Citation
Visualizing Incremental Growth with Dynamic Suitability Modeling

Material Information

Title:
Visualizing Incremental Growth with Dynamic Suitability Modeling : Alachua County's Growth with the Addition of Plum Creek's Sector Plan
Creator:
Deledda, Max
Place of Publication:
(Gainesville, FL)
Publisher:
University of Florida
Publication Date:
Language:
English
Physical Description:
1 online resource; 152p

Thesis/Dissertation Information

Degree:
Master's ( Master of Landscape Architecture (M))
Degree Grantor:
University of Florida
Committee Chair:
Carr, Margaret H
Committee Members:
Hoctor, Thomas Scott

Subjects

Subjects / Keywords:
Alachua County ( local )
Land development ( jstor )
Plums ( jstor )
Area development ( jstor )
Spatial Coverage:
Florida -- Alachua County -- Plum Creek

Notes

Abstract:
This project contains two major comparisons: 1) Incremental growth projections based on development suitability using static and dynamic methods of population allocation, and 2) comparison between projected future development for Alachua County with and without the inclusion of Plum Creek’s Envision Alachua Sector Plan. Both of these comparisons relate to the question of how proximity to existing or proposed development can alter the outcomes of future land use modeling, with a focused interest on how land adjacent to Plum Creek’s Envision Alachua Sector Plan will be influenced by changes in development suitability with and without the sector plan implementation. Four case studies have been selected that share characteristics with Plum Creek’s Envision Alachua Sector Plan. The case studies indicate that Plum Creek’s Envision Alachua Sector Plan must attract residents from further than Alachua County for sustainable growth. ( ,, )
Abstract:
Future land use modeling, as well as analysis of the case studies, was performed with ArcGIS software. M. Carr and P. Zwick’s book, Smart land-use analysis: The LUCIS model land-use conflict identification strategy, informs much of the methodology of this project; particularly the analysis of development suitability and population allocation. Incremental adjustment of development suitability during the future land use modeling results in the location of future development closer to previous development. While this result was expected, the application of this dynamic suitability method did not greatly increase the future development projections for the area in and around Plum Creek’s proposed sector plan development. This study concludes that the reason for this is the inherent lack of physical suitability of the Plum Creek land and environs for development.
Abstract:
Recommendations for future study include: 1) alternative proposals for Plum Creek’s Alachua County land holdings, 2) analysis that incorporates specific area plans that are not available at this point in Plum Creek’s Sector Plan application such as economic or political drivers, and 3) the paradox of sector plans in they purport to be environmentally friendly, but are almost always located on lands with significant natural resource value.
General Note:
Landscape Architecture terminal project
Statement of Responsibility:
by Max Deledda

Record Information

Source Institution:
University of Florida
Holding Location:
University of Florida
Rights Management:
Copyright Max Deledda. Permission granted to the University of Florida to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder.
Resource Identifier:
1022120884 ( OCLC )

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Visualizing Incremental Growth with Dynamic Suitability Modeling Alachua County’s Growth with the Addition of Plum Creek’s Sector Plan 6/26/2015 A Thesis Project Presented in Partial Fulfillment of the Requirements for t he Degree of Master of Landscape Architecture By Max Deledda Committee Margaret Carr Thomas Hoctor Kristin Larsen University of Florida School of Landscape Architecture and Planning March 2015

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ii List of Figures List of Figures ............................................................................................................................................... iv List of Tables ................................................................................................................................................ iv List of Charts ................................................................................................................................................. v Abstract ......................................................................................................................................................... 1 Chapter 1 I ntroduction ............................................................................................................................... 2 Hypothesis ................................................................................................................................................. 2 Study Area ................................................................................................................................................. 2 Methods .................................................................................................................................................... 3 Limitations ................................................................................................................................................ 4 Chapter 2 Literat ure Review ....................................................................................................................... 5 Planning in Florida: Sector Plans, DRIs and Comprehensive Plans ........................................................... 5 Sprawl ....................................................................................................................................................... 7 Literature Related to Methodology .......................................................................................................... 8 Chapter 3 – Plum Creek’s Envision Alachua Sector Plan ............................................................................. 13 Chapter 4 Methodology ............................................................................................................................ 15 Case Study Methodology ........................................................................................................................ 15 Land Use Modeling Methodology ........................................................................................................... 15 Criteria used to determine development suitability .............................................................................. 16 Identifying land proximal to developed land and the resulting suitability ......................................... 17 Identifying areas of high road density and resulting suitability .......................................................... 22 Identifying lands of approved DRIs and PUDs .................................................................................... 23 Identifyi ng areas without wetlands and the resulting suitability ....................................................... 23 Identifying lands proximal to major roads and the resulting suitability ............................................. 23 Identifying areas with well drained soil and the resulting suitability ................................................. 24 Identifying areas within urban service areas and the resulting suitability ......................................... 25 Identifying areas without flood hazards and the resulting suitability ................................................ 25 Identif ying lands with mild or moderate slopes and the resulting suitability .................................... 25 Combining Suitability .............................................................................................................................. 26 Population Allocation .............................................................................................................................. 27

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iii List of Figures Future Land Use Model One – Static Suitability Model ...................................................................... 29 F uture Land Use Model Two – Dynamic Suitability Model ................................................................. 29 Future Land Use Model Three – Dynamic Suitability Model with Plum Creek S ector Plan ................ 30 Future Land Use Model Four – Plum Creek at Fifty Percent Development ........................................ 35 Methods used to gather results .............................................................................................................. 36 Chapter 5 Case Studies and Plum Creek ................................................................................................... 38 Case Studies ............................................................................................................................................ 38 Celebration .......................................................................................................................................... 40 Nocatee ............................................................................................................................................... 44 Harmony .............................................................................................................................................. 48 The Villages ......................................................................................................................................... 52 Plum Creek’s Envision Alachua Sector Plan ............................................................................................ 56 Case Study Conclusions and Correlation to Plum Creek’s Sector Plan ................................................... 58 Chapter 6 Results ...................................................................................................................................... 59 Model 1, 2, and 3 Results ........................................................................................................................ 60 Model 4 Results ....................................................................................................................................... 67 Chapter 7 Discussion ................................................................................................................................. 69 Chapter 8 Conclusions .............................................................................................................................. 73 Study Area Specific Conclusions ............................................................................................................. 73 Conclusions That May be Applied Elsewhere ......................................................................................... 74 Process Rel ated Conclusions ................................................................................................................... 74 Future Study Recommendations ............................................................................................................ 75 Appendix 1 Developed and Undeveloped Land Category Assignment .................................................... 77 Appendix 2 Data Used .............................................................................................................................. 80 Appendix 3 Criterion Suitability and Resulting 2015 Overall Suitability ................................................... 82 Appendix 4 Population Growth Projections and Allocations .................................................................... 92 Appendix 5 Plum Creek Property and Proposed Sector Plan Land Use .................................................... 94 Appendix 6 Plum Creek Sector Plan Development Areas ......................................................................... 95 Appendix 7 Dynamic Suitability Criterion with Plum Creek Sector Plan ................................................... 96 Appendix 8 Model 1 Future Growth Projections .................................................................................... 104 Appendix 9 Model 2 Future Growth Projections .................................................................................... 109 Appendix 10 Model 3 Future Growth Projections .................................................................................. 114

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iv List of Figures Appendix 11 Overall Static Suitability and Overall Dynamic Suitability by Decade ................................ 119 Appendix 12 2060 Future Land Use Model 1 and Model 2 City Scale Maps .......................................... 127 Works Cited ............................................................................................................................................... 143 List Figure 1 Suitability Assignment Reclassify versus Slice .......................................................................... 20 Figure 2 Dy namic Suitability Process ........................................................................................................ 30 Figure 3 Model 1 ....................................................................................................................................... 33 Figure 4 Model 2 ....................................................................................................................................... 34 Figure 5 Model 3 ....................................................................................................................................... 35 Figure 6 Celebration Location Map ........................................................................................................... 41 Figure 7 Celebration Structures Built Over Time .................................................................................... 42 Figure 8 Nocatee Location Map ................................................................................................................ 45 Figure 9 Nocatee Structures Built Over Time ........................................................................................... 46 Figure 10 Harmony Location M ap ............................................................................................................ 49 Figure 11 Harmony Structures Built Over Time ........................................................................................ 50 Figure 12 The Villages Location Map ........................................................................................................ 53 Figure 13 The Villages Structures Built Over Time ................................................................................. 54 Figure 14 2060 Future Development Based on Static Suitability ............................................................. 61 Figure 15 2060 Future Development Based on Dynamic Suitability ........................................................ 62 Figure 16 2060 Future Development Based on Dynamic Suitabi lity With Plum Creek Sector Plan ......... 63 Figure 17 2060 Future Development Based on Static Suitability Focus on Plum Creek ......................... 64 Figure 18 2060 Future Development Based on Dynamic Suitability Focus on Plu m Creek .................... 65 Figure 19 2060 Future Development Based on Dynamic Suitability with Plum Creek Sector Plan Focus on Plum Creek ............................................................................................................................................. 66 Figure 20 Future Land Use Model Four – Plum Creek at Fifty Percent Development .............................. 68 Table 1 The growth of suburban areas in the US (Nicolaides & Wiese, 2006) ........................................... 8 Table 2 Criteria, Rationale and Analysis for Development ....................................................................... 17 Table 3 Soil Drainage Characteristics and Assigned Suitability Values ..................................................... 25 Table 4 Slope Values and Assigned Suitability .......................................................................................... 26 Table 5 Suitability Weights ....................................................................................................................... 27 Table 6 Population Projections and Required Land for Alachua County (Bureau of Economic and Business Research (BEBR), University of Florida, 2014) ............................................................................. 28 Table 7 Celebration DRI Facts ................................................................................................................... 40 Table 8 Ce lebration County Population Change Characteristics (Bureau of Economic and Business Research (BEBR), University of Florida, 2015) ............................................................................................ 40

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v List of Charts Table 9 Nocatee DRI Facts ........................................................................................................................ 44 Table 10 Nocatee County Population Change Characteristics (Bureau of Economic and Business Research (BEBR), University of Florida, 2015) ............................................................................................ 44 Table 11 Harmony DRI Facts ..................................................................................................................... 48 Table 12 Harmony County Population Change Characteristics .............................................................. 48 Table 13 The Villages DRI Facts ................................................................................................................. 52 Table 14 The Villages County Population Change Characteristics .......................................................... 52 Table 15 Plum Creek's Envision Alachua Sector Plan Facts ...................................................................... 56 Table 16 Plum Creek's Envision Alachua Sector Plan County Population Change Characteristics ......... 57 Table 17 Average Distance of Allocated Land to Previous Development ................................................. 60 Table 1 8 Future Developed Land In and Around Plum Creek ................................................................... 60 Table 19 Average Suitability Values of Future Developed Land ............................................................... 60 Table 20 Model 4 Statistics ....................................................................................................................... 67 Chart 1 Case Study Comparison of Scale .................................................................................................. 39 Chart 2 Case Study Regional Comparison of Structures Built Over Time ............................................... 39 Chart 3 Celebration Structures Built Over Time ..................................................................................... 43 Chart 4 Celebration Region Structures Built Over Time ......................................................................... 43 Chart 5 Nocatee Structures Built Over Time .......................................................................................... 47 Chart 6 Nocatee Region Structures Built Over Time .............................................................................. 47 Chart 7 Harmony S tructures Built Over Time ......................................................................................... 51 Chart 8 Harmony Region Structures Built Over Time ............................................................................. 51 Chart 9 The Villages Structures Built Over Time ..................................................................................... 55 Chart 10 The Villages Region Structures Built Over Time ....................................................................... 55 Chart 11 Plum Creek Structures Built Over Time .................................................................................... 57 Chart 12 Plum Creek Region Structures Built Over Time ....................................................................... 58

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1 Abstract Abstract T his project contains two major com parisons : 1) I ncremental growth projections based on development suitability using static and dynamic methods of population allocation , and 2) c omparison between projected future development for Alachua County with and without the inclusion of Plum Creek’s Envision Alachua Sector Plan. Both of these comparisons relate to the question of how proximity to existing or proposed development can alter the outco mes of future land use modeling, with a focused interest on how land adjacent to Plum Creek’s Envision A lachua Sector Plan will be influenced by changes in development suitability with and without the sector plan implementation. Four case studies have been selected that share characteristics with Plum Creek’s Envision Alachua Sector Plan. The case studies i ndicate that Plum Creek’s Envision Alachua Sector Plan must attract residents from further than Alachua County for sustainable growth. F uture land use modeling, as well as analysis of the case studies, was performed with Arc GIS software. M. Carr and P. Zw ick’s book, Smart landuse analysis: The LUCIS model landuse conflict identification strategy , informs much of the methodology of this project; particularly the analysis of development suitability and population allocation. Incremental adjustment of development suitability during the future land use modeling results in the location of future development closer to previous development. While this result was expected, the application of this dynamic suitability method did not greatly increase the future dev elopment projections for the area in and around Plum Creek’s proposed sector plan development . This study concludes that the reason for this is the inherent lack of physical suitability of the Plum Creek land and environs for development. Recommendations for future study include: 1) alternative proposals for Plum Creek’s Alachua County land holdings, 2) analysis that incorporates specific area plans that are not available at this point in Plum Creek’s Sector Plan application such as economic or political d rivers, and 3) the paradox of sector plans in they purport to be environmentally friendly, but are almost always located on lands with significant natural resource value .

