Population Projection and Housing Demand Methods II
Daniel Turner 34 S. 4th Avenue Highland Park, NJ 08904 daniel.turner86@gmail.com
INTRODUCTION Suffolk County is the easternmost county in New York State, comprising 1,000 square miles of the eastern two-‐thirds of Long Island.i The Algonquin tribe was native to the land that later became known as Suffolk County before the first European, a Dutchman named Adrian Block, made landfall in 1614.ii From 1614 until the 1930’s, the primary industries of Suffolk County were farming, fishing and shipbuilding.iii In the 1930’s, however, the County became home to many large-‐scale U.S. defense and aerospace industries.iv It was during this time that the population of Suffolk County began to experience a notable rise. As indicated in TABLE 1, the population of Suffolk County grew from 110,246 in 1920 to 197,355 in 1940, a 79% rise in two years. Between 1940 and 1970, Suffolk County experienced dramatic population growth. New highways, such as the Long Island Expressway (est. 1958), along with mass-‐produced housing developmentsv spurred this growth. As indicated in TABLE 1, the population of Suffolk County grew from 197,355 in 1940 to 1,124,950 in 1970, an astonishing 470.013% rise over this thirty-‐year period. Since this time period, the population growth in Suffolk County has leveled off, growing by only 32.748% from 1970 to 2010 and by only 5.212% between 2000 and 2010. Table 1: Historical Population Data Year 1790 1800 1810 1820 1830 1840 1850 1860 1870 1880 1890 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010
Population
Change Number Percent
16,400 19,735 21,113 23,936 26,780 32,469 36,922 43,275 46,924 52,888 62,491 77,582 96,138 110,246 161,055 197,355 276,129 666,784 1,124,950 1,284,231 1,321,864 1,419,369 1,493,350
N/A 3,335 1,378 2,823 2,844 5,689 4,453 6,353 3,649 5,964 9,603 15,091 18,556 14,108 50,809 36,300 78,774 390,655 458,166 159,281 37,633 97,505 73,981
N/A 20.335% 6.983% 13.371% 11.882% 21.243% 13.715% 17.207% 8.432% 12.710% 18.157% 24.149% 23.918% 14.675% 46.087% 22.539% 39.915% 141.476% 68.713% 14.159% 2.930% 7.376% 5.212%
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Source: U.S. Census Bureau
The following report analyzes the demographic changes that occurred in Suffolk County between 1940 and 2000. Using historical data and trends, several models have been employed to attempt to project the Suffolk County population in 2010 as well as housing demand in 2010. I. AGE–SEX PYRAMIDS The following Age–Sex Pyramids graphically represent the population of a given year by 5-‐ year age intervals, separated by sex. These pyramids are a useful tool for representing and understanding demographic changes over time. Included here are three Age–Sex Pyramids for the years 1950, 1970, and 2000, along with analyses of their significance. (APPENDIX 1 contains Age–Sex Pyramids for all years from 1940 to 2010, with the exception of 1960 because of the lack of data).
1950 Population The Age–Sex Pyramid for 1950 (see Figure 1 above) reflects the demographic impact that resulted from large-‐scale migration of residents to Suffolk County after World War II. The largest adult population cohorts in 1950 were those between 25 and 45 years old, making up more than 30% of the total population. The largest cohort overall, however, was
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persons under 5 years of age. This cohort totaled 25,275 people, or 9% of the total population. This group of children is part of the generation known as “baby boomers,” defined by the U.S. Census Bureau as people born from mid-‐1946 to 1964.vi In many ways, Suffolk County epitomized the suburban growth that occurred in the United States after World War II as the population exploded with new young families. The year 1950 represents the early stage of population explosion and residential development in Suffolk County that began to wane by 1970. A look at the 1970 Age–Sex Pyramid offers insight into the nature of this growth.
1970 Population Between 1950 and 1970, Suffolk County’s population grew by 848,821 people, or 307.4%. This growth occurred rapidly and without comprehensive planning.vii The political landscape of Suffolk County before this rapid development reflected a much more rural and dispersed population distribution. A variety of municipalities and school districts existed before the large-‐scale growth, and the lack of cohesion between these entities might be looked at as a potential cause of the sprawling style of development that occurred between 1950 and 1970 and still continues to a degree today. A look at the 1970 Age–Sex Pyramid (see Figure 2, above) reflects a more balanced distribution than seen in 1950 but is still profoundly affected by the post-‐war baby boom. Children (those 19 years old and younger) made up 42% of the total population of Suffolk
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County in 1970. The largest cohorts of adults were still the 25-‐ to 45-‐year-‐old cohorts observed in 1950. The main difference between the years 1950 and 1970, however, is the overall number of residents. Population growth, unsurprisingly, coincided with a housing boom. Between 1950 and 1970 more than 220,000 individual detached homes were built in Suffolk County.viii This enormous boom in housing construction, along with the retail sprawl that accompanied it, dramatically altered the landscape of the county, decimating the agricultural landscape and contributing to the decline of pre-‐WWII downtowns.ix The land use changes that occurred between the period of 1950 and 1970 are very important in understanding the demographic changes in the county since that period as well as the planning challenges that that face the county moving forward.
2000 Population By the year 2000, population growth in Suffolk County had slowed dramatically compared to the post-‐war period, growing only 7.376% over the previous decade. The Age–Sex Pyramid for 2000 (see FIGURE 3, above) reflects this slowed growth through noticeable demographic shifts, namely the aging of the population. Children under 19 years old made up only 28.36% of the total population in 2000 compared to 42.42% in 1970. Along those lines, 66.31% of the population of Suffolk County was over the age of 25 in 2000 compared
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with 51.73% in 1970. For those 50 years and older, the numbers show a similar trend with 27.89% of the population belonging to this age group in 2000 compared with 19.18% in 1970. As seen in FIGURE 4, below, the Suffolk County population distribution of those over 50 years old in 2000 closely mirrors that of the United State overall. This might be interpreted as a reflection of how representative the post-‐WWII baby boom in Suffolk County was representative of the United States overall.
