population projection and housing demand

Population Projection and Housing Demand Methods II

Daniel Turner

34 S. 4th Avenue

Highland Park, NJ 08904

[email protected]

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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 1930s, the primary industries of Suffolk County were farming, fishing and shipbuilding.iii In the 1930s, 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 Change Year Population Number Percent 1790 16,400 N/A N/A 1800 19,735 3,335 20.335% 1810 21,113 1,378 6.983% 1820 23,936 2,823 13.371% 1830 26,780 2,844 11.882% 1840 32,469 5,689 21.243% 1850 36,922 4,453 13.715% 1860 43,275 6,353 17.207% 1870 46,924 3,649 8.432% 1880 52,888 5,964 12.710% 1890 62,491 9,603 18.157% 1900 77,582 15,091 24.149% 1910 96,138 18,556 23.918% 1920 110,246 14,108 14.675% 1930 161,055 50,809 46.087% 1940 197,355 36,300 22.539% 1950 276,129 78,774 39.915% 1960 666,784 390,655 141.476% 1970 1,124,950 458,166 68.713% 1980 1,284,231 159,281 14.159% 1990 1,321,864 37,633 2.930% 2000 1,419,369 97,505 7.376% 2010 1,493,350 73,981 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. AGESEX PYRAMIDS The following AgeSex 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 AgeSex Pyramids for the years 1950, 1970, and 2000, along with analyses of their significance. (APPENDIX 1 contains AgeSex Pyramids for all years from 1940 to 2010, with the exception of 1960 because of the lack of data).

1950 Population The AgeSex 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 AgeSex Pyramid offers insight into the nature of this growth.

1970 Population Between 1950 and 1970, Suffolk Countys 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 AgeSex 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 AgeSex 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 Countys 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

Year Actual Population Linear Exponential Logarithmic Polynomial Power

Moving Average

Log Modified Exponential

1940 197,355 215,589 253,829 212,084 80,597 177,221 - -32,075 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% 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 modelspolynomial, moving average, and log-modified exponentialall 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 agesex cohorts (similar to the AgeSex 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. Agesex 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. 2The 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 agesex cohort for 1990. This rate was derived from taking the inverse of the death rate data released by the Centers for Disease Control for 19891991. 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 agesex 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 19891991 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 agesex 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 its known, for each agesex 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 agesex 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 agesex pyramid for the actual 2010 population of Suffolk County is shown below in FIGURE 13.

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A comparison of the two agesex 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

Source: http://www.suffolkcountyny.gov/Departments/Planning/Divisions/CartographyandGIS.aspx 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.

0 6 12 18 24

Miles

1 in = 12.09 milesN

LONG ISLANDNew York

Huntington

NASSAUCOUNTY

Babylon

SmithtownBrookhaven

Riverhead

Southampton

Southold

EastHampton

ShelterIsland

ATLANTICOCEAN

Long Island Sound

CONNECTICUT

Prepared by Suffolk County Department of Planning, January 27, 2010.

Islip

SUFFOLK COUNTY

QUEENS

BROOKLYN

BRONX

MANHATTAN

STATENISLAND

OysterBay

NorthHempstead

Hempstead

NEWYORK

NEWJERSEY

Suffolk County, Nassau County & the 5 Boroughs Region

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FIGURE 15: Suffolk County Towns and Incorporated Villages

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

Source: http://www.suffolkcountyny.gov/Departments/Planning/Divisions/CartographyandGIS.aspx 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.