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2 Chapter 1 Introduction Introduction Hypothesis There are many factors that determine the loc ation of development. Some factors are attributes of the p hysical characteristics of the land, such as ability of the site’s soil to drain water. Other factors are based on the surroundings of the developed parcel, such as distance to major roadways. One o f the most important factors when locating future development is the proximity to existing development (Carr & Zwick, 2007) . As a consequence, development may occur on a sub optimal site only because it is located near exist ing development. A proposed development in Alachua County , Florida, is the focus of this project and is used to test the hypothesis that new development may occur near existing development despite factors that would otherwise make development unsuitable. Local governments, under Florida’s statutes , have the ability to approve large developments for incorporation into county comprehensive plans. This is known as the sector plan process and is intended for developments that exceed 15,0 00 acres (Fla. Stat. 163.3245, 2014) . The development selected as a focus of this project is Plum Creek’ s Envision Alachua Sector Plan , referred to in this paper as Plum Creek’s Sector Plan. Plum Creek is a timber company with land hol dings throughout the US. They own 415,000 acres in Florida, 98,600 of which are under conservation easements (Plum Creek, 2015) . The proposed Plum Creek Sector Plan ( see Appendix 5 ) is sixty five tho usand acres consisting of existing conservation, new conservation, agriculture and development. The proposed development is concentrated in Eastern Alachua County, referred to in this paper as the Windsor Tract, due to its close proximity to the community of Windsor on the Eastern edge of Lake Newnan. Plum Creek’s Sector Plan , still in the review process, is a controversial proposal with in the community. It was chosen for this project for many of the same reasons that make it controversial; the

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3 C hapter 1 Introduction amount of land involved, the location of the area proposed for development and the possible change in character of the rural communit ies adjacent to the property. The sector planning process claims to incorporate , “long term commitments for preservation of enviro nmental resources and agricultural lands as well as policy commitments that emphasize strong urban form to create livable communities and a balanced transportation network” (Powell, Hunter Jr., & Rhodes, 2014, pp. 33.1 2 ) . While the sector planning process shapes these large developments, there is a boundary to the sector plan areas. The properties adjacent to the sector plan are not bound by the same sector planning regulations , which means development may occur in way s that are contrary to the environmental and planning commitments the sector plan is supposed to promote . The land use modeling in this project focuses on how the land adjacent to the Windsor Tract is impacted by Plum Creek’s Sector Plan. Alachua County, Florida, is used as the extent of this project’s study area. Using Bureau of Economic and Business Research population projections, land allocations can be made to accommodate the projected new residents for the C ounty. Suitability analyses are used to ide ntify the optimal areas for these population allocation s. The determination of suitability is based on criteria which commonly influence the siting of new development , including physical and economic. The validity of this hypothesis will be measu red against the outcome of three computer generated models that project future land use. The models are based on suitability analyses, where criteria for development are factored together to identify lands most suitable for development. The first model is based on criteria that reflect present day suitability for development. The second model is based on suitability for development that changes with each increment of growth. A third model was

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4 Chapter 1 Introduction created with the same incremental suitability changes as the sec ond model, but with the inclusion of hypothetical development in the areas proposed for development in Plum Creek’s Envision Alachua sector plan. ESRI ArcGIS was used to create the future land use models, each depicting projected developed land for the ye ars 2030, 2040, 2050, and 2060. The models are created in such a way that the main difference is the way in which proximity to existing development is dealt with. The first model may be referred to as the static suitability model. The second and third mode ls are considered dynamic suitability models, with the third including Plum Creek’s Envision Alachua sector plan. L imitations The limitations for this project are due to the generaliz ed nature of Plum Creek’s current sector plan proposal and the comple x ity of development drivers . Only general lan d use designations are available at this time, so these generalizations are carried through the modeling of future land use scenarios. Eventually , the sector plan proposal and subsequent specific area plans will provide more detailed land use designations and locations that would result in more accurate modeling . Criteria for development are created for the purpose of determining suitability , and a method for altering those suitability values in response to increm ental growth stages has been developed . While t he conversion of suitability from static to dynamic was performed for some criteria, the forecasting of economic and real estate market drivers for development were excluded due to their complexity. The method ology chapter makes note of lesser modeling assumptions made involving variables such as population growth and development density that were decided mainly for procedural efficiency.

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5 Chapter 2 Literature Review Florida’s pattern of development is often described as sprawl. Strip malls and suburbs were built to accommodate the masses of people moving into the state. Growth management through local governments’ comprehensive planning had limited effectiveness because of the relatively short twenty year planning period. A tool developed to help direct growth of larger developments is the sector plan process. (Powell, Hunter Jr., & Rhodes, 2014) The sector plan proc ess was introduced in 1998 as a pilot program, as an alternative to the existing Development of Regional Impact ( DRI ) program which has stood as the process for large scale planning since 1972. During the pilot period, three sector plans were approved befo re the program was adopted in 2011 by the Florida Legislature . The definitions of each are defined as: DRI Sector Plan “Developments which, because of their character, magnitude or location, are presumed to have a substantial effect upon the health safe ty, or welfare of citizens of more than one county. The variety of projects that can fall under DRI status include large scale planned development, airport expansions, “ In recognition of the benefits of long range planning for specific areas, local governments or combinations of local governments may adopt into their comprehensive plans a sector plan in accordance w ith this section. This section is intended to promote and encourage longterm planning for conservation, development, and agriculture on a landscape scale; to further support innovative and flexible planning and development strategies, and the purposes of this part and part I of chapter 380; to facilitate protection of regionally significant

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6 Chapter 2 Literature Review office and industrial parks, mining operations, and sports and entertainment facilities” (Fla. Stat. 380.06, 2014) resources, including, but not limited to, regionally significant water courses and wildlife corridors; and to avoid duplication of effort in terms of the level of data and analysis required for a development of regional impact, while ensuring the adequate mitigation of impacts to applicable regional resources and facilities, including those within the jurisdiction of other local governments, as would otherwise be provided. Sector plans are intended for substantial geographic areas that include at least 15,000 acres of one or more local governmental jurisdictions and are to emphasize urban form and protection of regionally significant resources and public facilities. ” (Fla. Stat. 163.3245, 2014) . The definitions give little indication of the process for sector plan or DRI approval; nor the entities that must provide the approval. The sector plan process requires two planning phases . The f irst is a long term master plan expressing the overall vision of the development. S econd are detailed specific area plan s (DSAP) focusing on a detailed land use proposal for an area of at least 1,000 acres. A sector plan is approved or denied by local govern ment, with corresponding amendment of the ir comprehensive plan. DRIs are approved and adopted by local government, but not before a regional planning council (RPC ) coordinates multi agency review of the proposed DRI. “ The role of the RPCs is to provide a b road based regional perspective and to enhance the ability and opportunity of local governments to resolve issues and problems transcending their individual boundaries ” (Community Affairs, 2011) . Multi agency review of DRIs has been regarded as burdensome by business owners and

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7 Chapter 2 Literature R eview developers, who commonly make significant concessions before final approval (Community Affairs, 2011) . Comprehensive planning has been a part of Florida planning since 1975, when the Legislature enacted the Local Government Comprehensive Planning Act. Each local governments’ comprehensive plan is required to align with state goals, objectives, and policies, containing chapters addressing: future land use, housing, transportati on, sanitary sewer, solid waste, drainage, potable water, natural groundwater recharge, coastal management, conservation, recreation and open space, intergovernmental coordination, and capital improvements (Deyle & Smith, 1998) . Comprehensive plans are a roadmap for local governments to help guide future land use , acting as framework for growth. While comprehensive plans are not a means for project specific planning, failure of a project’s proposed land use to align with a compr ehensive plan’s future land use may result in rejection (Community Affairs, 2011) . Sprawl While limiting sprawl has been claimed to be one of the goals of the sector planning process, the development of many sector plans at a distance from existing urban areas and utility service may actually classify the m entirely as sprawl, regardless of their internal design. The following definition of sprawl comes from the Florida statutes chapter dealing with growth policy, county and mun icipal planning, and land development regulation. “Urban sprawl” means a development pattern characterized by low density, automobile dependent development with either a single use or multiple uses that are not functionally related, requiring the extension of public facilities and services in an inefficient manner, and failing to provide a clear separation between urban and rural uses (Fla. Stat. 163.3164, 2012) .

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8 Chapter 2 Literature Review Since the late 1990’s public concern about sprawl has been on the rise. Of particular importance are the environmental impacts and loss of open space (D.N. Bengston et al, 2005) . The percentage of the country’s population that lives in the suburbs has been increasing, as seen in Table 1 . With federal and state policies stimulating suburban growth, the period post World War II is implicated as the dawn of sprawl in the US (Burchell, 2005) . The effects of sprawl have environmental im plications; air pollution, water pollution, greater use of energy, global warming, and loss of farm and forestland (Squires, 2002) . “Sprawl often leads to inefficient land use practices. Sprawling development requires large inf rastructure investments for roads, sewer systems, schools, and other public services ” (Squires, 2002, p. 12) . Table 1 T he growth of suburban areas in the US (Nicolaides & Wiese, 2006) Date Suburban Area Population Percent of US Population 1850 731,000 3.2 1880 1,667,000 3.3 1910 6,359,000 6.9 1940 17,666,000 13.4 1970 75,500,000 37.1 2000 140,604,000 50.0 The literature most relevant to this project ’s analysis phase focus es on future land use modeling. The book, Smart landuse analysis: The LUCIS model landuse conflict identification strategy , not only provided a majority of the framework for the methodology of this project, i t also helped in its creation. A portion of the concluding chapter is spent on considering some steps that may be taken in the future to build on the LUCIS process. The paragraph that helped inspire this project is included here:

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9 Chapter 2 Literature Review Dynamic land use modeling refers to the use of models that incorporate land use changes over time. These may be active (once set in motion, there is no need for intervention by the analyst) or they may be static (after each iteration the analyst must set the next iteration in motio n). The purpose of dynamic modeling is to capture land use changes that influence land use decisions or value assignments made in subsequent time periods. For example, if future land use is being allocated for a 50 year period, the incremental land use cha nges made over time will affect every subsequent suitability assignment. More specifically, as new lands are urbanized, the presence of those newly urbanized lands with their roads and other public infrastructure will help to increase the suitability of ad jacent lands for conversion to urban use. An alternative, dynamic approach for the 50 year period would be to divide the population projections into 5 or 10 year periods, capture the land use change that occurs within each increment, and input that “ new ” land use into the analysis models as each iteration begins. ArcGIS 9.2 users can take advantage of the ability of ModelBuilder to support iteration, which will make it easier to create dynamic GIS land use models (Carr & Zwick, 2007, p. 200) . Carr and Zwick (2007) cover three major subjects : suitability, conflict resolution and future land use modeling. Of these three, suitability and land use modeling were most pertinent to this project. The book begins with found ational information regarding GIS operations and structure. GIS data are spatially represented as either raster or vector. Raster data, also referred to as grids, makes up the main form of representation used in the LUCIS process and in this project as well . The advantage of raster data involves the simplicity of mathematical manipulation. The study area is divided into cells, whose size is determined by the desired resolution. The smaller the cell size, the greater the grid