II. TREND EXTRAPOLATION PROJECTIONS Trend extrapolation is a process that attempts to predict a future condition based on an aggregate of historical data. For the purposes of this report, multiple trend extrapolation models were used based only on historical population data over time. In order to help test the accuracy of the models, observed population data was used only up until the year 2000. The various models were used to project population to 2010. The projected population number could then be compared against the actual observed 2010 population. Seven types of trend extrapolation methods were used to project Suffolk County’s 2010 population: linear, exponential, logarithmic, polynomial, power, moving average, and log-‐ modified exponential. Each model makes different assumptions about growth. The linear model assumes growth based on constant increments, the exponential model assumes a constant exponential growth rate, the logarithmic model assumes growth based on a constant ratio of logarithms of growth increments, the polynomial and power models
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assumes a constant rate of change and the moving average model makes an assumption based on a given number of prior periods (in this case two). Finally, the log-‐modified exponential model assumes a linearized exponential growth rate but is limited by an asymptotic carrying capacity. The carrying capacity is used in order to acknowledge real world limits to growth such as the availability of space, resources, housing, and other growth limiting factors. Two statistical measures are used in this report to test the strength of each model. The first is the mean absolute percentage error (MAPE). This measures error based on the difference between the projected and actual data. This number ranges from 0 to 1 but is presented here as a percentage. A model with more error will display a higher percentage. The second measure is the R2 statistic. This is a measure of explained variation that also ranges from 0 to 1. In this case, a number closer to 1 is ideal. The following table displays the projected populations of the seven models used as well as the two statistical measures discussed above: Table 2: Statistical Analysis of Trend Extrapolation Models
Log Modified Exponential
Year
Actual Population Linear
Exponential Logarithmic Polynomial Power
1940
197,355
215,589
253,829
212,084
80,597
177,221
Moving Average -‐
1950
276,129
443,295
359,003
442,906
443,296
392,990
236,742
472,569
1960
666,784
671,001
507,756
672,548
751,997
626,181
471,457
821,175
1970
1,124,950
898,707
718,145
901,021
1,006,702
871,460
895,867
1,061,990
1980
1,284,231
1,126,413
1,015,709
1,128,338
1,207,409
1,126,137
1,204,591
1,228,345
1990
1,321,864
1,354,119
1,436,569
1,354,509
1,354,120
1,388,565
1,303,048
1,343,262
2000
1,419,639
1,581,826
2,031,812
1,579,546
1,446,833
1,657,616
1,370,752
1,422,646
2010
1,493,350
1,809,532
2,873,694
1,803,461
1,485,550
1,932,473
1,419,639
1,477,485
R2
0.8996
0.8490
0.9184
0.9555
0.9372
0.9671
MAPE
16.668%
27.336%
16.358%
21.904%
16.466%
24.999%
31.761%
-‐32,075
A close observation of TABLE 2 shows that the two statistical measures do not always align when it comes to measuring accuracy of the model. For example, the log-‐modified exponential model has the best R2 at 0.9671 but also the worst MAPE at 31.761%. This is because MAPE measures error for each data point, whereas R2 measures the closeness of the curve overall.
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Linear Model The linear trend extrapolation model is displayed in FIGURE 5, above. This model has the third best MAPE (16.668) but the second worst R2. These statistical measures do not indicate anything outstanding about this model, and a look at FIGURE 5 seems to indicate that the population growth in Suffolk County is not of a linear nature. This model compounds the rapid population rise of the mid-‐twentieth century with the much slower population growth of recent years and ends up overestimating future population growth by a wide margin (predicting 1,809,532 people in 2010 to the actual 1,493,350). The inability to adjust to more recent trends makes this a poor model to use to predict future growth in Suffolk County
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Exponential Model The exponential model for trend extrapolation is displayed in FIGURE 6, above. This model featured the worst R2 of the seven (0.8490) as well as the second worst MAPE (27.336%). This model compounds the problems of the linear model by not only failing to adjust to recent trends but also by assuming that growth will occur exponentially ad infinitum. This causes the model to dramatically overestimate future population growth, predicting a 2010 population of 2,873,532 people. The exponential model appears to be incongruous with a place like Suffolk County because of the real-‐life significant constraints to growth that exist in the region.
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Logarithmic The logarithmic trend extrapolation model is shown in FIGURE 7, above. This model demonstrates the highest MAPE of the seven models at 16.358% and one of the better R2 at 0.9184. However, a visual analysis of the curve in FIGURE 7 indicates that this model could not properly predict future conditions. Similar to the other models discussed above, this model does not properly adjust to recent trends and continues to project population growth at a high rate. This led the model to predict a 2010 population of 1,803,461 compared with the actual 2010 population of 1,493,350. This population projection was very similar to that of the linear model, which predicted a 2010 population of 1,809,532.
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Polynomial Model The polynomial model (displayed in FIGURE 8, above) has much more visual appeal than the other models discussed thus far. This model seems to more accurately reflect a slower population growth in recent years. Indeed, the polynomial model projected a 2010 population of 1,485,550, which was the closest of all the models to the actual 2010 population of 1,493,350. The R2 for this model was indeed the second highest of all the models at 0.9555, but the MAPE was in the middle of the pack at 21.904%. It appears from these measures that this model might be one of the better predictors of future population growth in Suffolk County.
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Power Model At first glance, the power model appears to have the same problems seen with the linear and logarithmic models (see FIGURE 9 above1). That is, it projects a growth rate that is more in line with past trends than future realities. Indeed, this model predicts a much higher population in 2010 (1,932,473) than the actual population (1,493,350). However, the statistical measures tell a different story. The MAPE for this model is 16.466% (the second lowest) and the R2 is 0.9372 (in the middle of the pack). The problem with this model, as well as the linear and logarithmic models, is that it uses a more constant rate of growth than actually occurred; therefore, it both underestimates and overestimates population at various points in the curve. As can be seen in the FIGURE 9, the power model estimates a population in 1970 that is more than 253,000 people fewer than the actual population. In 2000 the model estimates a population that is nearly 238,000 people more than the actual population in that year.
1 Actual years are not displayed in this model due to a statistical problem caused by their inclusion. In their
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Moving Average Model The moving average trend extrapolation model is displayed in FIGURE 10, above. Visually, this model has great appeal relative to the actual population observed over time. This model might seem to reflect more recent population trends better than most of the previous models because that is what this model is built to do. The moving average model uses an average of a given number of prior periods in order to determine a future estimate. In this case, two periods were used to predict future a future estimate. In other words, in order to predict the population of 1960, the model used an average of the populations of 1940 and 1950. Despite this level of connection to the observed data, this model produced a very high MAPE of nearly 25%. Because of the nature of this model, no R2 was found. This model might be more useful for predicting population in the near future than in the distant future because of its reliance on observed data. In fact, the moving average model predicted a 2010 population in Suffolk County of 1,419,639, which is relatively close to the observed population and, interestingly enough, exactly the same as the 2000 population.
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Log-‐Modified Exponential Model The final trend extrapolation model used was the log-‐modified exponential model (shown in FIGURE 11, above). The change in this model over the exponential model is the addition of an asymptotic carrying capacity that limits the possibility of future growth to a given limit as well as a log function that linearizes the model. For this model, a maximum population of 1,600,000 was used as the carrying capacity based on the apparent limit in the polynomial model as well as knowledge of constraints to future development in Suffolk County (i.e., space, housing, resources, etc). Given that population has been rising at a slow rate in the previous three decades and that new housing construction was down dramatically in the second half of the 2000 decade, it is reasonable to assume that the population of Suffolk County will not grow beyond 1,600,000 in the foreseeable future. With the carrying capacity added to the model, the log-‐modified exponential displayed some of the better predictive capability of all the models reviewed. The R2 for this model was highest of all the models at 0.9671, and the model predicted a 2010 population of 1,477,485, which was the second closest to the actual population of all the models. Interestingly, however, the MAPE for this model was the highest of all the models at 31.761%. This appears to be related to the inability of the model to accurately reflect actual population in the first three years of the model. In fact, this model estimates a negative population for 1940.