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Greenport

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Grove

Headof the

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Sag Harbor

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Amityville

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Cranberry Ho

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Hubbard Ave

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Robert Moses State Pkwy

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N Ferr y Rd

Lakeland Ave

Reeves Ave

Old Country R

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Riverhead-Hampton Bays Rd

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W Jericho Tpke

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Neck

Ln

Bay Ave

Cedar Point Rd

Hallock Ave

Church St

Speo

nk R

iverhe

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County Rd 39A

N Bayview Rd

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Conklin St

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N Wellwood Ave

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Woods Ln

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of P

ond

Rd

Patchog

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Red Creek Rd

State Hwy 25

Old Montauk Hwy

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Jericho Tpke

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W Jericho Tpke

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N Ferry Rd

Route 2

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Ve terans Memorial Hwy

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Mill Ln

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SouthsideHospital

BrunswickHospital

HuntingtonHospital

SouthamptonHospital

St. CharlesHospital

St. Catherineof Siena

GoodSamaritanHospital

Veterans AdministrationMedical Center

Central SuffolkHospital

PilgrimPsychiatric

Center

Eastern LongIsland Hospital

University Hospitalat Stony Brook

John T. MatherMemorial Hospital

Kings ParkPsychiatric Center

Sagamore Children'sPsychiatric Center

Central IslipPsychiatric Center

BrookhavenMemorial Hospital

MONTAUKAIRPORT

SPADAROAIRFIELD

REPUBLICAIRPORT

MATTITUCKAIRPORT

CALVERTONAIRPORT

BAYPORTAERODROME

ELIZABETHAIRPORT

EAST HAMPTONAIRPORT

BROOKHAVENCALABRO AIRPORT

FRANCIS S. GABRESKIAIRPORT

LONG ISLAND ISLIPMacARTHUR AIRPORT

SCCCAmmerman CampusSCCC

Grant Campus

SCCCSayville Downtown Center

SCCCEastern Campus

SCCCCulinary Arts Program

Calverton

Ridge

Manorville

Coram

Montauk

Shirley

DixHills

Melville

Riverhead

Yaphank

FlandersMedford

Southold

Commack

Springs

Islip

Smithtown

Noyack

Brentwood

NorthSea

Bohemia

Cutchogue

WaterMill

Hauppauge

RockyPoint

Westhampton

Bridgehampton

Mattituck

Northampton

Centereach

NorthwestHarbor

Fort Salonga

Orient

Holtsville

Holbrook

Northville

HamptonBays

WadingRiver

Sayville

Wainscott

Selden

Huntington

EastQuogue

Elwood

WestIslip

Eastport

MiddleIsland

DeerPark

Ronkonkoma

Mastic

CentralIslip

WestBabylon

Amagansett

EastPatchogue

MillerPlace

Kings Park

BayShore

St. James

Peconic

Brookhaven

Stony Brook ShelterIsland

Jamesport

Bayport

WestHills

Laurel

MountSinai

Gilgo

Tuckahoe

Nesconset

EastIslip

Wyandanch

EastMoriches

Napeague

Greenlawn

Aquebogue

EastShoreham

Terryville

GreatRiver

Farmingville

NorthBellport

EastNorthport

CenterMoriches

EastFarmingdale

Riverside

Copiague

GardinersIsland

FishersIsland

HuntingtonStation

Baywood

BrookhavenNational

Laboratory

Moriches

NorthBabylon

Baiting Hollow

SouthHuntington

NorthBay Shore

EastMarion

Shinnecock Hills

Quiogue

NorthAmityville

SoundBeach

North Patchogue

WestSayville

IslipTerrace

Wheatley Heights

Setauket-East Setauket

EastHampton

North

LakeRonkonkoma

ShelterIsland

Heights

Fire Island

GreenportWest

Centerport

ColdSpringHarbor

Remsenburg-Speonk

BluePoint

WestBay

Shore

Port JeffersonStation

NorthGreatRiver

Halesite

GordonHeights

PlumIsland

NorthLindenhurst

StonyBrook

University

EatonsNeck

ShinneockReservation

Hampton Bays

RobinsIsland

Oakdale

NewSuffolk

Oak Beach-Captree

PoospatuckReservation

495 EASTHAMPTON

SHELTERISLAND

ATLANTIC OCEAN

Long Island Sound GardinersBay

Great PeconicBay

Great SouthBay

GENERAL

o

0 3 6 9 12Miles

SOUTHAMPTON

SOUTHOLD

SmithtownBay

BROOKHAVEN

SMITHTOWN

ISLIP

HUNTINGTON

BABYLON

SUFFOLK COUNTY, NEW YORK

NASSAUCOUNTY

Block IslandSound

December 19, 2011 - CD-11-18

RIVERHEAD

Map is subject to revision. This map is not to be used for surveying, conveyance of land, or other precise purposes.Source: Suffolk County Department of Planning, Division of Cartography; NYS Office of Cyber Security & Critical Infrastructure Coordination.

ConnecticutNewYork

NewJersey

SuffolkCtyNassau

CtyAtlanticOcean

Long IslandSound

Legend

HospitalAirportMajor Road

County RoadInterstate HighwayLong Island Rail RoadTown BoundaryVillage

l

o

oH. Lee Dennison

Building

NorthCounty

Complex

o

o

YaphankCountyCenter

RiverheadCountyCenter

o Suffolk County CenterSuffolk County Community Collegek

RobinsIs

PlumIs

GardinersIs

Sunrise Hwy

EASTHAMPTON

SHELTERISLAND

ATLANTIC OCEAN


Great PeconicBay

Great SouthBay

L AND USE, 2007

o

0 3 6 9 12Miles

SOUTHAMPTON

SOUTHOLD

SmithtownBay

BROOKHAVEN

SMITHTOWN

ISLIP

HUNTINGTON

BABYLON


NASSAUCOUNTY

Block IslandSound

January 6, 2012 - CD-11-18

RIVERHEAD

Map is subject to revision. This map is not to be used for surveying, conveyance of land, or other precise purposes.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.