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10 Chapter 2 Literature Review resolution . Greater resolution a llows for more accurate representation, but at the cost of larger file size and increased processing speed. To broadly describe o perations in ArcGIS of relevance to the LUCIS process , there are three main objectives: manipulation of data, selection of data, and creation of data. Manipulation includes common mathematical operations , such as summation and multiplication, as well as reclassification from one value to another value . Selection operations are used mainly for the purpose of isolating relevant cell s so that they can be manipulated or provide a base for creating new data. Selection operations are performed mainly based on the value of a cell. Creation of new data, as it pertains to the LUCIS process , usually begins with cells of interest. With those cells, new data can be created to show proximity, density, or other statistical measures. The LUCIS method is built on the generalization of land use into three categories: agriculture, conservation, or urban. With those three categories in mind, the proc ess continues with five steps: defining goals and objectives, data inventory, suitability, preference, and conflict . Goals and objectives are actionable statements, purposed toward identifying criteria important for determination of suitability for each land use category in question. For instance , an objective may be to identify lands suitable for development based on slope. Elevation data, and subsequent slope determination, will result in cells with values that can be classified into a range of suitabilit y. The suitability range used in LUCIS is from 1 to 9 (Carr & Zwick, 2007) . The structure of suitability determinations is much like a watershed . Many creeks run into a few streams, which flow into one river. The many subob jectives combine to make a few objectives, which are combined to make one goal. Of importance is the fact that if every goal has objectives , and every objective has subobjectives, the sub objectives are the only point of entry for the data used in the proc ess. Once the subobjective suitability is determined, referred to as a single utility assessment (SUA)

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11 Chapter 2 Literature R eview in the LUCIS process, the only steps left are combinatory. When subo b jectives are combined to form objectives , or objectives are combined to form goals, the manipulation is referred to as a multiple utility assessment (MUA) . The MVA process involve s weighting of each input grid to appropriately reflect its importance to the overall suitability of the land use category . The weighting of each suitability den otes a hierarchy of importance . Systematic assignment of weights can be managed using the Analytical Heirarchy Process (AHP) (Carr & Zwick, 2007) . The remaining two steps of the LUCIS process are preference and conflict. Th e overall suitability for each land use, agriculture, conservation and urban, are condensed from values that range from 1 to 9 into three values : 1, 2, and 3 , referred to as preference values for each land use category. Three is the most preferred location and 1 is the least. To determine conflict, the three values for the three land use types, agriculture, conservation and urban, are combined, so that each cell in the study area has a three digit number, where the 1, 2, or 3 in the hundreds place describes agriculture preference , the 1, 2, or 3 in the tens place describes conservation and the 1, 2, or 3 in the ones place describes urban land use. The comparison of these three digits to one another describes the conflict in each cell among land use preferenc es. For instance, a cell of value 113, is described as having high urban preference and low conflict. This is because the digit in the ones place, the 3, indicates high urban preference. The 1 values correspond to agriculture and conservation and because t hey are both low preference values, they do not conflict with the urban preference; thus the low conflict descriptor. There are 27 distin ct conflict combinations possible in the conflict grid ( 3 3 3 = 27 ) . The resulting conflict grid can then be used to iden tify where each land use has high preference and low conflict compared to the other two land uses. The conflict grid can be used to select the land most suitable to accommodate projected population growth (Carr & Zwick, 2007) .

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12 Chapter 2 Literature Review While LUCIS provided most of the framework for this project, other works were referenced for more detailed procedural steps. M. Carr and P. Zwick produced Florida 2060: A population distribution scenario for the state of Florida, in which a future dev elopment scenario was created based on statewide population projections through the year 2060. Carr and Zwick (2006) reach the conclusion that rural land is being urbanized at an alarming rate if development policies remain consistent with those in use in 2005. Of use to this project was the population projection interpolation method based on average annual yearly growth. Of greater importance was the third appendix, which listed suitability criteria , a rationale for their use, and assigned weights. Although certain criteria differ in this project, it provided a rational starting point for the weighting of development criteria used in this project (Carr & Zwick, 2006) .

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13 Chapter 3 – Plum Creek’s Envision Alachua Sector Plan – Sub urban sprawl is important to understand at two scales. The local scale shows impacts to community development and growth patterns of cities; impacts that can be avoided with developments designed to limit sprawl. A larger scale must be considered, as well, to see the impacts of development on the region. When referring to sprawl without defining the scale, similar arguments can be ultimately be at odds. Plum Creek’s sector plan addresses how it will control sprawl with cluster development and greenbelt bor ders at the periphery of the mixed use areas (Envision Alachua, 2015) . Alachua County’s Growth Management Department also wants to limit sprawl in the county, as well. While both parties agree that sprawl is to be avoided, thei r perceptions about Envision Alachua conflict. The County has this to say about Plum Creek’s proposed development: The development proposed by the Envision Alachua Sector Plan has been determined to be sprawl by the state definitions. This has been analyze d in Section VII Statutory Requirements for Comprehensive Plan Amendments and Sector Plans in the staff report. New development inside the Urban Cluster that surrounds Gainesville is infill, which is generally considered to be the opposite of sprawl. The U rban Cluster boundary was established in 1991 and is the area within which public services including water, sewer, transportation systems and other services can be efficiently provided to urban development. (Alachua County Fl orida, 2015, p. 5) Envision Alachua, in a May 2012 document titled, Vision, Goals and Planning Principles for Plum Creek Lands in Alachua County , seemingly has recommendations that are in keeping with Alachua County’s Growth Management Department. The co nsideration of Maryland’s Rural Legacy Program as a case study, particularly focused on conservation of forest lands, yielded “Lessons for Gainesville and Alachua

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14 Chapter 3 – Plum Creek’s Envision Alachua Sector Plan County ” (Envision Alachua, 2015, p. 128) . One of the conclu sions was to “Promote local transfer of development rights (TDR) programs to provide an alternate means of financing conservation of land while encouraging development within and near existing urban areas” (Envision Alachua, 2015, p. 128) . Plum Creek has negotiated transfer of development rights in the past. In 2009, Marion County, which borders Alachua County to the south, approved a TDR agreement with Plum Creek to conserve almost 2,000 acres of forest near Fort McCoy. “ Plum Creek will continue to manage the conservation land as a working forest and will eventually sell the development rights received for use in areas designated for future growth” (Plum Creek, 2015) . According to Plum Creek’s web site: Transfer of Development Rights (TDR) programs are an innovative entitlement tool used by landowners and local governments to direct growth near available infrastructure or towards urban areas equipped to manage growth while protecting larger tracts o f land for environmental benefits. TDR programs enable increased development where existing transportation and infrastructure exist, while saving taxpayers and municipalities money by decreasing the spread of municipal service requirements. (Plum Creek, 2015)

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15 Chapter 4 Methodology 4 Methodology There are two phases to this project; case study analysis and future land use modeling. The case studies compare growth patterns in and around each to the area in and around the Windsor Tract of Plum Creek’s Sector Plan. The future land use modeling compares growth patterns in Alachua County with and without the simulated influence of Plum Creek’s Sector Plan. The location and timing of development in and around each case s tudy DRI is of the highest importance when comparing to the area in and around Plum Creek’s Sector Plan. GIS parcel data were used to identify those with structures and the year the structures were built. While the type of structure is not known, the prese nce of a built structure implies development of some sort . The statewide parcel data, listed in Appendix 2 , on page 80 , was clipped to each case study DRIs’ boundary , using the DRI data also listed in Appendix 2 . For each DRI , there were three study areas : ; the area inside the DRI boundary, the area within one mile of the DRI, and the area within fifteen miles of the DRI. The Buffer tool was used to create the distances from the DRI boundaries. For each of the buffered areas, the DRI was excluded using the Erase tool. The statistics and maps created are all based on the parcel data field “ACTYRBLT”, the actual year built of a structure on a parcel, if one has been built. The analysis covers the years 1970 to 2013. The purpose of the future land use modeling in this project is two fold : first, to compare static and dynamic suitability modeling and second, to compare future development projections in Alachua County with and without the influence of Plum Creek’s Sector Plan.

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16 Chapter 4 Methodology T hree future land use scenarios are created in this project , to compare the results . E xisting and future land use are reclassified into two broad categories that summarize land use : developed and undeveloped areas. See Appendix 1 , on page 77 , for the details on reclassification of existing land use into either developed or undeveloped areas. This classification simplifies in corporation of allocated urban area into subsequent suitability iterations simply as developed area. Much of the procedure for this project is based on early steps of the LUCIS model . Conflict identification was not used because c onservation and agricultu re suitability analys e s were not performed because it is assumed that no new agriculture or conservation lands will be allocated in the future land use scenarios. While important in real world land use planning, the determination of conservation or agriculture suitability was not central to the premise of this project. T his project focuses on development suitability . u d d s uitability Projecting population growth involves the creation of general preferences for urban develo pment. These preferences are referred to in this paper more often as suitability. Suitability describes the relative degree to which land is fit for an identified purpose. The purpose, in this case, is development. The suitability value ranges from 1 to 9, where 1 is the least suitable and 9 is the most suitable. Nine criteria for development have been used and are listed in Table 2 . Each criterion has a goal that is actionable because there are GIS data which allow for the identification of these areas. Many of the criteria and rationale of Table 2 are similar to those established by Carr and Zwick (2007). D ata used for each goal, as well as the source and description can be seen in Appendix 2 on page 80.

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17 Chapter 4 Methodology Table 2 Criteria, Rationale and Analysis for Development Criteria for development Rationale Analysis Close to developed land New development tends to occur near existing urban development Identify lands proximal to developed areas In areas of high road density New development tends to occur in areas of relatively higher road density Identify areas of high road density In areas planned for development New development is exp ected in areas already approved for development Identify lands of approved DRIs and PUDs Outside of wetlands The cost of development tends to increase in wetland areas Identify areas without wetlands Close to major roads Existing roads enable new develop ment Identify lands proximal to major roads In areas with soil that allow water drainage New development costs tend to increase in areas of poorly drained soils Identify areas with well drained soil Existing utility service New development tends to occu r in areas of existing or planned utility service Identify lands within urban service areas Outside of flood hazard area New development and insurance costs tend to increase in flood hazard areas Identify areas without flood hazards In areas of flat land New development costs tend to increase in areas with steep elevation change Identify lands with mild or moderate slopes p d l As new urban development tends to occur near existing urba n development, this step determines suitability based on proximity to existing development (Carr & Zwick, 2007) . To determine existing developed area, parcel data was reclassified as “developed” or “undeveloped” according t o each land use code ( see Appendix 1 on page 77 ). Because this suitability is based on the proximity to developed parcels, an average distance was determined using a Euclidean Distance operation for all of the developed parcels in Alachua County which captured the distance of existing developed land from other developed land. Statistics were tabulated from the output of the Euclidean Distance using the

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18 Chapter 4 Methodology zones of the Urban Reserve Boundary of Alachua Cou nty data. The output gave an average distance of development from other development in areas within the Urban Reserve Boundary of Alachua County . The mean distance is 259 meters, with a standard deviation of 400 meters. A common procedure for creating sui tability based on distance to an area of interest is to use the Reclassify tool to rank the Euclidean Distance values into 1 to 9 integers based on whether it is suitable to be near or far from an area of concern (Carr & Zwick , 2007) . The reclassification is based on the mean and standard deviation. For distance from an area of interest, where the shorter the distance from that area the higher the suitability, the value of 9 is given from the edge of the area up until the ave rage distance. A value of 8 is given beyond that zone, extending for a distance of one fourth the standard deviation. The values assigned continue to decrease with each subsequent fourth of the standard deviation value until the value of 1. The value of 1 represents the distance of twice the standard deviation from the average. Using the average and standard deviation distances found for distance of developed area from other developed area, the 9 value is assigned up until 259 meters from developed area. A t the distance of 1,059 meters and beyond, the reclassification process now assigns a value of 1, as 1,059 meters is the average, 259 meters, plus twice the standard deviation which is 400 meters. The output suitability map shows the 9 to 1 integer values r adiating from existing developed land. The previous paragraph describes a useful process for developing suitability based on proximity to an area of interest, however, it was not the process used here because the integer value output from 1 to 9 contribut ed to a lack of differentiation of final suitability values when the time came to select cells . The specifics of population allocation and the raster cells that represent the people allocated are discussed in a later section , but generally, the closer the quantity of cells selected is to the cells needed

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19 Chapter 4 Methodology to represent a growing population, the better. Instead of an integer output of 1 to 9, the process described in the next paragraph gives an output that includes a tenths place. The resulting suitability sti ll goes from 1 to 9, but instead of whole numbered intervals , 1, 2, 3 the intervals are now, 1.1, 1.2, 1.3, and so on, up to 9. Again, the reason the process below was utilized was to obtain an output that contains a wider variety of values in the final s uitability, with the added benefit of a suitability output that is easier to defend as it relates to real world implications of distance based decision making. There most likely is not a lot of difference in suitability of the actual land between the 259th and the 300th meter from developed land, but with integer values this meter represents a drop from 9 to 8 in suitability. In the process below, it now represents a drop from 9 to 8.9 in suitability.