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REVIEW OF ALL TREND EXTRAPOLATION MODELS FIGURE 12, below, displays the curves for all seven trend extrapolation models as well as the observed population. This chart illustrates the relative difficulties each model had in accurately reflecting observed population. However, given that the purpose of these models is to estimate future conditions, four models stand out as being incongruous with this task: the linear, exponential, logarithmic, and power models. The other three models— polynomial, moving average, and log-‐modified exponential—all closely resemble actual population growth between 2000 and 2010.
III. COHORT-‐COMPONENT MODEL Another method for predicting population growth is the cohort-‐component model. This model breaks down the population into age–sex cohorts (similar to the Age–Sex Pyramids) and considers birth and death rates and migration in attempting to predict future population growth. In constructing this model, two base years were used for data collection: 1990 and 2000. Age–sex cohort data was collected for five-‐year intervals2 using data from the U.S. Census. Two additional pieces of data were collected for this model: birth rates from 1990 and 2000 and death rates from those years (both acquired from the Centers for Disease Control). This data was collected for New York State because of the lack of county-‐specific data. 2
The last cohort is larger than five years and contains ages 85 and up.
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The first consideration made in the model was the survival rate of each age–sex cohort for 1990. This rate was derived from taking the inverse of the death rate data released by the Centers for Disease Control for 1989–1991. Multiplying the number of people within a given cohort by the corresponding survival rate for that cohort provided an estimation of how many of those individuals survived to make it into the next cohort in 1995. This calculation was made for all age–sex cohorts except 85 and over. For this group, the survival number was calculated using an average of the death rates for all the different age periods above 85. In order to account for additions to the population by birth, a fertility rate was applied to all age-‐appropriate female cohorts. These rates were acquired from Centers for Disease Control Life Tables for 1989–1991 for the New York State level. To estimate the number of births in the period between 1990 and1995, the fertility rate was multiplied by the number of females within the appropriate cohort. Each number was then multiplied by 5 and added together to determine an estimate for the number of births within this period. In order to properly apply these numbers to the age–sex model, the number was divided into males and females based on the assumed newborn ratio of 0.49 females and 0.51 males. This entire procedure was repeated for 2000 using the estimates derived from the 1990 data as well as the 1990 survival rates. Estimates for migration were derived by comparing the estimated 2000 population with the actual 2000 population. The migration residual, as it’s known, for each age–sex cohort was calculated by taking the difference of the actual 2000 figure and the estimated figure. Using U.S. Census data from 2000, as well as fertility and mortality data from this year, the entire procedure was repeated for 2010. The cohort-‐component model predicted an estimated population of 1,380,495. FIGURE 12, below, shows an age–sex pyramid for Suffolk County in 2010 using the cohort component model projection.
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IV. COMPARING COHORT-‐COMPONENT MODEL PROJECTION WITH ACTUAL 2010 DATA In order to assess the accuracy of the cohort-‐component model, the projected 2010 data was compared to the actual 2010 population data. The cohort-‐component model predicted a 2010 population of 1,380,495 compared with the actual population of 1,493,350 (a difference of –112,885). An age–sex pyramid for the actual 2010 population of Suffolk County is shown below in FIGURE 13.
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A comparison of the two age–sex pyramids above reveals an interesting discrepancy between the actual 2010 population and cohort projection. Namely, the projection dramatically undercounts the number of children under 14 (–50,110) while overestimating the number of people between 15 and 34 (+66,705). The middle-‐age population between 35 and 60 is also dramatically underrepresented (–95,928), as is the population of those over 85 (–10,778). The most likely reason for this discrepancy is the use of state-‐wide data to make assumptions about fertility and mortality rates in Suffolk County. As mentioned before, Suffolk County is one of the most populous counties in the United States. In addition, it is also one of the wealthiest (ranking 23rd overall).x These rankings likely mean that Suffolk County is not very representative of New York State, which is characterized not only by a large rural landscape but by New York City, which accounts for 42.5% of the total population of the State.xi It is possible that these differences between Suffolk County and New York State overall (in income, density, and other socio-‐economic factors) caused the cohort-‐component model to estimate a population that was not entirely representative of the actual population of Suffolk.
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V. MAP OF SUFFOLK COUNTY, CHARACTERISTICS FIGURE 14: Map of Long Island Counties
LONG ISLAND New York
Suffolk County, Nassau County & the 5 Boroughs Region
CONNECTICUT
NEW YORK
Long Island Sound
Shelter Island Southold East Hampton
Riverhead
NEW JERSEY
Southampton BRONX
MANHATTAN
North Hempstead QUEENS
BROOKLYN
Oyster Bay
NASSAU COUNTY
Huntington
Smithtown
SUFFOLK COUNTY Brookhaven
Islip Babylon
Hempstead
STATEN ISLAND
ATLANTIC OCEAN
Í
N 1 in = 12.09 miles 0
6
Prepared by Suffolk County Department of Planning, January 27, 2010.
Source: http://www.suffolkcountyny.gov/Departments/Planning/Divisions/CartographyandGIS.aspx
12
18
24 Miles
Suffolk County is located on the eastern two-‐thirds of Long Island. The county is 86 miles long and 26 miles wide at its largest point. The county is comprised of ten towns and a number of incorporated villages. The town governments control most of the land use decisions as well as the provision of basic local services. FIGURE 15, below, shows the various towns and villages in Suffolk County.
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FIGURE 15: Suffolk County Towns and Incorporated Villages S U F F O L K C O U N T Y, N E W YO R K
ELIZABETH AIRPORT
Menantic Rd
v
und So
Ro u
k Ln
er R iv
e Rd eplac Fir
O l d Montau k H
uk Hwy Old Monta
Amagansett
Rd Hole berry Montauk Hwy Cran
Hwy
Napeague
ods
Ln East Hampton
GENERAL
Sa gaponack
Southampton
New York
Beach Rd
Dune Rd
0
Source: Suffolk County Department of Planning, Division of Cartography; NYS Office of Cyber Security & Critical Infrastructure Coordination.