LegendLand Use

Low Density Residential

Medium Density Residential

High Density Residential

Commercial

Industrial

Institutional

Recreation & Open Space

Agricultural

Vacant

Transportation

Utilities

Wast Handling & Management

Underwater Land

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FIGURE 17: 2010 Suffolk County Population Density

Source: http://www.suffolkcountyny.gov/Departments/Planning/Divisions/CartographyandGIS.aspx

FIGURE 18: 20002010 Suffolk County Population Change

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.

Gilgo

FireIsland

BrookhavenNational

Laboratory

NorthAmityville

GardinersIs

PlumIs

State Hwy 27

I 495

Main Rd

Route

112

Sound Ave

Dune Rd

Montauk Hwy

River Rd

Nesconse

t Hwy

R oute

25

Islip

Ave

Noyac Rd

Route 109

Route 25A

W hiskey Rd

Meadow Ln

Granny Rd

Broa

dholl

o w R

d

Sagg

Rd

Osborn Ave

W Neck Rd

Edwa

rds A

ve

N Co

untry R d

F landers Rd

Peconic Bay B

lvd

Broa

dway

Town Ln

Hill St

Oregon

Rd

Accabo

nac Rd

New

York

Ave

Dee r

Par

k Rd

Scuttle

Hole R

d

E Lake Dr

Manor Ln

Cox Ln

Dunes Rd

Ocea

n Rd

Soun

dview

Ave

Sag H arbor Tpke

Noyac

k Rd

Smithtown

Byp

Ferry Rd

Deer

Par

k Ave

Lewis Rd

Old S

tone

Hwy

Nugen t Dr

Roanoke Ave

Doctors Path


Bridge Ln

Moun

t Sina

i Cora

m Rd

Herricks Ln

P leas

u re D

r

Wood

bury R

d

Sebonac Rd

Wad

ing R

iver R

d

Jericho Tpke

Schu

ltz R

d

Swan Pond Rd

Medfo

rd A

ve

Lloyd Ha rbor Rd

Fort S alonga Rd

Sunrise Hwy

Old Dock

Rd

Lyn

n A

ve

Haup

paug

e Rd

Water Mill Towd Rd


Buckskill Rd

Main Bayview Rd

Walt W

hitma

n Rd

Mill Ln

Stat e

Hwy

231

Cranberry Ho

le Rd

Hubbard Ave

Mille

r Plac

e Rd

S Ferry Rd

Fresh Pond Ave


Nassau Point Rd

N Magee St

N Ferr y Rd

Lakeland Ave

Reeves Ave

Old Country R

d

W B

artle

tt Rd

Sagap

onac

k Main

St

Josh

uas P

ath

Springy Banks Rd

Sprin

gs Fi

replac

e Rd

Beach Rd

North RdE Shore Rd

Qu o g ue S t

Narrow

Rive

r Rd

Three

Mile

Harb

or HC R

d

Brick

Kiln

Rd

Cedar St

Halse

y Nec

k Ln

Hampton

Rd

Ponquogue Ave


Front St

W Jericho Tpke

First

Neck

Ln

Bay Ave

Cedar Point Rd

Hallock Ave

Church St

Speo

nk R

iverhe

ad R

d

Brander Pkwy

Canal Rd

Merrick Rd

County Rd 39A

N Bayview Rd

Nostrand Pkwy

Conklin St

Jess

up L

n

N Oc

ean A

ve

Mill Rd

Stony Hill Rd

Mena

ntic R

d

Old Town Rd

N Wellwood Ave

Fulton St

Woods Ln

Head

of P

ond

Rd

Patchog

ue Yaph

ank Rd

Red Creek Rd

State Hwy 25

Old Montauk Hwy

Nesconset H

wy

Main Rd

E Main St

Jericho Tpke

Main St

E M

ain S

t

O ld Montauk Hwy

E Main St

Route 112

W Jericho Tpke

Montauk Hwy

Montauk Hwy

Noyack

Rd

State Hwy 27

Main StMain

Rd

Montauk Hwy