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20 Chapter 4 Methodology Figure 1 Suitability Assignm ent Reclassify versus Slice The Slice tool was used here instead of reclassifying, outlined above. To summarize the steps below in lay terms, a donut of land was isolated based on its distance from developed land and then cut into 81 rings . The r ings end up with values decreasing at equal distances, in tenths, from 9, at the inner edge, to 1, at the outer edge. The land closer to development than the inner edge value of 9 is also assigned a value of 9. Similarly, the land further than the outer ed ge value of 1 is also assigned a value of 1. The distance from the mean to the mean plus twice the standard deviation was first isolated from the output of the Euclidean Distance by using the Extract by Attributes op eration: "Value" >= 259 AND "Value" <= 1059.858. The value 259 is the average distance between developed land and t he value 1059.858 is the total number of meters obtained when the mean distance is added to

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21 Chapter 4 Methodology twice the standard deviation. This step isolates the donut mentioned earlier. The Euclid ean Distance will be called RasterA, to be used again in the final step, and the extraction output will be called RasterB. Raster B is then reclassified, using the Slice tool, into 81 output zones , based on equal intervals. The Raster Calculator tool is the n used to convert the output of the Slice tool, called RasterC, into the 1 to 9 range using the calculation: ( RasterC * 1.00 + 9) / 10. The number of slices was chosen as 81, so the output value range of 1 to 81 can be summed with 9, yielding a 10 to 90 range. The output is then divided by ten, giving the final desired range of 1 to 9. Note that RasterC is multiplied by a value of 1.00. While mathematically unnecessary, multiplying by 1.00 is done to ensure an output that contains decimals, as a conversion to integers is a default for raster calculator operations that only contain whole numbers. In this instance, suitability is inversely proportional to distance, so an inversion step is now necessar y. The inversion is required because t he Slice tool output v alues go from low to high, over the range of distance values that also go from low to high. The Raster Calculator is used to invert the values with the calculation: RasterD (2 * RasterD )) + 10, where RasterD is the output of the previous Raster Calculat or step. The output now yields lower distance values corresponding to higher suitability values. In the circumstance where the desired output is a suitability that is directly proportional to distance, this step would not be required. Also, if the distance spanned by the suitability is greater and more precision is desired, the area can be spliced into 801 divisions, which can be similarly transformed to the 1 to 9 range by adding 99 and dividing by 100. This would produce values with increments of one hund redth. Now that the Slice tool and a few Raster Calculator operations have been performed the remaining steps are to simply assign 1 or 9 values to the areas not addressed earlier. The areas of No Data created when the Extract by Attributes tool selected the distance range between 259 and 1059.858 meters, must be converted back to a value. The conversion is done with a Raster Calculator expression:

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22 Chapter 4 Methodology Con(IsNull(Raster E ), 1, RasterE ) , where RasterE is the output of the inversion performed by the previous Rast er Calculator operation. A value of 1 has now been assigned to all of the cells that were previously No Data , corresponding to the distances beyond the 9 to 1, where the suitability is at its lowest . T he cells at a closer distance are assigned a value of 9 by running the Cell Statistics tool, asking for the maximum values when comparing the output of the previous step, called RasterF, with a raster, called RasterG, which is formed by the Raster Calculator expression: Con(RasterA <= 259, 9, 1), where RasterA is the original Euclidean Distance raster. See Appendix 3 on page 82 , for the resulting suitability map. Suitability based on road d ensity was performed, as new development tends to occur in areas of relatively higher road density (Carr & Zwick, 2007) . Road density was determined by performing the Line Density tool on r oadways from the U.S. Geological Su rvey. Class 5 roadways were excluded from the data input, so that off road trails did not influence the output. The search radius for the Line Density Tool was set to one mile. The average road density for the developed area was determined using the Zonal Statistics tool for the zone of existing development, established when finding suitability based on distance to development. The average road density for existing developed land is 5.84 and the standard deviation is 4.5. Similar to the process described earlier for determining suitability based on proximity to developed land, the Slice tool was used to obtain the suitability range of 1 to 9 for suitability based on road density. The values of road density equal to and less than the average, 5.84, was isolated and then sliced, using equal intervals, into 81 sections, yielding a range from 1 to 81. Using the Raster Calculator tool, the slices were normalized to the range from 1 to 9 by adding 9 to the value and then dividing by

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23 Chapter 4 Methodology ten. The areas with road densi ty values greater than 5.84 were assigned a value of 9 using the Raster Calculator expression: Con(IsNull(Raster1), 9,Raster1), where Raster1 is the normalized slice output. See Appendix 3 on page 82, for the resulting suitability map. Because new development is expected in areas already approved for development, suitability based on DRI and PUD areas was created (Carr & Zwick, 2007) . DRI and PUD areas were identified with the data listed in Appendix 2 on page 80. Using the Reclassify tool, the DRI and PUD areas were assigned a value of 9. A value of 1 was assigned to the remaining land. See Appendix 3 on page 82 , for the resulting suitability map. Suitability based on absence of wetlands was created, as the cost of development tends to increase in wetland areas (Carr & Zwick, 2007) . Wetland areas were determined by the “marsh/swamp” and “reservoir” zones from the National Hydrography Dataset. Using the Reclassify tool, wet land areas are assigned a value of 1 and the remaining area is assigned a value of 9. See Appendix 3 on page 82 , for the resulting suitability map. Suitability based on proximity to major roads was created, as existing roads enable new development (Carr & Zwick, 2007) . Major roads were identified with the data listed in Appe ndix 2 on page 80 . The Euclidean Distance tool was used to assign cell values to the Alachua County study area based on distance to the nearest major road. The average distance of developed land from major roads was determine d using the Zonal Statistics tool for the zone of existing development, established when finding suitability based on distance to development, using the values from the Euclidean Distance tool

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24 Chapter 4 Methodology output. The average distance of existing developed land from ma jor roads is 563.8 meters, with a standard deviation of 589.7 meters. The same steps that were used to find the suitability based on distance to development were used to find the suitability based on distance to major roads. For the specific steps, see th e process described in that section. The area of the resulting suitability gradient from 9 to 1 corresponds to the area between the average distance from development from major roads, 5 63.8 meters, and the average distance plus twice the standard deviation , 1743.23 meters. With those two distances extracted from the Euclidean Distance from major roads utilizing the Extract by Attributes tool, the same slicing, normalizing, inverting and No Data conversion steps, detailed when outlining the process of develo ping suitability based on distance to development, were duplicated. See Appendix 3 on page 82 , for the resulting suitability map. Suitability based on soil drainage characteristics was created, as new development costs tend to increase in areas of poorly drained soils (Carr & Zwick, 2007) . The soil data, listed in Appendix 2 on page 80, was reclassified, using the Reclassify tool, based on the field describing drainage c haracteristics, DRAINAGECL. See Table 3 for suitability values assigned to soil drainage characteristic s. See Appendix 3 on page 82, for the resulting suitability map.

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25 Chapter 4 Methodology Table 3 Soil Drainage Characteristics and Assigned Suitability Values DRAINAGECL Description Assigned Suitabi lity Value Excessively drained 9 Well drained 9 Moderately well drained 8 Somewhat poorly drained 5 Poorly drained 3 Very poorly drained 1 No value (corresponds to open water) 1 ility Suitabilit y based on urban service areas was created, as n ew development tends to occur in areas of existing or planned utility service (Carr & Zwick, 2007) . Lands designated by Alachua County as u rban and extra territorial reserves were used to represent this area. Using the Reclassify tool, the areas inside the urban and extraterritorial reserves were assigned a suitability value of 9, while areas outside were assigned a suitability value of 1. See Appendix 3 on page 82, for the resulting suitability map. Suitability based on avoidance of flood hazard areas was created, as cost of new developm ent and insurance tend to increase in flood hazard areas The flood hazard area data, listed in Appendix 2 on page 80 , was reclassified, using the Reclassify tool, based on the field describing designating location inside or outside the flood zone, DESCRIPT. Using the Reclassify tool, the areas inside flood zone hazard areas were assigned a suitability value of 1, while areas outside were assigned a suitability value of 9. See A ppendix 3 on page 82 , for the resulting suitability map. Suitability based on slope was created, as new development costs tend to increase in areas with steep elevation change. The slope value of land was determined by using the topography data, listed in

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26 Chapter 4 Methodology Appendix 2 on page 80. The Slope tool was used in conjunction with the topography values to output percent rise, utilizing a Z factor of 0.3048 to compensate for the meter to feet conversion. The resulting slope values were reclassified, using the Reclassify tool, according to Table 4 . See Appen dix 3 on page 82, for the resulting suitability map. Table 4 Slope Values and Assigned Suitability Slope Value (percent) Assigned Suitability Value 0 – 5 9 5 – 10 7 10 – 15 5 15 – 20 3 Over 20 1 The criteria for development suitability, in the previous section, are combined to determine the overall development suitability for Alachua County. While the criteria are used to project future developed land, the significance of each criterion on real world development is not equal. The degree to which the overall development suitability is influenced by each criterion is reflected in the percent of weight assigned to each criterion. For example , suitability based on proximity to development is assigned a weight of 25%, while suitability based on slope is assign ed a weight of 5% ; meaning the distance to development is considered 5 times more important than the slope of land. See Table 5 for the list of criteria and the weights assigned to each. See Appendix 3 on page 82, for the map of overall suitability for development that results from this weighted combination. The weights are informed by two so urces; M . O’Brien (2010) and Carr and Zwick (2006) . O’Brien’s highest weighted criterion, proximity to developed areas, made up for 17% of his total development suitability. Carr and Zwick’s (2006) highest weighted criterion was also proximity to developed areas, making up 33% of their total development suitability.