3
6
New Jersey
Miles 12
9
Connecticut Long Island Sound
ATLANTIC OCEAN
Dunes
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Hwy
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S
Ho
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Sa ga po
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Wading River Rd
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NC
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MONTAUK AIRPORT
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ill Rd
Dunes Rd
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59
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38
52
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39
Hampton Bays
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EAST HAMPTON AIRPORT
ttle cu
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EAST 4 l HAMPTON
Wainscott
79
H
Rd
80
North Sea
4
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Westhampton Beach
No
k Rd
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4
FRANCIS S. GABRESKI AIRPORT
try Rd Old Coun
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Northwest Harbor
ek R
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Rd
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Hand
Broadway
Rd
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d-H
P
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71
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Gardiners Island
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4
60
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Rob e rt Mos e s State Pkwy
December 19, 2011 - CD-11-18
104
31
Rd
4
ac R d
Noyack
East Quogue
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Westhampton try
Noy
Great Peconic Bay
Rd
Riv erh
Shelter Island
y Rd Ferr
Co un
Pkwy
Old
RemsenburgSpeonk
Mastic Beach
Great South Bay Ocean
4
S Ferry Rd
71
West Hampton
Oak BeachCaptree
F land e
err y
Northampton SCCC Eastern Campus
Poospatuck Reservation
Gilgo
Riverside
Block Island Sound
NF
36
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55
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98
4 ISLAND 116
Gardiners Bay
Rd
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Robins Island
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East Moriches
4
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4 4 Eastport 51
SPADARO AIRFIELD
Mastic
Shirley
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Brookhaven
in B
Rd N Fe rry
115
26
New Suffolk
ge e St N Ma
80
ni
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Main Rd
Orient
Dering Harbor 42
Nassau Point Rd
l
4 21
4
111
Front St
Nos
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Co
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Brookhaven Memorial Hospital
e Ln idg
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101
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Pa
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l
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Ma
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4
495
Laurel
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BAYPORT AERODROME
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48
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61
112
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Dr Riverhead N u ge n t
§ ¨ ¦ BROOKHAVEN CALABRO AIRPORT
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85
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Jamesport
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63
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105
Rd
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4
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43
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Medford
4
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4 4
Ñ
Bay Ave
Bohemia
North Great River
I 495
Central Suffolk Hospital 58
Sound Ave
Northville
s Ave
Ln Manor
Islip Terrace
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Reeve
Herricks
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Brookhaven National Laboratory
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SOUTHOLD
rs
4
State Hwy 27 Southside Islip Hospital Main St
Ñ
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Good Bay SamaritanShore Hospital
LONG ISLAND ISLIP MacARTHUR AIRPORT
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West Islip
4 50
4
Mont 82auk Hwy
4
90
Pond
Riverhead
RIVERHEAD
CALVERTON AIRPORT
Swan
4 BROOKHAVEN
Ave Osborn
Babylon
State Hwy 25
Ridge
Gordon Heights
on Oreg
Mattituck
Baiting Hollow
Rd
46
4 Holtsville
19
l
ISLIP
4
St
96
29
W hiskey
Sound Ave
Rd
57
34
4
4
4
4
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Memo rial Hw y
d Ave Lakelan
12
an s
Wading River
21
Mill Rd
urch
ood Ave
4
Rd Granny
93
4
4 54
Route 25A
Middle Island
Town Coram Rd
SCCC Ammerman Campus Farmingville
4 4
na l Rd
East Shoreham
Rocky Point
nor
109
North Lindenhurst
Central Islip Psychiatric Center
Ñ
13
k
Old
Selden
Miller Place
Fresh Pond Ave
Baywood North Babylon
Ca
4
97
Islandia Ronkonkoma
na l Rd
r Ma
ute
Lindenhurst
67
Brentwood
Ca
Terryville
Long Island Sound
Shoreham
ive
28
4
Route 25A
Sinai
83
4
Centereach
Lake Ronkonkoma
t er
20
Hwy conset Nes
Nesconset
4
Central Islip
4
North Bay Shore
St. James
Lake Grove
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76
Ch
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Hwy
Sound Beach
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Ro
North Amityville
6
set con Nes
Village of the Branch p
S mi
Hauppauge
100
3
47 Sunrise Hwy Brunswick Hospital
Me rric k Rd
4
Pilgrim Psychiatric Center
4
o
at Stony Brook
John T. Mather
Ñ Memorial Hospital
Hallock Ave
n adi W
2
SCCC Grant Campus
Ñ
Port Jefferson Station
k Rd han
4
Deer Park
k
Ñ
North County Complex
St. Charles Hospital
Por tÑ Jefferson
A
Stony Brook
R
E Main St
Smithtown
Ve
Wyandanch
SMITHTOWN
Tpke
o
ntry ou
25
te
SetauketStony Brook East Setauket University University Hospital
e Yap r Plac
Wheatley Heights
l 4 BABYLON
1
W Jericho
H. Lee Dennison Building
4
4 Amityville
Ñ
66
Dix Hills
4
East Farmingdale
Ñ
Jericho Tpke Commack
4
Ñ
Melville
Fu lton St
St. Catherine of Siena
14
HUNTINGTON South Huntington
4
Ro u
4 68
Head of the Harbor
l
Belle Ter re
Poquott Main St
Nissequogue
Ñ
Mille
Elwood
Jericho Tpke
Sagamore Children's Psychiatric Center
Conklin StREPUBLIC AIRPORT
Rd Dock
E Main Kings Park St Psychiatric Center
Huntington Station
West Hills
NASSAU COUNTY
Old
te 112 Rou
92
Kings Park
East Northport
Greenlawn
Smithtown Bay
Veterans Administration Medical Center
Ñ
10
86
Fort Salonga
Rd
4
4
Plum Island East Marion Rd Eastern Long North Island Hospital
St
35
44
Fort S alonga
Huntington
4
W Jericho Tpke
Nor thpor t
Hospital
Ñ
11
County Road Interstate Highway Long Island Rail Road Town Boundary Village
Main
kR
Centerport
Halesite Huntington Main St
Cold Spring Harbor
Old Field
d
ec
Huntington Bay
d
First
Ñ
W
N
Suffolk County Center Suffolk County Community College Hospital Airport Major Road
o
k
Lloyd Harbor
Hals
Asharoken Eatons Neck
Lloyd Ha bor Rd r
Fishers Island
l
Legend
Nassau Cty
Suffolk Cty Atlantic Ocean
Map is subject to revision. This map is not to be used for surveying, conveyance of land, or other precise purposes.
Source: http://www.suffolkcountyny.gov/Departments/Planning/Divisions/CartographyandGIS.aspx
The Long Island Railroad (LIRR) offers service to Suffolk County from New York City. The Long Island Expressway runs down the center of the island from Queens to Riverhead, the seat of the county government. Riverhead is located at the nexus of what are known as the North and South Forks on the east end of the island. Agriculture remains a significant industry on the two forks and transportation to these areas is limited. There are no major highways on the forks and the LIRR runs only infrequent service. FIGURE 16: 2007 Suffolk County Land Use S U F F O L K C O U N T Y, N E W YO R K Smithtown Bay
Legend
Land Use Low Density Residential
Institutional
Utilities
Medium Density Residential
Recreation & Open Space
Wast Handling & Management
High Density Residential
Agricultural
Underwater Land
Commercial
Vacant
Industrial
Transportation Long Island Sound
HUNTINGTON
SHELTER ISLAND
SOUTHOLD
Plum Is
Gardiners Bay
o Block Island Sound Gardiners Is
SMITHTOWN RIVERHEAD
NASSAU COUNTY
Robins Is
Great Peconic Bay
BROOKHAVEN BABYLON
EAST HAMPTON
ISLIP SOUTHAMPTON
Sunrise Hwy
ATLANTIC OCEAN
Great South Bay January 6, 2012 - CD-11-18
Source: Suffolk County Department of Planning, Division of Cartography; Suffolk County Department of Real Property Tax Service Agency; NYS Office of Cyber Security & Critical Infrastructure Coordination.
0
3
6
9
Miles 12
Source: http://www.suffolkcountyny.gov/Departments/Planning/Divisions/CartographyandGIS.aspx
LAND USE, 2007 Map is subject to revision. This map is not to be used for surveying, conveyance of land, or other precise purposes.
FIGURE 16, above, shows the land use in Suffolk County in 2007. The county contains a variety of land uses; however, the majority is residential. The western half of the county contains most of the population density (see FIGURE 17, below), while the east end is characterized by agricultural land and open space preserves.