Sound Ave

Main St

Old Country Rd

E Main St

N Ferry Rd

Main StRoute

25A


Main St

Route 25A

Canal Rd

Mill Ln

Calverton

Manorville

Montauk

Yaphank

Riverhead

Flanders

Southold

Springs

Noyack

NorthSea

WaterMill

Mattituck

Westhampton

Cutchogue

Bridgehampton

Northampton

NorthwestHarbor

WadingRiver

Orient

Northville

LLOYD

HARBOR

Wainscott

East QuogueEastport

Amagansett

Brookhaven

Laurel

Jamesport

QUOGUE

Peconic

EastMoriches

GreatRiver

Aquebogue

NISSEQUOGUE

Baiting Hollow

FireIsland

SOUTHAMPTON

ShelterIsland

TuckahoeSAGAPONACK

Napeague

EAST HAMPTON

FishersIsland

EastHampton

North

ShelterIsland

Heights

OLDFIELD

GreenportWest

NORTHHAVEN

EastMarion

Remsenburg-Speonk

ShinnecockHills

Quiogue

HEADOF THEHARBOR

ASHAROKEN

WESTHAMPTONBEACH

BELLETERRE


Oak Beach-Captree

NewSuffolk

SALTAIRE

DERINGHARBOR

WEST HAMPTON

DUNES

OCEAN

BEACH

RidgeDix HillsMelville

Bohemia

Hauppauge

Rocky Point

Fort Salonga

HamptonBays

MiddleIsland

MillerPlace

West Hills

EastShoreham

ISLANDIA


EastFarmingdale

CenterMoriches

Riverside

Moriches

ColdSpringHarbor

BELLPORT

SAG HARBOR

North Great River

EatonsNeck

HUNTINGTONBAY

VILLAGEOF THEBRANCH

SHOREHAM

Coram

Shirley

Medford

Smithtown

Holtsville

Huntington

Elwood

Ronkonkoma

KingsPark

EastPatchogue

St. JamesStony Brook

MountSinai

Bayport

Wyandanch

OakdaleNorth

Bellport

South Huntington

MasticBeach

PORTJEFFERSON

Centerport

BluePoint

WestBay Shore


WestSayville

Halesite

GordonHeights

GREENPORT

POQUOTT


Commack

Islip

Centereach

Holbrook

SayvilleMastic

EastIslip

Nesconset

Greenlawn

EastNorthport

Terryville

Farmingville

Baywood

LAKEGROVE

NORTHPORT

NorthPatchogue

BRIGHTWATERS

Wheatley Heights

Selden

WestIslip

DeerPark Central

Islip

BayShore

BABYLON

LakeRonkonkoma

AMITYVILLE

SoundBeach

Islip Terrace

Brentwood

WestBabylon

NorthBabylon

PATCHOGUE

NorthBay

Shore

StonyBrook

UniversityHuntingtonStation

NorthLindenhurst

LINDENHURST

Copiague

EASTHAMPTON

SHELTERISLAND

ATLANTIC OCEAN


Great PeconicBay

Great SouthBay

POPUL ATION DENSITY BYCENSUS DESIGNATED PL ACE, 2010

o

0 3 6 9 12Miles

SOUTHAMPTON

SOUTHOLD

Legend

Census Designated Places, 2010Persons per sqmi

1,0001,001 - 2,0002,001 - 3,000

3,001 - 4,0004,001 - 5,0005,001 - 6,0006,001 - 7,000> 7,000SmithtownBay

BROOKHAVEN

SMITHTOWN

ISLIP

HUNTINGTON

BABYLON


NASSAUCOUNTY

Block IslandSound

December 5, 2011 - CD-11-18

RIVERHEAD

Map is subject to revision. This map is not to be used for surveying, conveyance of land, or other precise purposes.Source: Suffolk County Department of Planning, Division of Cartography; US Census Bureau; NYS Office of Cyber Security & Critical Infrastructure Coordination.