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27 Chapter 4 Methodology Table 5 Suitability Weights Suitability based upon Weight proximity to developed areas 25% road density 17% DRI and PUD areas 15% wetlands 13% proximity to maj or roads 8% soil drainage 7% urban service areas 5% flood hazard areas 5% slope 5% Total 100% Population allocation was determined by three factors: current population, current developed land area, and future population growth projection. When the current population is divided by the current developed land area, the outcome is referred to as gross urban density. The gross urban density is then multiplied by the population needed to allocate, which is found by subtracting the cu rrent population from the population growth projection. See Appendix 4 , on page 92, for population growth projections for Alachua County. When multiplying the gross urban density by the population gro wth , the number obtained is the amount of land needed to allocate that growth. While land area is commonly measured in acres and gross urban density is commonly reported in people per acre, the GIS analysis is easier done with land area measured in cells and gross urban density calculated in people per cel l because b oth the current developed land area and the selection of land for population allocation are based on number of cells in the raster layer. T he method used in this analysis is based on cell counts , with the conversion to acres performed after the fact for the purposes of presentation. The gross urban density, derived from 2013 population and current developed land area, was used for all of the future developed land scenarios in this project. The gr oss urban density is calculated at 2.06 people per acre,

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28 Chapter 4 Methodology based on the 2013 values of population and total acres of developed land in Alachua County , found in Table 6 . Table 6 Population Projections and Required Land for Alachua County (Bureau of Economic and Business Research (BEBR), University of Florida, 2014) Year Population Developed Land Area Total Growth Total Cells Additional cells Total Acres Additional Acres 2013 248,002 --4,868,350 --120,299 --2030 289,200 41,198 5,677,078 808,728 140 , 283 19 , 984 2040 306,800 17,600 6,022,571 345,493 148 , 820 8,537 2050 * 328,480 21,680 6,448,156 425,585 159 , 337 10,517 2060 * 350,160 21,680 6,873,741 425,585 169 ,854 10,517 *derived by extrapolation The process of selecting the cells required for each population allocation was the same for each of the scenarios. The overall suitability raster is first altered so that open water, rights of way, existing conservation and all p revious development are avoided for the allocation. The alteration is done using the Raster Calculator tool and the expression: Con((Raster1 = 1) OR (Raster2 = 1) OR (Raster3 = 1) OR (Raster4 = 1), 1, Raster5), where Rasters 1,2,3 and 4 represent the avoid ed areas and Raster 5 represents the overall suitability raster. The Slice tool was then used to divide the suitability into 100,000 slices. The Raster Calculator expression: ( ( ) , 1, 0) This equation produces a raster of the study area with cell values of 1 and 0, where 1 values are cells allocated for population growth and 0 values are non allocated cells. See Appendix 4 , on page 92 , for the number of cells required and the number of cells selected for the three models described in the following section.

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29 Chapter 4 Methodology – For the first model, population allocations were made for the years 2030, 2040, 2050 and 2060. This model is r eferred to as the Static Suitability Model because the suitability values were based on one overall suitability map : the combination of the nine suitability criteria discussed previously, according to the weights in Table 5 , on pa ge 27 . In other words, the population allocation for 2060 was based on current suitability, the same way that the population allocation for 2030 was based on current suitability. The cell selection for each decade was based on total projected growth for Alachua County. For instance, the population allocation cells required for the year 2040 include the population growth from 2013 to 2040, and not just the decade preceding 2040. See Appendix 4 , on page 92 , for details regarding the quantity of cells required for allocation and the quantity of cells actually selected. – For the second model, population allocations were mad e for the years 2030, 2040, 2050 and 2060. This model is referred to as the Dynamic Suitability Model because one suitability criterion was adjusted for each decade of population allocation, while the remaining eight suitability criteria were static, similar to the first model. The dynamic suitability criterion was also the highest weighted of the nine : suitability based on proximity to developed land. The population allocation for 2030 is based on the same current overall suitability as the first model. Th e allocation for 2040 differs in that the 2030 population is now considered developed land. As developed land, it is combined with the existing developed land and a new suitability based on proximity to developed land is created. As each subsequent decade’ s population allocation is made, the suitability based on proximity to development is altered to include development up until that point. See Figure 2 for a graphic representation of this process.

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30 Chapter 4 Methodology Figure 2 Dynamic Suitability Process – For the third model, population allocations were made for the years 2030, 2040, 2050 and 2060. Similar to the second model, this mo del also includes dynamic suitability elements. The major difference is this model has incorporated changes based on general land uses proposed by Plum Creek’s Sector Plan. For this reason, this model is referred to as the Dynamic Suitability Model Including Plum Creek Proposed Sector Plan. See Appendix 5 , on page 94 , for general land use proposed in the Plum Creek’s sector plan . The first and second models did not take into consideration the boundary of Plum Creek ’s 2015 Developed land (existing) 2015 Suitability based on proximity to development Contributes to 2030 Allocation of developed land 2015 Developed land + 2030 Allocation of developed land 2030 Suitablity based on proximity to development Contributes to 2040 Allocation of developed land 2015 Developed land + 2030 and 2040 Allocation of developed land 2040 Suitablity based on proximity to development Contributes to 2050 Allocation of developed land 2015 Developed land + 2030, 2040 and 2050 Allocation of developed land 2050 Suitablity based on proximity to development Contributes to 2060 Allocation of developed land

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31 Chapter 4 Methodology property, with the exception of existing conservation land , so that projected development may be sited within the boundary if the development suitability is sufficient. In contrast, the third model restricts population allocation from Plum Creek property ; consistent with Plum Creek’s assumption that the population inhabiting their development will be above and beyond Alachua County projected growth. The consideration of the Plum Creek Sector plan is two fold in terms of suitability analysis . Firstly, the suitability based on proximity to developed land includes phases of growth proposed by Plum Creek. The same method used in the second model is applied here, meaning previous development allocations influence subsequent suitability, in turn, effecting the next population allocation. The land proposed to be developed according to Plum Creek’s sector plan is divided into five areas. They are referred to as areas A, B, C, D, and E. In Plum Creek’s graphics, areas D and E are often considered one area. See Appendix 6 , on page 95 , for the map of these areas. Two conditions are assumed in order to align the development of these areas with the decades selected for population allocation projections. One is the development will happen in phases beginning with A, then B, then C, and then D and E. The other assumption is that the development of these areas will happen between the years of population allocation projections , meaning area A will be dev eloped between now and 2030, area B will be developed between 2030 and 2040, area C will be developed between 2040 and 2050, and areas D and E will be developed between 2050 and 2060. The incorporation of these development areas into the suitability based on development proximity was done at the beginning of each development phases’ timeframe. This means area A was incorporated into the 2015 development area so that it influences the 2030 population allocation because the effect of area A’s development between 2015 and 2030 would have real world influence on the actual development suitability within the decade of its construction. If it were considered developed land in 2030 the effect on population

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32 Chapter 4 Methodolog y allocation would not be seen until 2040. Each decade’s suit ability based on proximity to development can be seen in Appendix 7 , on page 96. The second consideration for Plum Creek’s proposed sector plan is a change in road density suitability. As seen in Table 5 , on page 27 , this is the second most influential criterion of the overall suitability. The road density for the proposed sector plan is not known at this time, so steps were taken to simulate th is. The development phases, A, B, C, D, and E, were incorporated into suitability based on road density for 2015 and each subsequent allocation year in the same way as the suitability based on proximity to development, described in the previous paragraph. For each phase the suitability was assigned a value of 9 at the boundary and a value of 1 at some distance away from the boundary. This distance range was determined by examining the previously created suitability based on road density. The shortest distan ce from any value of 9 to any value of 1 was used as the distance away from Plum Creek’s phases of development over which the suitability will gradually decrease from 9 to 1. This distance was found to be 1,208.9 meters. The gradual decrease was produced b y performing a Euclidean Distance from the development phase boundaries. The area within 1,208.9 meters was extracted and sliced using the process described earlier regarding the suitability based on proximity to developed land. Each phase was done separat ely, so the influence on suitability could be added as each phase was assumed to be constructed. In order to add the phases to the already created suitability based on road density, the Cell Statistics tool was used to combine the two by selecting the maxi mum values between them. The road density influence from area A was combined with the previously created suitability to make a 2015 suitability based on road density. The influence from area B was then combined with the 2015 suitability using a cell statis tics maximum method to obtain the 2030 suitability based on road density. Likewise, area C was combined with the 2030 suitability based on road density to obtain the

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33 Chapter 4 Methodology 2040 suitability. Areas D and E were combined last to form the 2050 suitability based on r oad density. Each decade’s suitability based on road density can be seen in Appendix 7 , on page 96 . The following graphics serve as a procedural summary for the three models. Figure 3 Model 1

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34 Chapter 4 Methodology Figure 4 Model 2

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35 Chapter 4 Methodology Figure 5 Model 3 – P roduced as a generalization of anoth er growth projection, a fourth mo del was created after the results of the first three models were obtained and analyzed . It was created after the fact, as a way to depict the relative development suitability of the area in and around the Windsor Tract. The question this model answers is, “If Alachua County were developed according to only the 2015 suitability values, from highest to lowest, how much of the county will be developed at the time when half of the Windsor Tract is considered suitable for development?” This amount of land will b e referred to as county wide developed land to the point of fifty percent build out of Plum Creek. To answer this question, the average suitability value of Plum Creek’s proposed developed land was calculated, as described in the

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36 Chapter 4 Methodology previous section. The Extr act by Attributes tool was then used to select all of the suitability values from the 2015 static suitability raster, used in the first model, with the selection expression: “Value” >= 5.003. The 5.003 value is the average value of overall suitability for the Windsor Tract of Plum Creek’s sector plan. With the quantity of land at fifty percent build out of Plum Creek determined, the quantity of people allocated to that land can be calculated. The amount of land in Alachua County obtained by this process was then multiplied by the gross urban density to quantify how many people would be allocated to the selected land. The gross urban density of existing development was used, with the assumption that development density will not change. This population growth figure can then be compared to the projected growth of Alachua County, seen in Appendix 4 , on page 92 . If it is assumed that Alachua County will continue to grow at the annual rate computed at 2,168 p eople per year, the formula below calculates the years needed for that growth. ( ) = The Zonal Statistics as a Table tool was used to find various statistics relevant to the existing and futur e population allocation models, requiring a value raster and a zone raster. The value raster is the output of Euclidean Distance tool performed on all development, existing and future, before the allocation in question. The zone raster is the allocation in question. For instance, 2050 projected future development area is the zone of interest, while the distance from all existing and projected development through 2040 is used as the Euclidean Distance boundary. The Zonal Statistics as a Table tool was also used to determine the average suitability value of lands selected in the population allocations for each m odel , performed with the input zone raster of the allocated land for the year in question. The input value raster was the suitability values that each

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37 Chapter 4 Methodology allocation in question was based on. The average suitability of the areas proposed for development accord ing to Plum Creek’s sector plan, seen in Appendix 6 , on page 95 , was also computed. The 2050 overall suitability for development produced for each model was used as the input value raster, while Plum Creek’s land proposed for development was used as the input raster zone. Computing the amount of land developed in and around the Windsor Tract required a query of each population allocation for each of the three models. The development boundary is base d on the development land proposed in Plum Creek’s sector plan, seen in Appendix 6 , on page 95 . The extent of land considered around Plum Creek’s proposed developed land was determined by the largest distance of influence created by the alterations in suitability described in the previous section. The distance is 1280.9 meters, corresponding to the alteration of suitability based on road density. The methods used in this project are for two main pur poses; analyzing development as it has happened in the case study areas and projecting where development may occur in Alachua County. The following chapter covers the analysis of development in the case study areas.

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38 Chapter 5 Case Studies and Plum Creek 5 k Four case studies have been selected and analyzed for comparison to Plum Creek’s sector plan : The Villages, Harmony, Nocatee and Celebration. The case studies, chosen for characteristics similar to Plum Creek’s proposed sector plan, are loc ated in Central and North Florida. The similarities and differences between each case study, as well as the Plum Creek’s proposed sector plan, are shown using d ata includ ing population change characteristics and parcel data reflecting structures and dates of construction for areas within and around the developments in question. Chart 1 , on page 39 , serves as a quick comparison of scale, relative to structures built within the boundaries of each case st udy . Chart 2 , on page 39, shows the structures built within 15 miles of the boundary of each case study , including the boundary of proposed development according to Plum Creek’s sector plan . As seen b y the dates of approval for each case study, they are all DRIs, as the sector plan process was in its infancy for Nocatee and did not exist as an option for the other three developments.