19 | P a g e
FIGURE 17: 2010 Suffolk County Population Density S U F F O L K C O U N T Y, N E W YO R K
Fishers Island
Legend 4,001 - 5,000
v
und So
Ro u
e Rd eplac Fir
ile Har bo
rings Sp
Thre eM
w
y
Hwy
c Rd
t one
na
Ac ca bo
Old S
Brick Kiln Rd d
le Ho
Sagg Rd
S
O l d Montau k H
Rd Hole berry Montauk Hwy Cran
Hwy
Napeague
EAST HAMPTON
M ain S t
n Rd
n ack
Ocea
Ln
Amagansett
SAGAPONACK
Sa ga po
Rd pton Ham
k Ln
Town
Mo n ta uk
Ln
SOUTHAMPTON
Nec
P lea su
Lyn
ey Nec k Ln
re D r
Rd head
da r St
North
ods
Montauk uk Hwy Old Monta
t
First
Hals
Rd Place Miller
e an Ave N Oc
Ave
Medford
Speonk River
Jessup Ln
ve
Edwards Ave
ain St
Schultz Rd
Ha
s Pat h Joshua
Islip Ave
Wading River Rd
uppa ug e Rd
d ark R
Deer P
Deer Park Ave 231
Ce
Wo
EL a
Dr
ks Rd Ban
Montauk H w y
Bridgehampton
Rd
ke
ingy Spr
9A
Wainscott
ill Rd
County Rd 3
Hill St
Ln Meadow
ttle cu
sk ck
Tuckahoe
Shinneock Reservation
Water Mill
Tpke
Bu
Shinnecock Hills
nA
H
Seb ona c Rd
SOUTHAMPTON
a rbor
d
Hampton Bays
North Sea
EAST East HAMPTON Hampton
S ag
yac
R
C rH
Springs
ek R
No
Rd
Northwest Harbor
s C re
W k Rd
SAG HARBOR
Hand
t e Hwy
Rd
Sta
unt Sina i Cor am Rd
NC
d
Woo db ury Rd
Av e
New Yor k
Rd Whitman Walt
P
oin t
ys
r da
Stony Hill Rd
n Ba
Gardiners Is
Ce
ac R d
Rd
d Rd ow ll T
am pto
ck ya
r Mi ate
d-H
Block Island Sound
Gardiners Bay
Shelter Island
y Rd Ferr
lo w Rd
Pkwy
SHELTER ISLAND S Ferry Rd
adhol
err y
B ro
NF
Brander wy
ea
o g ue S
WESTHAMPTON BEACH
No
R ed C re
QUOGUE
Beach Rd
Dunes Rd
P O P U L AT I O N D E N S I T Y BY C E N S U S D E S I G N AT E D P L A C E , 2 0 1 0
Dune Rd
ATLANTIC OCEAN
DUNES
Fire Island
0
Source: Suffolk County Department of Planning, Division of Cartography; US Census Bureau; NYS Office of Cyber Security & Critical Infrastructure Coordination.
SALTAIRE
d Pk tr an
try Rd Old Coun
Quiogue
Poospatuck Reservation
Nos
Rd
RemsenburgSpeonk
OCEAN
Rob e rt Mos e s State Pkwy
Riv erh
Flanders
Westhampton try
N Bayview Rd ew Rd
Shelter Island
NORTH HAVEN
Great Peconic Bay
East Quogue Co un
New Suffolk
ge e St N Ma
East Moriches
ay v i
Noy
Rd
Rd
Fire Island
nic B
Ponquogue Ave
Old
Center Moriches
in B
Noyack
Northampton
Manorville
WEST HAMPTON
December 5, 2011 - CD-11-18
Dr
Qu
Mastic Beach
Ma
lvd ay B
Riverside
Eastport
Moriches
Shirley Brookhaven
BELLPORT
P e co
o
Main Rd
Orient
Rd Heights N Fe rry Rd
EM
F land e
Mastic
North Bellport
te 25
Nassau Point Rd
N u ge n t
Rd
og tch
Great South Bay
Oak BeachCaptree
Gilgo
Ave Hubbard
Rd
w rro
DERING HARBOR
Southold
Peconic
Rd ek
Pa
e Av
Cutchogue
Bay Ave
Rd
Ln
k East an ph Patchogue ue Ya
PATCHOGUE
Blue Point
Bayport
Rd
Main Rd
Sound Ave
Laurel
Jamesport
Aquebogue
wis Le
Sayville
West Sayville Great River
Copiague
Riverhead
n St
Yaphank
North Patchogue St
ood Ave
Oakdale
urch
Main St
East Islip
s Ave
Ln Manor
State Hwy 27
West Bay Shore
auk Hwy
Holbrook Bohemia
d Ave Lakelan
N Wellw
Mont
E Mai I 495
Medford
ISLIP North Great River Islip Terrace
Islip
BRIGHTWATERS
West Islip
BABYLON
Brookhaven National Laboratory
Reeve
Herricks
Bay Shore
State Hwy 27
West Babylon
LINDENHURST
R iver
Mattituck Northville
RIVERHEAD
BROOKHAVEN
Holtsville
Ronkonkoma
Memo rial Hw y
Ch
North Lindenhurst
Sunrise Hwy
AMITYVILLE Me rric k Rd
Baywood
North Babylon
Rd
rs
BABYLON
109
Pond
Mill Rd
an s
iew
SOUTHOLD
Baiting Hollow
Calverton Swan
Rd
North Amityville
ute
t er
Sound Ave
State Hwy 25
Ridge
nor
Ro
Rd Granny
Wading River
Rd
r Ma
Fu lton St
Central Islip
W hiskey
Middle Island
ive
Farmingville
ISLANDIA
North Bay Shore
na l Rd
Rd
Gordon Heights
Lake Ronkonkoma
Ve
Wyandanch
East Farmingdale
Brentwood
Deer Park
Town
gR
Wheatley Heights
Old
Selden
on Oreg
Na
GREENPORT Front St
in Rd Ma
x Ln
Ca
Coram
Centereach
Route 25A
n adi W
Hauppauge
Stony Brook Hwy conset Nes
LAKE GROVE
Long Island Sound
East Shoreham
Rocky Point
Path
Nesconset
na l Rd
Doctors
VILLAGE OF THE BRANCH p By wn thto
Ca
Terryville
oke Ave Roan
E Main St
S mi
Hwy
Mill Ln
SMITHTOWN St. James
set con Nes
> 7,000
SHOREHAM
Co
R
2,001 - 3,000
Plum Is East Marion Greenport North Rd West
Sound Beach Route 25A
Ave Osborn
Tpke
Miller Place
Fresh Pond Ave
W Jericho
Mount Sinai
k Rd han
Jericho Tpke
Commack
Dix Hills
PORT JEFFE RSON
e Yap r Plac
HUNTINGTON
South Huntington
ntry ou
6,001 - 7,000
e Ln idg
HEAD OF THE HARBOR
Smithtown
A
SetauketHallock Ave East Setauket Port Jefferson Stony Station Brook University
Mille
Elwood
25
5,001 - 6,000
Br
Greenlawn
Jericho Tpke
te
≤1,000 1,001 - 2,000
ll Ln Mi
NISSEQUOGUE
Huntington Station
Melville
Conklin St
Broadway
POQUOTT Main St
Ro u
Rd Dock
te 112 Rou
West Hills
Old
Kings E Main St Park
in St Ma
East Northport
W Jericho Tpke
NASSAU COUNTY
Fort Salonga
Huntington
Mo
Rd
Fort S alonga
Main St
BELLE TERRE
W Bartle tt Rd
Halesite Cold Spring Harbor
OLD FIELD
Smithtown Bay
NORTHPORT
St
Centerport
Main
kR d
Route 112
ec
re Rd E Sho
HUNTINGTON BAY
Head of Pond Rd
W
N
er
Persons per sqmi
ASHAROKEN
Eatons Neck
LLLOYD loyd Ha rbor Rd
HARBOR
R iv
3,001 - 4,000
Menantic Rd
Census Designated Places, 2010
3
6
Miles 12
9
Map is subject to revision. This map is not to be used for surveying, conveyance of land, or other precise purposes.