Gilgo

FireIsland

BrookhavenNationalLaboratory

NorthAmityville

PlumIs

GardinersIs

State Hwy 27

I 495

Main Rd

Route

112

Sound Ave

Dune Rd

Montauk Hwy

River Rd

Nesconse

t Hwy

R oute

25

Islip

Ave

Noyac Rd

Route 109

Route 25A

W hiskey Rd

Meadow Ln

Granny Rd

Broa

dholl

o w R

d

Sagg

Rd

Osborn Ave

W Neck Rd

Edwa

rds A

ve

N Co

untry R d

F landers Rd

Peconic Bay B

lvd

Broa

dway

Town Ln

Hill St

Oregon

Rd

Accabo

nac Rd

New

York

Ave

Dee r

Par

k Rd

Scuttle

Hole R

d

E Lake Dr

Manor Ln

Cox Ln

Dunes Rd

Ocea

n Rd

Soun

dview

Ave

Sag H arbor Tpke

Noyac

k Rd

Smithtown

Byp

Ferry Rd

Deer

Par

k Ave

Lewis Rd

Old S

tone

Hwy

Nugen t Dr

Roanoke Ave

Doctors Path


Bridge Ln

Moun

t Sina

i Cora

m Rd

Herricks Ln

P leas

u re D

r

Wood

bury R

d

Sebonac Rd

Wad

ing R

iver R

d

Jericho Tpke

Schu

ltz R

d

Swan Pond Rd

Medfo

rd A

ve

Lloyd Ha rbor Rd

Fort S alonga Rd

Sunrise Hwy

Old Dock

Rd

Lyn

n A

ve

Haup

paug

e Rd

Water Mill Towd Rd


Buckskill Rd

Main Bayview Rd

Walt W

hitma

n Rd

Mill Ln

Stat e

Hwy

231

Cranberry Ho

le Rd

Hubbard Ave

Mille

r Plac

e Rd

S Ferry Rd

Fresh Pond Ave


Nassau Point Rd

N Magee St

N Ferr y Rd

Lakeland Ave

Reeves Ave

Old Country R

d

W B

artle

tt Rd

Sagap

onac

k Main

St

Josh

uas P

ath

Springy Banks Rd

Sprin

gs Fi

replac

e Rd

Beach Rd

North RdE Shore Rd

Qu o g ue S t

Narrow

Rive

r Rd

Three

Mile

Harb

or HC R

d

Brick

Kiln

Rd

Cedar St

Halse

y Nec

k Ln

Hampton

Rd

Ponquogue Ave


Front St

W Jericho Tpke

First

Neck

Ln

Bay Ave

Cedar Point Rd

Hallock Ave

Church St

Speo

nk R

iverhe

ad R

d

Brander Pkwy

Canal Rd

Merrick Rd

County Rd 39A

N Bayview Rd

Nostrand Pkwy

Conklin St

Jess

up L

n

N Oc

ean A

ve

Mill Rd

Stony Hill Rd

Mena

ntic R

d

Old Town Rd

N Wellwood Ave

Fulton St

Woods Ln

Head

of P

ond

Rd

Patchog

ue Yaph

ank Rd

Red Creek Rd

State Hwy 25

Old Montauk Hwy

Nesconset H

wy

Main Rd

E Main St

Jericho Tpke

Main St

E M

ain S

t

O ld Montauk Hwy

E Main St

Route 112

W Jericho Tpke

Montauk Hwy

Montauk Hwy

Noyack

Rd

State Hwy 27

Main StMain

Rd

Montauk Hwy

Sound Ave

Main St

Old Country Rd

E Main St

N Ferry Rd

Main StRoute

25A


Main St

Route 25A

Canal Rd

Mill Ln

Calverton

Manorville

Montauk

Yaphank

Riverhead

Flanders

Southold

Springs

Noyack

NorthSea

WaterMill

Mattituck

Westhampton

Cutchogue

Bridgehampton

Northampton

NorthwestHarbor

WadingRiver

Orient

Northville

LLOYD

HARBOR

Wainscott

East QuogueEastport

Amagansett

Brookhaven

Laurel

Jamesport

QUOGUE

PECONIC

EastMoriches

GreatRiver

Aquebogue

NISSEQUOGUE

Baiting Hollow

FireIsland

SOUTHAMPTON

ShelterIsland

TuckahoeSAGAPONACK

Napeague

EAST HAMPTON

FishersIsland

EastHampton

North

ShelterIsland

Heights

OLDFIELD

GreenportWest

NORTHHAVEN

EastMarion

Remsenburg-Speonk

ShinnecockHills

Quiogue

HEADOF THEHARBOR

ASHAROKEN

WESTHAMPTONBEACH

BELLETERRE


Oak Beach-Captree

NewSuffolk

SALTAIRE

DERINGHARBOR

WEST HAMPTON

DUNES

OCEAN

BEACH

RidgeDix HillsMelville

Bohemia

Hauppauge

Rocky Point

Fort Salonga

HamptonBays

MiddleIsland

MillerPlace

West Hills

EastShoreham

ISLANDIA


EastFarmingdale

CenterMoriches

Riverside

Moriches

ColdSpringHarbor

BELLPORT

SAG HARBOR

North Great River

EatonsNeck

HUNTINGTONBAY

VILLAGEOF THEBRANCH

SHOREHAM

Coram

Shirley

Medford

Smithtown

Holtsville

Huntington

Elwood

Ronkonkoma

KingsPark

EastPatchogue

St. JamesStony Brook

MountSinai

Bayport

Wyandanch

OakdaleNorth

Bellport

South Huntington

MasticBeach

PORTJEFFERSON

Centerport

BluePoint

WestBay Shore


WestSayville

Halesite

GordonHeights

GREENPORT

POQUOTT


Commack

Islip

Centereach

Holbrook

