distribution of the
residential population.
8
Table of Contents: Appendix B
Appendix B includes three sets of findings derived from the social vulnerability analysis.
1. Tables B1, B2, and B3 include summary statistics for each of 12 social
vulnerability indicators. The statistics compare the percent and number of
people who are social vulnerable at different geographic scales.
 Table B1 displays the percent and number of people that live in the 100year floodplain by indicator in Sims Bayou and compares these findings
to the entire Sims Bayou watershed and the City of Houston.
 Table B2 displays the percent and number of people by indicator who
live in the area projected to be exposed to sea level rise in 2100 and
compares these findings to the entire Sims Bayou watershed and the City
of Houston.
 Table B3 compares the percent and number of people that live in the
100-year floodplain with the percent and number of people exposed to
the potential sea level rise in 2100 by indicator.
2. Figures B1-B12 displays mapped findings of the most socially vulnerable
populations within Sims Bayou for each of the 12 social vulnerability indicators
listed in Tables B1-B3. As discussed in Appendix A, the most vulnerable are
considered to be in the top 25 percent of census blocks among over 1,451 census
blocks in Houston. We identified these areas and displayed them on maps in the
Sims Bayou watershed.
3. Table B-4 and Figure B13 illustrate physical vulnerability based on the
improved value of structures within the Sims Bayou watershed.
9
List of Tables and Figures: Appendix B
Summary Statistics for Social Vulnerability
Table B1. Social Indicators within 100-year floodplain, Sims Bayou Watershed & Houston
Table B2. Social Indicators within 2100 sea level rise, Sims Bayou Watershed & Houston
Table B3. Social Indicators within 100-year floodplain, 2100 sea level rise & Remainder of the
watershed
Maps of Social Vulnerability
Figure B1. Social Indicator Poverty inside the 100-year Floodplain and Remainder of the
Watershed
Figure B2. Social Indicator Per capita Income inside the 100-year Floodplain and Remainder of
the Watershed
Figure B3. Social Indicator Less than High School inside the 100-year Floodplain and Remainder
of the Watershed
Figure B4. Social Indicator Older than 65 inside the 100-year Floodplain and Remainder of the
Watershed
Figure B5. Social Indicator Younger than 17 inside the 100-year Floodplain and Remainder of the
Watershed
Figure B6. Social Indicator Single Parent Household inside the 100-year Floodplain and
Remainder of the Watershed
Figure B7. Social Indicator Minority inside the 100-year Floodplain and Remainder of the
Watershed
Figure B8. Social Indicator English Fluency inside the 100-year Floodplain and Remainder of the
Watershed
Figure B9. Social Indicator Multi-unit Structures inside the 100-year Floodplain and Remainder
of the Watershed
Figure B10. Social Indicator Mobile Homes Inside the 100-year Floodplain and Remainder of the
Watershed
Figure B11. Social Indicator Crowding inside the 100-year Floodplain and Remainder of the
Watershed
Figure B12. Social Indicator No Vehicle inside the 100-year Floodplain and Remainder of the
Watershed
Summary Statistics and Map of Physical Vulnerability
Table B4. Physical Indicators within the Hazard Zones and the Watershed
Figure B13. Standardized Improved Parcel Value within Sims Bayou Watershed (US$/square
foot)
Figure B14. Standardized Improved Parcel Value within 100-year floodplain (US$/square foot)
Figure B15. Standardized Improved Parcel Value within 2100 sea level rise (US$/square foot)
10
Table B1: Social Indicators within 100-year floodplain, Sims Bayou Watershed & Houston
Socioeconomic
Status
Social Indicator
Data Level
Below Poverty
Population