BEACH
Source: http://www.suffolkcountyny.gov/Departments/Planning/Divisions/CartographyandGIS.aspx
FIGURE 18: 2000–2010 Suffolk County Population Change S U F F O L K C O U N T Y, N E W YO R K
Legend
6
9
er R iv
e Rd eplac Fir
ile Har bo
rings
Thre eM
Sp
w
y
Hwy
c Rd
t one
na
Town
Ln
Mo n ta uk
Old S
Ac ca bo
Brick Kiln Rd d
le Ho
S
re D r
Sagg Rd M ain S t
n Rd Ocea
Ln
O l d Montau k H
Montauk
Hwy
uk Hwy Old Monta
Rd Hole berry Montauk Hwy Cran
Napeague
Amagansett
EAST HAMPTON
SAGAPONACK
Sa ga po
Head of Pond Rd
n ack
ain St
Schultz Rd
Menantic Rd
v
k Ln Nec
ey Nec k Ln
First
Hals
Edwards Ave
Rd head
P lea su
Lyn
ve
Rd Place
e an Ave N Oc
Ave
Medford
Wading River Rd
Ha
s Pat h Joshua
Islip Ave
unt Sina i Cor am Rd
uppa ug e Rd
d
Miller
d
Av e
New Yor k
ark R
Deer P
Deer Park Ave 231 t e Hwy
W Bartle tt Rd
NC
Woo db ury Rd
Rd Whitman Walt
Sta
Speonk River
Jessup Ln
t
3
da r St
North
ods
Dr
Beach Rd
ATLANTIC OCEAN
0
Ce
Wo
EL a
ke
Source: Suffolk County Department of Planning, Division of Cartography; US Census Bureau; NYS Office of Cyber Security & Critical Infrastructure Coordination.
Tpke
ill Rd
Dunes Rd
Bridgehampton
Wainscott
Rd
Springs
SOUTHAMPTON
Dune Rd
DUNES
Fire Island
Montauk H w y
sk ck
Rd pton Ham
ttle cu
Bu
Water Mill
ks Rd Ban
9A
H
County Rd 3
Hill St
a rbor
d
Seb ona c Rd
Tuckahoe
Shinneock Reservation Ln Meadow
o g ue S
North Sea
S ag
Shinnecock Hills
nA
k Rd
R
C rH
EAST East HAMPTON Hampton ek R
SOUTHAMPTON
QUOGUE
Rd
s C re
Hampton Bays
yac
Northwest Harbor
Hand
No
Rd
SAG HARBOR
ingy Spr
lo w Rd
Rd
ys
P
oin t
n Ba
r da
am pto
Gardiners Is
Ce
Stony Hill Rd
d-H
Block Island Sound
Gardiners Bay
Shelter Island
y Rd Ferr
adhol
Pkwy ac R d
W
R ed C re
ea
S Ferry Rd
B ro
err y
try Rd Old Coun
Quiogue
OCEAN SALTAIRE
NF
Rd
No
ck ya
d Rd ow ll T
Rob e rt Mos e s State Pkwy
SHELTER ISLAND
NORTH HAVEN
Noy
r Mi ate
Fire Island
Brander wy
December 5, 2011 - CD-11-18
Westhampton try
WESTHAMPTON BEACH
Poospatuck Reservation
Riv erh
East Quogue Co un
RemsenburgSpeonk
WEST HAMPTON
Great South Bay
d Pk tr an
Mastic Beach
East Moriches
Qu
BELLPORT
Old
Center Moriches
Nos
Moriches
Shirley Brookhaven
New Suffolk
Great Peconic Bay
Rd
Flanders
Eastport Mastic
North Bellport
N Bayview Rd ew Rd
Shelter Island
Cutchogue
ge e St N Ma
Rd
og tch
ay v i
Nassau Point Rd
Pa
in B
Noyack
Northampton
Manorville
o
Main Rd
Orient
Rd Heights N Fe rry Rd
EM
Dr
Ponquogue Ave
k East an ph Patchogue ue Ya
Ma
lvd yB
Rd
PATCHOGUE
nic B a
Riverside F land e
n St
Yaphank
Blue Point
P e co
wis Le
Bayport
te 25
PECONIC
Rd ek
North Patchogue Sayville
Great River
Oak BeachCaptree
Gilgo
Ave Hubbard
Rd
w rro
DERING HARBOR
Southold
x Ln
N u ge n t
Ln
Bohemia
Oakdale West Sayville
Copiague
Rd
Laurel
Jamesport
Aquebogue
Bay Ave
North Great River
Islip Terrace
Islip
Main St
East Islip
Ln Manor
State Hwy 27
West Bay Shore
I 495
Rd
Main Rd
Sound Ave
Herricks
BRIGHTWATERS
Holbrook
St
West Islip auk Hwy
E Mai
Medford
ISLIP
d Ave Lakelan
Mont
Holtsville
Ronkonkoma
urch
ood Ave
BABYLON
LINDENHURST
Riverhead
rs
Bay Shore
State Hwy 27
West Babylon
N Wellw
Sunrise Hwy
Memo rial Hw y
Ch
North North Amityville Lindenhurst
AMITYVILLE Me rric k Rd
North Bay Shore
Baywood
North Babylon
BROOKHAVEN
Brookhaven National Laboratory
s Ave
Path
BABYLON
109
Rd
R iver
Mattituck
Reeve
Na
GREENPORT Front St in Rd Ma
e Av
SOUTHOLD
Northville
RIVERHEAD
Rd
ute
Pond
Mill Rd
an s
on Oreg
Baiting Hollow
Calverton Swan
nor
Ro
t er
Sound Ave
State Hwy 25
Ridge
r Ma
Fu lton St
Rd Granny
Wading River
Rd
ive
Farmingville
ISLANDIA
Central Islip
W hiskey
Middle Island
Gordon Heights
Lake Ronkonkoma
Ve
Wyandanch
East Farmingdale
Brentwood
Deer Park
na l Rd
Rd
gR
Wheatley Heights
Town
Route 25A
n adi W
Hauppauge
Old
Selden
East Shoreham
iew
Co
Ca
Coram
Centereach
Nesconset
Long Island Sound
SHOREHAM
Rocky Point
Plum Is East Marion Greenport North Rd West
e Ln idg
Stony Brook Hwy conset Nes
LAKE GROVE
na l Rd
Doctors
VILLAGE OF THE BRANCHp By wn thto
S mi
Ca
Terryville
No Data*
oke Ave Roan
E Main St
Hwy
> 35%
-5 - 5%
Ave Osborn
SMITHTOWN St. James
set con Nes
-4.9 - -15%
Fresh Pond Ave
Tpke
R
Sound Beach Route 25A
k Rd han
W Jericho
Miller Place
25.1 - 35%
Mill Ln
Smithtown Jericho Tpke
Commack
Dix Hills
Mount Sinai
e Yap r Plac
Jericho Tpke
HUNTINGTON
South Huntington
PORT JEFFERSON
15.1 - 25%
-14.9 - -25%
Br
HEAD OF THE HARBOR
ntry ou
A
Mille
Elwood
25
te 112 Rou
Kings E Main St Park
Greenlawn
te
SetauketHallock Ave East Setauket Port Jefferson Stony Station Brook University
5.1 - 15%
-24.9 - -35%
ll Ln Mi
NISSEQUOGUE
Huntington Station
Melville
Conklin St
Broadway
POQUOTT Main St
Ro u
Rd Dock
in St Ma
West Hills
Old
Mo
Fort Salonga
East Northport
>-35%
St
Rd
Huntington
W Jericho Tpke
NASSAU COUNTY
Smithtown Bay
NORTHPORT
Fort S alonga
Main St
BELLE TERRE
Main
kR
Centerport
Halesite Cold Spring Harbor
OLD FIELD
Route 112
ec
re Rd E Sho
HUNTINGTON BAY
d
und
W
N
So
HARBOR
Ro u
ASHAROKEN
Eatons Neck
LLLOYD loyd Ha rbor Rd
Fishers Island
Population Change: 2000-2010 Percent Change
Miles 12
PERCENT POPULATION CHANGE BY CENSUS DESIGNATED PLACE, 2000-2010** *Some CDP's have been added, split, or merged so that there is no comparable data from 2000 for comparison. ** Some CDP boundaries have been updated, therefore, direct community temporal comparison should be viewed with caution. See 2000 Census Designated Places map for 2000 boundary line to determine these areas. Map is subject to revision. This map is not to be used for surveying, conveyance of land, or other precise purposes.
BEACH
Source: http://www.suffolkcountyny.gov/Departments/Planning/Divisions/CartographyandGIS.aspx
An analysis of FIGURE 17 and FIGURE 18 shows a large discrepancy between where the majority of residents live in Suffolk County and where most of the growth in population has occurred between 2000 and 2010. This indicates that most of western Suffolk County is built out and cannot handle significant housing construction. It lieu of growth in western Suffolk, development has shifted eastward. This threatens the agriculture and open space that characterize this region. Planners in Suffolk County and the various towns within it must plan for the future in growth in the region. Unfortunately, the massive growth that occurred mid-‐century did not lay a blueprint for planned growth. Land constraints make future sprawl impossible, however. Either growth in the county takes a different form than that in the past or the threat of population and economic contraction looms large.