SayvilleMastic

EastIslip

Nesconset

Greenlawn

EastNorthport

Terryville

Farmingville

Baywood

LAKEGROVE

NORTHPORT

NorthPatchogue

BRIGHTWATERS

Wheatley Heights

Selden

WestIslip

DeerPark Central

Islip

BayShore

BABYLON

LakeRonkonkoma

AMITYVILLE

SoundBeach

Islip Terrace

Brentwood

WestBabylon

NorthBabylon

PATCHOGUE

NorthBay

Shore

StonyBrook

UniversityHuntingtonStation

NorthLindenhurst

LINDENHURST

Copiague

EASTHAMPTON

SHELTERISLAND

ATLANTIC OCEAN


Great PeconicBay

Great SouthBay

PERCENT POPULATION CHANGE BY CENSUS DESIGNATED PLACE, 2000-2010**

o

0 3 6 9 12Miles

SOUTHAMPTON

SOUTHOLD

SmithtownBay

BROOKHAVEN

SMITHTOWN

ISLIP

HUNTINGTON

BABYLON


NASSAUCOUNTY

Block IslandSound

December 5, 2011 - CD-11-18

RIVERHEAD

Map is subject to revision. This map is not to be used for surveying, conveyance of land, or other precise purposes.Source: Suffolk County Department of Planning, Division of Cartography; US Census Bureau; NYS Office of Cyber Security & Critical Infrastructure Coordination.

LegendPopulation Change: 2000-2010

Percent Change

>-35%-24.9 - -35%-14.9 - -25%-4.9 - -15%-5 - 5%

5.1 - 15%15.1 - 25%25.1 - 35%> 35%No Data*

*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.

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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.

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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 Number Change in Number of Housing Units 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 20002010 31,774 Unmet Housing Demand 20112020 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

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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 3- & 4- Family 5+ Family

2000 4,932 3,910 234 126 662 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

Totals 33,836 27,809 1,108 590 4,329

Building Type Number of Permits

Start to Permit Ratio

Completion to Start Ratio

Number of Completion

Single Family 27,809 1.023 0.965 27,452.90576 Multi Family 6,027 0.775 0.925 4,321

Total 33,836 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 agesex pyramids show a loss of population in the young-adult cohort (2545). 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

25 | P a g e

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 Executives Office. (2011). History of Suffolk County . Retrieved from http://www.suffolkcountyny.gov/Departments/CountyExecutive/HistoryofSuffolkCounty.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 Cuomos 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 iSuffolk County Executives Office. (2012). History of Suffolk County. Retrieved from http://www.suffolkcountyny.gov/Departments/CountyExecutive/HistoryofSuffolkCounty.aspx ii Suffolk County Executives Office iii Suffolk County Executives Office iv Suffolk County Executives Office v Suffolk County Executives 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/ xiAmerican Fact Finder (2012). xiiLong Island Index. (2012). 2012 Profile Report.p. 5. Retrieved from http://www.longislandindex.org/fileadmin/Reports_and_Maps/2012_Reports/LI%20Profile%202012.pdf xiiiLong Island Index. p. 9 xivLong Island Index. p. 7 xvNew York Times (2011).Long Island Gets Big Grant in Cuomos Competition. Retreived from http://www.nytimes.com/2011/12/09/nyregion/cuomos-regional-development-competition-awards-grants.html?_r=0 xviTown of Brookhaven. (2012) Retrieved from http://www.brookhaven.org/Departments/PlanningEnvironment/Planning/RonkonkomaHub.aspx

population projection and housing demand

Documents

population of suffolk

suffolk county population

easternmost county

population projection

following agesex pyramids

historical data

demographic changes

time period