Per Capita Income ($)
100-year Floodplain
(number)
Sims Bayou Watershed
(number)
Houston
(number)
8.5% (2,227)
8.9% (27,161)
8.5% (169,863)
$ 14,207
$ 15,007
$ 26,102
Less than High School
Population
23.1% (6,054)
21.7% (66,058)
16.5% (330,900)
Older than 65
Population
8.6% (2,241)
8.5% (25,962)
9.1% (181,085)
Younger than 17
Population
31.7% (8,311)
30.6% (93,002)
26.1% (522,082)
Family with One Spouse
Households with Children
34.6% (2,435)
38.9% (29,570)
36.8% (165,279)
Minority
Population
46.3% (12,131)
58.0% (176,485)
44.6% (891,025)
English Less than Well
Population
19.3% (5,054)
18.1% (55,147)
14.3% (286,563)
Multi-Unit Housing
Housing Units
17.9% (1,593)
20.6% (22,224)
34.6% (298,190)
Mobile Homes
Housing Units
1.9% (173)
2.8% (3,019)
1.4% (12,457)
Crowding (people/room)
Housing Units
10.0% (896)
8.8% (9,523)
6.3% (54,582)
No Vehicle Available
Housing Units
9.6% (857)
9.3% (10,028)
8.7% (75,341)
Total Population
26,180
304,062
1,999,431
Area (sq. mi)
7.1 (8.4%)
84.9 (100%)
587.8
Overall Population Density (per sq. mi)
3,687
3,581
3,402
Household
Composition
Minority
Status
Housing /
Transportation
11
Table B2. Social Indicators within 2100 sea level rise, Sims Bayou Watershed & Houston
Socioeconomic
Status
Social Indicator
Data Level
Below Poverty
Population
Per Capita Income ($)
2100 Sea Level Rise*
(number)
Sims Bayou Watershed
(number)
Houston
(number)
4.9% (3,341)
8.9% (27,161)
8.5% (169,863)
$ 14,529
$ 15,007
$ 26,102
Less than High School
Population
11.9% (8,162)
21.7% (66,058)
16.5% (330,900)
Older than 65
Population
4.2% (2,861)
8.5% (25,962)
9.1% (181,085)
Younger than 17
Population
16.3% (11,130)
30.6% (93,002)
26.1% (522,082)
Family with One Spouse
Households with Children
31.0% (3,048)
38.9% (29,570)
36.8% (165,279)
Minority
Population
23.2% (15,845)
58.0% (176,485)
44.6% (891,025)
English Less than Well
Population
11.2% (7,646)
18.1% (55,147)
14.3% (286,563)
Multi-Unit Housing
Housing Units
9.3% (2,365)
20.6% (22,224)
34.6% (298,190)
Mobile Homes
Housing Units
1.3% (319)
2.8% (3,019)
1.4% (12,457)
Crowding (people/room)
Housing Units
5.6% (1,422)
8.8% (9,523)
6.3% (54,582)
No Vehicle Available
Housing Units
4.2% (1,077)
9.3% (10,028)
8.7% (75,341)
Total Population
26,180
304,062
1,999,431
Area (sq. mi)
7.1 (8.4%)
84.9 (100%)
587.8
Overall Population Density (per sq. mi)
3,687
3,581
3,402
Household
Composition
Minority
Status
Housing /
Transportation
* Excludes 100-year floodplain
12
Table B3. Social Indicators within 100-year floodplain, 2100 sea level rise & Remainder of the Watershed
Socioeconomic
Status
Social Indicator
Data Level
Below Poverty
Population
Per Capita Income ($)
100-year Floodplain
(number)
2100 Sea Level Rise*
(number)
Remainder
(number)
8.5% (2,227)
4.9% (3,341)
8.9% (21,593)
$ 14,207
$ 14,529
$ 15,267
Less than High School
Population
23.1% (6,054)
11.9% (8,162)
21.4% (51,843)
Older than 65
Population
8.6% (2,241)
4.2% (2,861)
8.6% (20,860)
Younger than 17
Population
31.7% (8,311)
16.3% (11,130)
30.3% (73,560)
Family with One Spouse
Households with Children
34.6% (2,435)
31.0% (3,048)
9.9% (24,087)
Minority
Population
46.3% (12,131)
23.2% (15,845)
61.2% (148,509)
English Less than Well
Population
19.3% (5,054)
11.2% (7,646)
17.5% (42,447)
Multi-Unit Housing
Housing Units
17.9% (1,593)
9.3% (2,365)
7.5% (18,266)
Mobile Homes
Housing Units
1.9% (173)
1.3% (319)
1.0% (2,527)
Crowding (people/room)
Housing Units
10.0% (896)
5.6% (1,422)
3.0% (7,205)
No Vehicle Available
Housing Units
9.6% (857)
4.2% (1,077)
3.3% (8,094)
Total Population
26,180
26,180
242,528
Area (sq. mi)
7.1 (8.4%)
7.1 (8.4%)
70.1 (82.5%)
Overall Population Density (per sq. mi)
3,687
3,687
3,460
Household
Composition
Minority
Status
Housing /
Transportation
* Excludes 100-year floodplain
13