20 | P a g e
VI. THE FUTURE OF SUFFOLK COUNTY There are a variety of challenges relating to future growth in Suffolk County. These include not only the location of future residential development but also the nature of that development and the cost of living that accompanies it. According to the Long Island Index, a non-‐profit research organization concerned with growth on Long Island, the population of people between the ages of 25 and 34 decreased by 12% between the years 2000 and 2010.xii This compares to a 4% increase for this age cohort over the same period country-‐ wide. The cost of housing is likely a primary cause of this decline. While the cost of housing is high for all age cohorts on Long Island (in 2000, 27% of Long Island households spent more than 35% of their income on housing; by 2010, that share had risen to 38%), it is even higher for those between 25 and 34 years old.xiii For this age cohort, 43% pay more than 35% of their household income on housing.xiv An aging population raises concerns about the economic viability of the county in the future. With more residents retiring (and collecting government pensions), many planners are left to wonder whether there are enough tax-‐paying and well-‐employed residents to replace these retirees. VII. HOUSING DEMAND The final section of this report estimates the unmet housing demand in Suffolk County. Data was collected from the U.S. Census Bureau for both 2000 and 2010 measuring total population, population in group homes (including prison), population living in a household, average household size, and number of households. These data were used to project 2020 data based on a linear curve. These results are summarized in TABLE 3A, below. TABLE 3A: Housing Demand Projection
Category
2000 Census
2010 Census
2020 Projection
Population
1,419,369
1,493,350
1,571,187
Group Population
28,578
29,406
30,242
Household Population
1,390,791
1,463,944
1,540,945
Average Household Size
2.96
2.93
2.89
Number of Households
469,299
499,922
532,543
Source: U.S. Census Bureau (2000 and 2010 Census)
As indicated in TABEL 3B, below, some large assumptions were made in order to project 2020 conditions. The 2020 projections assume the total housing units to be the same as 2010 and the occupied housing units to be the same as the total. This means that the vacancy rate for 2020 is zero.
21 | P a g e
TABLE 3B: Housing Demand Projection
Category
2000 Census
2010 Census
2020 Projection
Total Housing Units
522,323
569,985
569,985
Occupied Housing
469,299
499,922
569,985
Vacant Units
53,024
70,063
0
Vacancy Rate
0.10
0.12
0.00
Source: U.S. Census Bureau (2000 and 2010 Census)
With these assumptions, this model predicted 569,985 total housing units in 2020 for only 532,543 households, a ratio of 1.07 housing units for every one household. This analysis was expanded on, however, to account for additional factors that might have an impact on housing demand. TABLE 3C: 2020 Housing Demand Projection
Category Change in Number of Housing Units
Number 63,244
Change in # of Vacant Units
–53,024
Units That Must be Replaced
19,189
Units Lost to Disaster
2,612
Units Lost to Conversion
2,612
Units Lost to Demolition
13,966
Total Number of Units Needed 2000 to 2020
12,832
Housing Completion 2000–2010
31,774
Unmet Housing Demand 2011–2020
–18,942
TABLE 3C, above, displays the variables that were added to the model in order to produce are more accurate housing demand estimation. These variables include units lost to disaster, conversion, and demolition. These variables were used to estimate the number of units that would need to be replaced by 2020. The number of units lost to demolition was derived from a ratio based on actual figures for the entire country over the period of 2000 to 2010. This was done because of the lack of available data on a state or county level. The demolition data was available in three-‐year groups. In order to determine an estimate of housing demolitions for Suffolk County, the nationwide demolition numbers were broken down into single years by dividing each number for the three-‐year group by three. The number for 2010 was not available, so the 2009 number was used for that year. In order to derive Suffolk County estimates based on these numbers, a ratio was applied. This ratio was determined by dividing the total number of housing units in Suffolk County for the years 2000 and 2010 by the number of total housing units nationwide for those respective years. The average of those two ratios was
22 | P a g e
then multiplied by the number of nationwide demolitions year by year in order to estimate yearly demolitions in Suffolk County. These numbers can be seen in TABLE 4, below. TABLE 4: Annual Residential Demolitions In Suffolk County
Year
Residential Demolitions
2000
620
2001
562
2002
562
2003
587
2004
587
2005
935
2006
935
2007
723
2008
723
2009
723
2010
723
Source: U.S. Department of Housing and Urban Development. U.S. Census Bureau
Additional assumptions were made in order to determine the number of units lost to disaster and conversion. Given the relatively stable nature of housing in Suffolk County as well as the lack of many significant natural disasters, this number was assumed to be very small. Both these numbers were determined by taking 0.05% of the total housing units in 2000. The units lost to disaster, conversions, and demolitions increased the demand figure by 19,189 units. Subtracting the number of projected vacant units in 2020 from the number of vacant units in 2000 provided an estimated change in vacant units. Combining the number of units lost with the change in vacant units and the projected change in the number of households provides an estimate of the total number of housing units needed for 2000 to 2020 (12,832 units). TABLE 5, below, displays the number of building permits for Suffolk County, by year, from 2000 to 2010. This data, in conjunction with two ratios provided by the U.S. Census Bureau (starts-‐to-‐permit ratio and completion-‐to-‐start ratio), was used to estimate the number of completions during this same period. Taking the difference of the number of housing units needed with the number of housing completions provided an estimate of the unmet housing demand between 2000 and 2020. As seen in TABLE 3C, this model shows Suffolk County to have an overabundance of housing compared to projected need by 18,942 units.