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39 Chapter 5 Case Studies and Plum Creek Chart 1 Case Study Comparison of Scale 0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 Structures Built within DRI boundary Actual Year Built Case Study Scale Comparison The Villages Harmony Nocatee Celebration Chart 2 Case Study Regional Comparison of Structures Buil t Over Time 0 2000 4000 6000 8000 10000 12000 14000 16000 18000 200001970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 Structures Built within 15 miles of DRI boundary, excludes DRI structures Actual Year Built Regional Comparison of Structures Built The Villages within 15 miles Harmony within 15 miles Nocatee within 15 miles Celebration within 15 miles Plum Creek within 15 miles of proposed developed area

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40 Chapter 5 Ca se Studies and Plum Creek Celebration Located in Northwest Osceola County, Celebration was approved as a DRI in 1994. The buildout date is at the end of 2023, with approval for 8,065 dwelling units, 1,977,087 SF of retail space, 3 golf courses 54 holes, 1,539 hotel r ooms, 150 timeshare units, 1,780,000 SF of industrial space, 5,000 parking spaces, a medical center consisting of 209 hospital beds and 360,036 SF of medical office, 1,299 acres of open space, and a 4.1 acre electrical substation . Celebration is unique fro m the other case study DRIs because much of the surrounding property is under the ownership of Disney (Osceola County, Celebration DRI, 2015) . Table 7 Celebration DRI Facts County Osceola Land Area 5,08 3 acres Date of DRI Approval 03/01 /199 4 Buildout date: December 30, 2023 Approved Dwelling Units 8,065 DU Table 8 Celebration County Population Change Characteristics (Bureau of Economic and Busine ss Research (BEBR), University of Florida, 2015) County Total Change 2010 2014 Births Deaths Natural Increase (Related Percent Change) Net Migration (Related Percent Change) Osceola 26,868 15,219 7,095 8,124 (30.2%) 18,744 (69.8%)

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41 Chapter 5 Case Studies and Plum Creek Figure 6 Celebration Location Map

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42 Chapter 5 Case Studies and Plum Creek Figure 7 Celebration Structures Built Over Time

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43 Chapter 5 Case Studies and Plum Creek Chart 3 Celebration Structures Built Over Time Chart 4 Celebration Region St ructures Built Over Time 0 50 100 150 200 250 300 350 400 450 5001970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 Structures Built Actual Year Built Celebration Structures Built Over Time Inside DRI Boundary Within 1 mile of DRI Boundary ----Date of Approval ----0 2000 4000 6000 8000 10000 12000 14000 16000 18000 200001970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 Structures Built Actual Year Built Celebration Region Structures Built Over Time Inside DRI Boundary Within 15 miles of DRI Boundary ----Date of Approval -----

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44 Chapter 5 Case Studies and Plum Creek Chart 3 and Chart 4 , on page 43 , show that construction inside the DRI boundary occurred promptly after approval. The area within one mile of Celeb ration’s border did not share this growth. This may have been an effect of the construction of Celebration, as the area within 15 miles of Celebration’s border shows steadily increasing growth. Table 8 on page 40 , shows that c lose to 70 percent of the population increase between 2010 and 2014, in Osceola County, was due to people moving into the county . Nocatee Nocatee is a DRI located mainly in St, Johns County, with a small portion of its northern area located over the Duva l County line. In addition to the almost 15,000 approved dwelling units, Nocatee is also approved for 1,000,000 square feet of retail, 4,000,000 square feet of office space and nine public schools. Almost two thirds of the land will be place d in preservati on and protected (Nocatee, 2015) . Nocatee is t hird in the list of top selling developments in the USA for 2014 (LaRue, 2015) . Table 9 Nocatee DRI Facts Counties St Johns an d Duval Land Area 13,356 acres Date of DRI Approval 02/09/2000 Approved Dwelling Units 14920 DU Table 10 Nocatee County Population Change Characteristics (Bureau of Economic and Business Research ( BEBR), University of Florida, 2015) County Total Change 20102014 Births Deaths Natural Increase (Related Percent Change) Net Migration (Related Percent Change) Duval 25,803 50,031 29,121 20,910 (81.0%) 4,893 (19.0%) St Johns 17,404 7,510 6,166 1,344 ( 7.7%) 16,060 (92.3%)

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45 Chapter 5 Case Studies and Plum Creek Figure 8 Nocatee Location Map

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46 Chapter 5 Case Studies and Plum Creek Figure 9 Nocatee Structures Built Over Time

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47 Chapter 5 Case Studies and Plum Creek Chart 5 Nocatee Structures Built Over Time Chart 6 Nocatee Region Structures Built Over Time 0 100 200 300 400 500 600 7001970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 Structures Built Actual Year Built Nocatee Structures Built Over Time Inside DRI Boundary Within 1 mile of DRI Boundary ----Date of Approval ----0 2000 4000 6000 8000 10000 120001970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 Structures Built Actual Year Built Nocatee Region Structures Built Over Time Inside DRI Boundary Within 15 miles of DRI Boundary ----Date of Approval -----

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48 Chapter 5 Case Studies and Plum Creek Chart 5 and Chart 6 show growth in Nocatee beginning in approximately 2006 and continuing to increase, despite the trend of surrounding structure buildi ng rates decreas ing over the same time period. Table 12 , on page 48 , shows that over 92 percent of the population change bet ween 2010 and 2014 was due to migration in to the county. Harmony Located in central Osceola County, Harmony was approved as a DRI in 1992 . The buildout date is 202 5. It is approv ed for a maximum of 7,200 single and multifamily residential units, 350,000 GSF of commercial space, 500,000 GSF of office space, and 1,000,000 GSF of light industrial space and institutional uses to include, but not limited to, a high school. It is designed as a tradi tional neighborhood development and known for its large percentage of conservation land (Osceola County, Harmony DRI, 2015) . Table 11 Harmony DRI Facts County Osceola Land Area 11, 031 acres Date of DRI Approval 1 0 /2 5 / 1992 Buildout date: 2025 Approved Dwelling Units and Commercial Space 7,200 DU, additional land use above Table 12 Harmony County Population Change Characteristics County Total Change 20102014 Births Deaths Natural Increase (Related Percent Change) Net Migration (Related Percent Change) Osceola 26,868 15,219 7,095 8,124 (30.2%) 18,744 (69.8% )

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49 Chapter 5 Case Studies and Plum Creek Figure 10 Harmony Location Map

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50 Chapter 5 Case Studies and Plum Creek Figure 11 Harmony Structures Built Over Time

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51 Chapter 5 Case Studies and Plum Creek Chart 7 Harmony Structures Built Over Time Chart 8 Harmony R egion Structures Built Over Time 0 20 40 60 80 100 1201970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 Structures Built Actual Year Built Harmony Structures Built Over Time Inside DRI Boundary Within 1 mile of DRI Boundary ----Date of Approval ----0 500 1000 1500 2000 2500 3000 3500 4000 4500 50001970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 Structures Built Actual Year Built Harmony Region Structures Built Over Time Inside DRI Boundary Within 15 miles of DRI Boundary ----Date of Approval -----

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52 Chapte r 5 Case Studies and Plum Creek Charts 7 and 8 show the beginning of development in Harmony started in 2003 and followed trends of the surrounding area. Table 12 , on page 48, shows that close to 70 percent of the population increase between 2010 and 2014, in Osceola County, was due to people moving to the area. Villages The Villages, located in Sumter, Marion and Lake Counties, is a retirement community first approved as a DRI in 1987. Ga ry H. Morse, the man responsible for the vision and growth of The Villages, created what is now known nationwide as a senior citizens ’ utopia. The development has continued to grow, marching south as it acquires new land (Pittman, 2002) . It is approved for 56,823 residential units and 8,555,147 square feet of commercial space. It is comprised of ten districts and was first in the list of top selling developments in the country in 2014 (LaRue, 2015) . T able 13 The Villages DRI Facts Counties Sumter, Marion and Lake Land Area 22,024 acres Date of DRI Approval (first) 07/20/1987 Approved Dwelling Units 56,823 Table 14 The Villages County Populati on Change Characteristics County Total Change 20102014 Births Deaths Natural Increase (Related Percent Change) Net Migration (Related Percent Change) Lake 12,689 12,197 13,664 1,467 (0 . 0%) 14,156 ( 10 0.0%) Marion 6,152 13,358 17,875 4,517 (0.0%) 10,669 (100.0%) Sumter 17,705 1,800 5,096 3,296 (0.0%) 21,001 (100.0%)

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53 Chapter 5 Case Studies and Plum Creek Figure 12 The Villages Location Map

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54 Chapter 5 Case Studies and Plum Creek Figure 13 The Villages Structures Built Over Time

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55 Chap ter 5 Case Studies and Plum Creek Chart 9 The Villages Structures Built Over Time Chart 10 The Villages Region Structures Built Over Time 0 500 1000 1500 2000 2500 3000 3500 4000 4500 50001970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 Structures Built Actual Year Built The Villages Structures Built Over Time Inside DRI Boundary Within 1 mile of DRI Boundary 0 1000 2000 3000 4000 5000 6000 7000 80001970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 Structures Built Actual Year Built The Villages Region Structures Built Over Time Inside DRI Boundary Within 15 miles of DRI Boundary ----Date of Approval -------Date of Approval ----

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56 Chapter 5 Case Studies and Plum Creek Chart 9 and 10 show the growth of The Villages according to structures built per year. Of note , the development within 15 miles has a fairly constant rate of growth up until 2003. Between 2003 and 2011, an increase and then decrease in building rates occurred , however, the rate of building in The Villages did not decrease quite as much as the surrounding area. In fact, more structu res were built within the boundary of The Villages after 2008 than there were built within 15 miles of its border. Table 14, on page 52 , shows the population growth between 2010 and 2014 is wholly att ributed to in migration. ’s The Plum Creek Sector Plan includes approximately 65 thousand acres within Alachua County. The majority of this area would remain timber land with a conservation easement. However, 11,393 acres between Lake Newnan and the city of Hawthorne , referred to as the Windsor Tract, are proposed as employment oriented mixed use development, to include 10,500 dwelling units and 15,500,000 square feet of commercial and industrial space. See Appendix 5 , on page 94 , and Appendix 6 , on page 95, for maps of the proposed sector plan. Table 15 Plum Creek's Envision Alac hua Sector Plan Facts County Alachua Land Area 11,000 acres proposed for development Date of Sector Plan Approval Currently in application process Prop o sed Dwelling Units 10,500

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57 Chapter 5 Case Studies and Plum Creek Table 16 Plum Creek's Envision Alachua Sector P lan County Population Change Characteristics County Total Change 20102014 Births Deaths Natural Increase (Related Percent Change) Net Migration (Related Percent Change) Alachua 3,394 11,528 6,948 4,580 (100%) 1,186 (0.0%) Chart 11 Plum Creek Structures Built Over Time 0 10 20 30 40 50 60 701970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 Structures Built Actual Year Built Plum Creek Structures Built Over Time Within 1 mile of Windsor Tract

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58 Ch apter 5 Case Studies and Plum Creek Chart 12 Plum Creek Region Structures Built Over Time While each case study is unique in its location, size and scale, a few correlations between the data raise some concerns. Looking at Chart 12 , which shows structures built within 15 miles of the Windsor Tract , the rate at which structures have been built has ch anged very little, save the boom in the early 80’s and the bust in 2008 . Interestingly, there is not a strong peak in 2006, like the other regions. The statistics seen in Table 16, on page 57 , are possibly worse than the le vel building rate, as they show a net migration out of Alachua County. This would make the aim of attracting new residents to Plum Creek’s development an effort against the trend. However, The Villages shows it’s possible to create a “build it and they wil l come” situation. 0 500 1000 1500 2000 25001970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 Structures Built Actual Year Built Plum Creek Region Structures Built Over Time Within 15 miles of Plum Creek proposed development area

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59 Chapter 6 Results 6 Results The results of the future land use models are fairly straightforward. The dynamic suitability model adjusted the suitability based on proximity to existing development with each increment of the growth projection, w hile the static model did not. The resulting projected future development was located nearer to existing development in the dynamic suitability model compared to projected future development in the static suitability model . This aligns with the expectation that incrementally increased suitability based on distance to existing development will lead to a development that is closer to existing development. The comparison of the results between the dynamic suitability models, one with and one without Plum Cre ek’s Sector Plan , show that in both cases the projected future development in and around the Windsor Tract is minimal. The purpose of the three models is to show existing and future developed land, for the years 2030, 2040, 2050, and 2060, necessary to a ccommodate population growth projections in Alachua County. The maps corresponding to model 1, based on static suitability criteria, can be seen in Appendix 8 , on page 104 . The maps corresponding to m odel 2, based on dynamic suitability criteria, can be seen in Appendix 9 , on page 109 . The maps corresponding to model 3, based on dynamic suitability criteria including Plum Creek’s proposed sector p lan, can be seen in Appendix 10, on page 114 . The 2060 existing and future land use maps for each of the three models are shown in Figure 14 , Figure 15 , and Figure 16, beginning on page 61 . Existing and future land use for the year 2060 can be seen at the city level in Appendix 12 , on page 127 . The cities shown are Alachua, Archer, Gainesville, Hawthorne, High Springs, Lacrosse, Newberry and Waldo.