Maps of Social Vulnerability
Figure B1. Social Indicator Poverty inside the 100-year Floodplain and Remainder of the
Watershed
Figure B2. Social Indicator Per capita Income inside the 100-year Floodplain and
Remainder of the Watershed
14
Figure B3. Social Indicator Less than High School inside the 100-year Floodplain and
Remainder of the Watershed
Figure B4. Social Indicator Older than 65 inside the 100-year Floodplain and Remainder
of the Watershed
15
Figure B5. Social Indicator Younger than 17 inside the 100-year Floodplain and
Remainder of the Watershed
Figure B6. Social Indicator Single Parent Household inside the 100-year Floodplain and
Remainder of the Watershed
16
Figure B7. Social Indicator Minority inside the 100-year Floodplain and Remainder of
the Watershed
Figure B8. Social Indicator English Fluency inside the 100-year Floodplain and
Remainder of the Watershed
17
Figure B9. Social Indicator Multi-unit Structures inside the 100-year Floodplain and
Remainder of the Watershed
Figure B10. Social Indicator Mobile Homes Inside the 100-year Floodplain and
Remainder of the Watershed
18
Figure B11. Social Indicator Crowding inside the 100-year Floodplain and Remainder of
the Watershed
Figure B12. Social Indicator No Vehicle inside the 100-year Floodplain and Remainder
of the Watershed
19
Summary Statistics and Map of Physical Vulnerability
Table B4. Physical Indicators within the Hazard Zones and the Watershed
Physical Indicator
Total Improved Value
Standardized Improved
Value (by sq. ft)
100-year Floodplain
(%)
$ 749 Million (12.5%)
$4.6
2100 SLR:
6-foot* (%)
$ 266 Million (4.4%)
$1.4
Remainder of the
Watershed** (%)
$ 4.99 Billion
(83.1%)
$2.9
* Excludes 100-year floodplain
** Excludes 100-year floodplain and 2100 sea level rise
Figure B13. Standardized Improved Parcel Value within Sims Bayou Watershed By
Census Tract (US$/square foot)
20
Figure B14. Standardized Improved Parcel Value within 100-year floodplain (US$/square
foot)
Figure B15. Standardized Improved Parcel Value within 2100 sea level rise* (US$/square
foot)
* Excludes 100-year floodplain
21
References
Climate Central. 2014. North Carolina and the Surging Sea: A Vulnerability Assessment
with Projections for Sea Level Rise and Coastal Flood Risk. Princeton, NJ.
[www.climatecentral.org]
Cutter, Susan and Christina Finch. 2008. Temporal and Spatial Changes in Social
Vulnerability to Natural Hazards. Proceedings of the National Academy of
Sciences 105(7): 2301-2306.
Flanagan, B., E. Gregory, E. Hallisey, J. Heitgerd, and B. Lewis. 2011. A Social
Vulnerability Index for Disaster Management. Journal of Homeland Security and
Emergency Management 8(1): 1-22.
Harris County Appraisal District (HCAD). 2015. 2010 Certified Values Retrieved from
http://pdata.hcad.org/download/2010.html.
Oak Ridge National Laboratory (ORNL). 2013, ORNL LandScan, (accessed 2/14,
http://web.ornl.gov/sci/landscan/index.shtml
Patterson, L., Doyle, M. 2009. Assessing Effectiveness of National Flood
Policy Through Spatiotemporal Monitoring of Socioeconomic Exposure. Journal
of the American Water Resource Association 45: 237–252.
Sabesan, A., K. Abercrombie, A.R. Ganguly, B. Bhaduri, E. Bright, and P. Coleman,
2007. Metrics for the Comparative Analysis of Geospatial Datasets With
Applications to High-Resolution Grid-Based Population Data. Geo Journal 69:
81-91.
US Army Corps of Engineers (USACE). 2014a. Application of Flood Risk Reduction
Standard for Sandy Rebuilding Projects: Sea-Level Change Curve Calculator
Using the Flood Risk Reduction Standard for Sandy Rebuilding Projects
[http://www.corpsclimate.us/ccaceslcurvesECB.html]
U.S. Census Bureau. 2006-2010 American Community Survey 5-year estimates. Using
American FactFinder. Retrieved from http://factfinder2.census.gov.
22