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As was the case with the cohort component model, significant assumptions were required in this analysis. Most significant is the assumption of zero vacancies in 2020. This seemed to have a large effect on the estimates of future need. TABLE 5: Suffolk County Annual Residential Building Permits and Estimated Completion by Housing Type (2000-2010)
Building Permits Year
Number of Permits
1-Family
2-Family
2000
4,932
3,910
234
3- & 4Family 126
2001
4,680
3,488
190
104
898
2002
4,384
3,481
204
109
590
2003
3,204
2,636
238
114
216
2004
3,397
2,940
230
98
129
2005
5,183
4,241
2
0
940
2006
2,573
2,410
4
6
153
2007
2,126
2,030
6
33
57
2008
1,396
972
0
0
424
2009
990
791
0
0
199
2010
971
910
0
0
61
33,836
27,809
1,108
590
4,329
Number of Permits 27,809
Start to Permit Ratio 1.023
Completion to Start Ratio 0.965
Number of Completion 27,452.90576
Multi Family
6,027
0.775
0.925
Total
33,836
Totals
Building Type Single Family
5+ Family 662
4,321 31,774
Source: U.S. Census Bureau
CONCLUSION If the housing projection model properly reflects reality, then there is an overabundance of housing in Suffolk County relative to future need. Whether this is an accurate number or not belies the more important discussion relating to the future of Suffolk County. That is, not whether there is enough housing but rather whether there is enough affordable, accessible, and desirable housing to meet future demand. The age–sex pyramids show a loss of population in the young-‐adult cohort (25–45). Aging population is a major concern among planners and politicians in Suffolk County. The challenge the planners and politicians have is to determine what the future of development in the county will look like. Will development continue in the pattern established after
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WWII until all available land is built out? Or will politicians and residents embrace new patterns of development that not only address the significant land and resource constraints but also properly adhere to future demand? All the models discussed in this report project continued population growth in Suffolk County. These models, however, cannot properly account for resource and land constraints or changing preferences, both economic and social. Because of this, planners in the county and towns within it must properly and proactively address questions about the nature of future development. Recently, many Suffolk County towns and communities have taken steps in this direction, focusing on revitalizing downtowns and building around existing infrastructure. In December of 2011, Long Island received a $101.6 million grant from New York State for 60 existing initiatives that focus on smart growth.xv Many of these projects, including the Ronkonkoma HUB project,xvi represent efforts by local planning officials to address development concerns by working with developers on finding profitable and responsible methods for future growth. Forward thinking and cooperative efforts such as this represent the only viable path forward to ensure continued growth in Suffolk County.
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APPENDIX 1: AGE-‐SEX PYRAMIDS
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APPENDIX 2: TREND EXTRAPOLATION MODELS
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WORKS CITED Suffolk County Executive’s Office. (2011). History of Suffolk County . Retrieved from http://www.suffolkcountyny.gov/Departments/CountyExecutive/HistoryofSuffolk County.aspx United States Census Bureau. (2011). The Older Population: 2010. Retrieved from http://www.census.gov/prod/cen2010/briefs/c2010br-‐09.pdf Suffolk County Planning Department (2000). Smart Communities Through Smart Growth. Retrieved from http://suffolkcountyny.gov/Portals/0/planning/Publications/SG032000.pdf Washington Post. (2011) Highest Income Counties in 2011. Retrieved from http://www.washingtonpost.com/wp-‐srv/special/local/highest-‐income-‐counties/ Long Island Index (2011). 2011 Profile Report.Retrieved from http://www.longislandindex.org/fileadmin/Reports_and_Maps/2012_Reports/LI% 20Profile%202012.pdf New York Times. (2011) Long Island Gets Big Grant in Cuomo’s Competition. Retrieved from http://www.nytimes.com/2011/12/09/nyregion/cuomos-‐regional-‐development-‐ competition-‐awards-‐grants.html?_r=0
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ENDNOTES i
Suffolk County Executive’s Office. (2012). History of Suffolk County. Retrieved from http://www.suffolkcountyny.gov/Departments/CountyExecutive/HistoryofSuffolkCounty.aspx ii Suffolk County Executive’s Office iii Suffolk County Executive’s Office iv Suffolk County Executive’s Office v Suffolk County Executive’s Office vi United States Census Bureau (2011) The Older Population:2010. p. 4. Retrieved from http://www.census.gov/prod/cen2010/briefs/c2010br-‐09.pdf vii Suffolk County Planning Department (2000). Smart Communities Through Smart Growth. p. i. Retrieved from http://suffolkcountyny.gov/Portals/0/planning/Publications/SG032000.pdf viii Suffolk County Planning Department: p. 1 ix Suffolk County Planning Department: p. 2 x Washington Post. (2011). Highest Income Counties in 2011.Retrieved from http://www.washingtonpost.com/wp-‐ srv/special/local/highest-‐income-‐counties/ xi American Fact Finder (2012). xii Long Island Index. (2012). 2012 Profile Report.p. 5. Retrieved from http://www.longislandindex.org/fileadmin/Reports_and_Maps/2012_Reports/LI%20Profile%202012.pdf xiii Long Island Index. p. 9 xiv Long Island Index. p. 7 xv New York Times (2011).Long Island Gets Big Grant in Cuomo’s Competition. Retreived from http://www.nytimes.com/2011/12/09/nyregion/cuomos-‐regional-‐development-‐competition-‐awards-‐ grants.html?_r=0 xvi Town of Brookhaven. (2012) Retrieved from http://www.brookhaven.org/Departments/PlanningEnvironment/Planning/RonkonkomaHub.aspx
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