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60 Chapter 6 Results The statistical results in the following tables are meant to show how each model varies on two major subjects. Table 17 shows the average distance of a population allocation to previously developed land, which includes previous allocations and existing development. Table 18 shows statistics relevant to the area within and in close proximity to development proposed in Plum Creek’s sector plan. Figure 17, Figure 18, and Figure 19 , beginning on page 64, provide a closer view of the area in and around Plum Creek’s proposed development in the year 2060 for each of the three models. Table 19 compares the suitability value of lands selected for future population allocation against the average suitab ility value of Plum Creek’s land proposed for development. Table 17 Average Distance of Allocated Land to Previous Development Model 2030 Allocation distance to previous development 2040 Allocation distance to previous develop ment 2050 Allocation distance to previous development 2060 Allocation distance to previous development Average Distance / Standard Deviation (meters) 1 106.6 / 94.9 302.9 / 618.9 269.6 / 505.3 258.9 / 597.5 2 106.6 / 94.9 77.8 / 68.6 74.3 / 64.8 72. 9 / 63.5 3 106.7 / 94.9 77.6 / 68.4 72.8 / 64.0 74.7 / 64.9 Table 18 Future Developed Land In and Around Plum Creek Model 2030 Development 2040 Development 2050 Development 2060 Development Development within Plum Creek propo sed development boundary (acres)/ Development within 0.8 miles of Plum Creek proposed development (acres) Total 1 0 / 89 18 / 237 104 / 358 85 / 268 206 / 951 2 0 / 89 14 / 240 87 / 306 102 / 247 202 / 882 3 2,893 / 90 1,285 / 362 2,761 / 368 4,453 / 3 14 11,392 / 1,133 Table 19 Average Suitability Values of Future Developed Land Model Average Suitability of Allocated Land by Year of Allocation Average Suitability of Plum Creek Land Proposed for Development based on 2050 Suitab ility *Model 1 based on 2015 Suitability Values 2030 2040 2050 2060 1 7.899 7.454 7.326 7.199 5.003* 2 7.899 7.490 7.356 7.247 5.083 3 7.899 7.491 7.357 7.248 6.585

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61 Chapter 6 Results Figure 14 2060 Future Development Based on Static Suitability

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62 Chapter 6 Results Figure 15 2060 Fut ure Development Based on Dynamic Suitability

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63 Chapter 6 Results Figure 16 2060 Fu ture Development Based on Dynamic Suitability With Plum Creek Sector Plan

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64 Chapter 6 Results Figure 17 2060 Future Development Based on Static Suitability Focus on Plum Creek

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65 Chapter 6 Results Figure 18 2060 Future Development Based on Dynamic Suitability Focus on Plum Creek

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66 Chapter 6 Results Figure 19 2060 Future Development Based on Dynamic Suitability with Plum Creek Sector Plan Focus on Plum Creek

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67 Chapter 6 Results The fourth model, created after the results of the first three models were obtained, depicts the amount of development in Alachua County at the point when ha lf of the Windsor Tract land is considered optimal for development based on development suitability values. The amount of projected development in this model corresponds with a population growth of 537,509 people, based on current gross urban density. If t he rate of Alachua County’s population growth remains the same as the BEBR growth projections from 2015 to 2060, the additional population of 537,509 people in this model would correspond to the year 2263. The relevant statistics of this growth model can b e seen in Table 20 . The map of existing and future development for this model is shown in Figure 20, on page 68 . Table 20 Model 4 Statistics Model Land selected for development (acres) Population represented by amount of selected land Year in which population allocated will meet current projected growth rates of Alachua County 4 260 , 732 537,509 2263

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68 Chapter 6 Results Figure 20 Future Land Use Model Four – Plum Creek at Fifty Percent Development

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69 Chapter 7 Discussion 7 Discussion T he results in Table 17 , on page 60 , show that suitability is altered such that allocations made with dynamic suit ability are closer to previous development by a factor of betwee n 3.5 and 4, meaning the allocation based on dynamic suitability produces a more condensed , less sprawling pattern of growth. The standard deviation should also be noted because it is based on the distance of values from the average, i mpl ying range . The standard deviation for the static suitability based allocation was between 7.8 and 9.5 times greater than the dynamic suitability based allocation. Keeping in mind this relates to distance of allocated land from previous development, it reveals that allocation based on static suitability is much more dispersed. As the difference between the first and second models is the alteration of a single suitability criterion that prioritizes close proximit y to development, the difference in the results are attributable to the difference in these values . The values will change as alternative processes for determining the suitability range are explored. The values may also be purposely changed to model future land use where development patterns are predicted to be either closer or further from existing development. The main hypothesis of this project is that the Windsor Tract development of Plum Creek’s property, according to their proposed sector plan, would produce a large amount of adjacent development due to the fact that development suitability increases with proximity to existing development. While Table 18, on page 60 , shows that the inclusion of P lum Creek’s development yields 28 percent more development in close proximity to its border than the dynamic suitability model without Plum Creek’s development, the difference in the amount of developed land is only 251 acres. One reason for this small amo unt of developed land may be due to the relatively low suitability of the land in and around the Windsor Tract for development . Interestingly, the amount of land projected for development in the Windsor Tract is less in the dynamic suitability model than t he static suitability

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70 Chapter 7 Discussion model , reinforcing the idea that the allocations made via the dynamic suitability model are less sprawling , as they are located nearer to existing development. As far as the topic of Plum Creek’s proposed development and the relative suitability of the land for development, Table 18, on page 60 , shows how few acres of land are allocated for population in both the static and dynamic suitability models. Where Plum Creek has propose d 11,392 acres that, for the purposes of this project, are generalized as development, the suitability of the static and dynamic models allocate just over 200 acres of development to the same area. It can be concluded from the results of this project that if the areas in and around the Windsor Tract are developed , it will be for reasons not addressed in this analysis. T hose factors may include economic or political drivers. Plum Creek is a corporate business, after all, and financial profit is a factor in their decision to develop . An excerpt from an interview with Plum Creek CEO Rick Holley last year, highlights the ir financial motivations: "One of the key initiatives for the company over the past several years has been the entitlement of our most valuable development properties," Holley told analysts on April 28. "Through the pursuit of these entitlements, we change the very nature of these assets and create long term value for shareholders. We do not intend to pursue vertical development or invest a sign ificant amount of capital into these properties. Rather our strategy is to spend time and effort to move these properties up the value chain through entitlement and capture that value." (Allison, 2014) Political drivers may als o be a factor. This project has one criterion for development that is founded in the political realm; urban reserve and extraterritorial boundaries. While it was incorporated as a proxy for the future utility service boundary, unlike the criteria that desc ribes physical attributes of land, this boundary is movable, with only a political process needed for its alteration.

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71 Chapter 7 Discussion The fourth model was created for two reasons. The first was to depict the relative suitability of the land proposed for development in P lum Creek’s sector plan. At the point when fifty percent of the proposed development area is actually developed, according to the relative rank of current suitability values, it will be the year 2263. The actual date of fifty percent build out of this prop erty, if it ever reaches fifty percent build out, is most likely much further in the future because the fourth model is an allocation based on static suitability which projects more sprawl than if a dynamic suitability were performed through the year 2260. The other reason this date is most likely further away is because the development density is projected at current rates. If the gross urban density increases, the amount of land needed for future population will decrease. This means that less land will be requir ed for future population growth, which, in turn, means that a higher population allocation quantity would be required to cover fifty percent of Plum Creek’s proposed development area, corresponding to a date further away than 2263. The other reason the fourth model was created was to show how and when land proposed for development in Plum Creek’s sector plan would develop without the sector plan being implemented. A landowner near the proposed sector plan development area may believe that developmen t will happen whether the sector plan is carried out or not. Th e fourth model provides one estimate as to when and to what degree that non sector plan development may happen; in the year 2263, when the current population of Alachua County has more than tripled, the area considered for development under Plum Creek’s sector plan will be half built. In summary , the dynamic suitability model projects development closer to existing development compared to the static suitability model. The influence of Plum Cree k’s sector plan on the area adjacent to the Windsor Tract is not as great as hypothesized, simply because the development suitability of the

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72 Chapter 7 Discussion land in and around the Windsor Tract is relatively low compared to the rest of Alachua County . The fourth model dem onstrates how low the suitability of the Windsor Tract is by showing how much of the rest of Alachua County is at or above the average development suitability of the Windsor Tract.

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73 Chapter 8 Conclusions 8 Conclusion s The area in and around Plum Creek’s proposed sector plan development is a poor candidate for development according to the suitability modeling performed in this project . The future land use models do not project much, if any, development in or around the Windsor Tract be cause the amount of lands of higher development suitability, most of which are located in the western portion of the county, are plentiful enough to acc ommodate the projected population growth through 2060 . If projections were to extend beyond the 2060 ran ge , the distribution of developed land may change. However, the fourth model, although basic in its assumptions, shows that much of the available land in the county would be developed sooner than Plum Creek’s Windsor Tract . Projections that extend beyond the 2060 range may also show an increasing divergence between results of the static and dynamic suitability models as more of the land with higher suitability for development is earmarked. The divergence is due to the process of dynamic suitability continuo usly increas ing the development suitability for areas in close proximity to development while projections based on static suitability sprawl away from existing development . Alachua County’s Growth Management department has made statements consistent with the results of this project, as well: Due to the extensive presence of poorly drained soils, floodplains, wetlands, high water table, downstream impaired lakes, and the high capital and maintenance costs to provide sufficient infrastructure and public ser vices to offset these constraints, the County’s current comprehensive plan policies encourage new development to be located where adequate infrastructure exists and natural resource impacts can be minimized. (Alachua County Gr owth Management, 2015, p. 6)

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74 Chapter 8 Conclusions Plum Creek lauds its past TDR deals as directing future development opportunity to areas closer to existing development and supporting infrastructure, but not in the instance of their Envision Alachua Sector Plan. As mention ed in the literature review, the sector planning process is meant to limit sprawl by requiring large developments to plan for strong urban form and balanced transportation networks. The development suitability of the land surrounding the Windsor Tract is l ow, making development sub optimal; meaning sprawling development at the periphery of the Windsor Tract is not likely, according to the results of the future land use modeling in this project. While this is good news for those desiring limited influence of Plum Creek’s Sector Plan on surrounding areas, it comes along with low development suitability values within the border of the Windsor Tract. T he hypothesis of this project , that a large amount of secondary devel opment will be the result of Plum Creek’s proposed sector plan , may not be supported by the results of this project . T he outcome may be different if applied to other proposed areas of large development. If a large development proposed far from existing dev elopment had relatively high development suitability , the difference in static and dynamic modeling may be more significant. While many steps from the LUCIS book were used, the substitution of the Slice tool in place of the Rec lassify tool was critical to the accuracy of each population allocation. The creation of this pr ocess was a result of necessity. In the event that a more appropriate process does not exist, the slicing process should be used whenever integer value suitabil ity results in too coarse a result. T he smaller suitability increments allowed better accuracy of allocation and could possibly be applied in situations beyond suitability or population allocation , where greater accuracy is desired .

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75 Chapter 8 Conclusions Another departure of t his project from the LUCIS book is the consideration, or lack, in this project, of the suitability of conservation and agriculture priorities due to the anticipation that the creation of a conflict grid and subsequent identification of land preference woul d favor agriculture or conservation and automatically bar consideration of Plum Creek’s land to development. While conflict grid creation is important for certain land use modeling , the implementation in this project would not have allowed the comparison o f proposed development to projected development. There were simplifications of some processes in this project because either their inclusion would not have contributed to the direction of the main hypothesis or because the inclusion would have required dat a projections beyond the scope of this work. At the time of this writing, the generalized land use proposed by Plum Creek in their sector plan is all that has been made accessible to the public. As more specific locations and classifications of land use are disseminated, more accurate modeling can be performed. Future study may also incorporate elements not included in this work, such as economic factors, in projecting future land use for this area. While this project addresses suitability of the area proposed for development by Plum Creek, future study may look at the other Plum Creek holdings in Alachua County as possible alternative sites for development. Future study may build on this project with conf lict grid creation and analysis, allow ing for the proposal of conservation and agriculture land uses in and around Plum Creek’s Windsor Tract. Future study may also look more closely at how the language of the sector planning statute pays homage to reducing sprawl and environm ental impacts, and how this may be at odds with the fact that

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76 Chapter 8 Conclusions sector plans proposed in Florida are primarily greenfield development; a source of the disagreement between Plum Creek’s Sector Plan and the Alachua County Growth Management Department.

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77 Appendix 1 Developed a nd Undeveloped Land Category Assignment Append 1 LUCODE DEVELOPED (1) UNDEVELOPED (0) DESCRIPT 0 0 VACANT RESIDENTIAL 1 1 SINGLE FAMILY 2 1 MOBILE HOMES 3 1 MULTI FAMILY 4 1 CONDOMINIA 5 1 COOPERATIVES 6 1 RETIREM ENT HOMES 7 1 BOARDING HOMES (INSTITUTIONAL) 8 1 MULTI FAMILY LESS THAN 10 UNITS 9 1 UNDEFINED RESERVED FOR DOR 10 0 VACANT COMMERCIAL 11 1 STORES ONE STORY 12 1 MIXED USE, I.E., STORE AND OFFICE 13 1 DEPARTMENT STORES 14 1 SUPERMARKET 15 1 REGION AL SHOPPING MALLS 16 1 COMMUNITY SHOPPING CENTERS 17 1 ONE STORY NON PROFESSIONAL OFFICES 18 1 MULTI STORY NON PROFESSIONAL OFFICES 19 1 PROFESSIONAL SERVICE BUILDINGS 20 1 AIRPORTS, MARINAS, BUS TERMINALS, AND PIERS 21 1 RESTAURANTS, CAFETERIAS 22 1 DRIVE IN RESTAURANTS 23 1 FINANCIAL INSTITUTIONS 24 1 INSURANCE COMPANY OFFICES 25 1 REPAIR SERVICE SHOPS 26 1 SERVICE STATIONS 27 1 AUTOMOTIVE REPAIR, SERVICE, AND SALES 28 1 PARKING LOTS, MOBILE HOME SALES 29 1 WHOLESALE, MANUFACTURING, AND PROD UCE OUTLETS 30 1 FLORIST, GREENHOUSES 32 1 ENCLOSED THEATERS, AUDITORIUMS

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78 Appendix 1 Developed and Undeveloped Land Category Assignment LUCODE DEVELOPED (1) UNDEVELOPED (0) DESCRIPT 33 1 NIGHT CLUBS, BARS, AND COCKTAIL LOUNGES 34 1 BOWLING ALLEYS, SKATING RINGS, ENCLOSED ARENAS 35 1 TOURIST ATTRACTIONS 36 1 CAMPS 37 1 RACE HORSE, AUTO, AND DOG TRACKS 38 1 GOLF COURSES 39 1 HOTELS, MOTELS 40 0 VACANT INDUSTRIAL 41 1 LIGHT MANUFACTURING 42 1 HEAVY MANUFACTURING 43 1 LUMBER YARDS, SAWMILLS, PLANNING MILLS, 45 1 CANNERIES, DISTILLERIES, AND WINERIES 46 1 OTHER FOOD PROCESSING 47 1 MINERAL PROCESSING 48 1 WAREHOUSES, AND DISTRIBUTION CENTERS 49 1 INDUSTRIAL STORAGE (FUEL, EQUIP, AND MATERIAL) 50 0 IMPROVED AGRICULTURE 51 0 CROPLAND SOIL CLASS 1 52 0 CROPLAND SOIL CLASS 2 53 0 CROPLAND SOIL CLASS 3 54 0 TIMBERLAND 55 0 TIMBERLAND 56 0 TIMBERLAND 57 0 TIMBERLAND 58 0 TIMBERLAND 59 0 TIMBERLAND 60 0 GRAZING LAND SOIL CLASS 1 61 0 GRAZING LAND SOIL CLASS 2 62 0 GRAZING LAND SOIL CLASS 3 63 0 GRAZING LAND SOIL CLASS 4 64 0 GRAZING LAND SOIL CL ASS 5 65 0 GRAZING LAND SOIL CLASS 6 66 0 ORCHARD, GROVES, CITRUS 67 0 POULTRY, BEES, TROPICAL FISH, RABBITS, ETC

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79 Appendix 1 Developed and Undeveloped Land Category Assignment LUCODE DEVELOPED (1) UNDEVELOPED (0) DESCRIPT 68 0 DAIRIES, FEED LOTS 69 0 ORNAMENTALS, MISC. AGRICULTURE 70 0 VACANT INSTITUTIONAL 71 1 CHURCHES 72 1 PRIVATE SCHOOLS 73 1 PRIVATE HOSPITALS 74 1 HOMES FOR AGED 75 0 ORPHANAGES 76 0 MORTUARIES, CEMETERIES 77 0 CLUBS, LODGES, AND UNION HALLS 78 0 SANITARIUMS, CONVALESCENT, AND BEST HOMES 79 0 CULTURAL ORGANIZATIONS 80 0 UNDEFINE D 82 0 FOREST, PARK, AND RECREATIONAL AREAS 83 1 PUBLIC SCHOOLS 84 1 COLLEGES 85 1 PUBLIC HOSPITALS 86 0 OTHER COUNTIES 87 1 OTHER STATE 88 0 OTHER FEDERAL 89 1 OTHER MUNICIPAL 90 0 GOV. OWNED LEASED BY NON GOV. LESSEE 91 1 UTILITIES 92 0 MINING , PETROLEUM, AND GAS LANDS 94 0 RIGHTS OF WAY STREETS, ROADS, AND CANALS 95 0 RIVERS, LAKES, AND SUBMERGED LANDS 96 0 SEWAGE DISPOSAL, BORROW PITS, AND WETLANDS 97 0 OUTDOOR RECREATIONAL 98 0 CENTRALLY ASSESSED 99 0 ACREAGE NOT ZONED FOR AGRICULTURAL 100 0 PARCELS WITH NO VALUES 999 0 NO DATA AVAILABLE

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80 Appendix 2 Data Used 2 Goal Data and Source Description Identify lands proximal to developed areas Parcels_14 (see Appendix 1 for developed c ategories) Source: Florida Geographic Data Library (FGDL) via www.fgdl.org Parcel boundaries with each parcel's associated tax information from the Florida Department of Revenue's tax database Identify areas with high road density rds2401 Source: FGDL Roa dways from the U.S. Geological Survey Identify lands of approved DRIs and PUDs pud_2009q4 and DRI_DEO_2014Q1 Source: FGDL Planned Unit Developments (PUD) in the State of Florida; Developments of Regional Impacts (DRI) in the State of Florida Identify ar eas without wetlands nhd24waterbody_dec12.shp (selected by field “DESCRIPT” = “SWAMP/MARSH” or “RESERVIOR”) Source: FGDL National Hydrography Dataset – Hydrographic Waterbody Features Identify lands proximal to major roads Majrds_jan15 Source: FGDL Flori da Department of Transportation Roads Characteristics Inventory Derived Major Roads – Statewide, January 2015 Identify areas with well drained soil Nrcs_soils_jun12 Source: FGDL Digital soil survey data developed by the National Cooperative Soil Surv ey Identify lands within urban service areas Urban Reserve Boundary of Alachua County Source: Alachua County Growth Management via www.arcgis.com Urban and Extra Territorial Reserves of Alachua County, FL Identify areas without flood hazards DFIRM_FLDHA Z_MAR14 Source: FGDL Flood hazard areas that are or will be depicted on the Flood Insurance Rate Map (FIRM) from the Federal Emergency Management Agency Identify lands with mild or moderate slopes Topo_01 Source: FGDL Countywide 5 foot contour lines from USGS quadrangle maps

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81 Appendix 2 Data Used Data used for the purpose of excluding lands to development allocation Area to be avoided Data and Source Description Existing Conservation Land FLMA_DEC14 Source: FGDL Florida Managed Areas – December 2014, published by Florida N atural Areas Inventory (FNAI) Open Water nhd24waterbody_dec12.shp (selected by field “DESCRIPT” = “LAKE/POND”) Source: FGDL National Hydrography Dataset – Hydrographic Waterbody Features Rights of Way Parcels_14 Source: FGDL The NoData between the parce l boundaries corresponds to the rights of way of existing roadways Additional data used Additional data need Data and Source Description Alachua County Study Area CNTBND_JUL11 Source: FGDL U.S. Census Bureau published boundaries of Florida counties P lum Creek Boundary and Land Use Designations derived from Proposed Sector Plan plumcreek071614 Source: Alachua County Growth Management via www.arcgis.com Plum Creek Boundary and Land Use Designations – Current Conservation, Potential Conservation, Agric ulture, Rural, Urban Land Uses proposed in Sector Plan

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82 Appendix 3 Criteri on Suitability and Resulting 2015 Overall Suitability 3

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83 Appendix 3 Criterion Suitability and Resulting 2015 Overall Suitability

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84 Appendix 3 Criterion Suitability and Resulting 2015 Overall Suitability

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85 Appendix 3 Criterion Suitability and Resulting 2015 Overall Suitability

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86 Appendix 3 Criterion Suitability and Resulting 2015 Overall Suitability

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87 Appendix 3 Criterion Suitability and Resulting 2015 Overall Suitability

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88 Appendix 3 Criterion Suitability and Resulting 2 015 Overall Suitability

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89 Appendix 3 Criterion Suitability and Resulting 2015 Overall Suitability

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90 Appendix 3 Criterion Suitability and Resulting 2015 Overall Suitability

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91 Appendix 3 Criterion Suitability and Resulting 2015 Overall Suitability

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92 Appendix 4 Population Growth Projections and Allocations 4 ions Table of Projected Population for Alachua County – Medium Estimate (Bureau of Economic and Business Research (BEBR), University of Florida, 2014) Year Population 2013 248,002 2015 252,600 2020 265,700 2030 289,200 2 040 306,800 2050 * 328,480 2060 * 350,160 *BEBR projection ends with 2040 projection . Projections for 2050 and 2060 calculated from average yearly growth from 201 5 to 2040, calculated at 2,168, multiplied by 10 and 20, respectively, and added to the 2040 Projection. Model 1 – Population Allocation Based on Static Suitability Year Population Cells Required for Total Development Cells Selected for Total Development Total Total Growth 2013 248,002 ------2030 289,200 41,198 808,728 787,723 2040 3 06,800 58,798 1,154,221 1,108,087 2050 * 328,480 80,478 1,579,806 1,578,709 2060 * 350,160 102,158 2,005,391 1,996,119 Model 2 – Population Allocation Based on Dynamic Suitability Year Population Cells Required for Incremental Development Cells Selected for Incremental Development Total Incremental Growth 2013 248,002 ------2030 289,200 41,198 808,728 787,723 2040 306,800 17,600 345,493 344,335 2050 * 328,480 21,680 425,585 424,438 2060 * 350,160 21,680 425,585 417,926 Total 102,158 2,005,3 91 1,974,422

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93 Appendix 4 Population Growth Projections and Allocations Model 3 – Population Allocation Based on Dynamic Suitability with Plum Creek Proposed Sector Plan Year Population Cells Required for Incremental Development Cells Selected for Incremental Development Total Incremental Growth 2013 248, 002 ------2030 289,200 41,198 808,728 788,703 2040 306,800 17,600 345,493 344,907 2050 * 328,480 21,680 425,585 418,299 2060 * 350,160 21,680 425,585 424,797 Total 102,158 2,005,391 1,976,706

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94 Appendix 5 Plum Creek Property and Proposed Sector Plan Land Use 5

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95 Appendix 6 Plum Creek Sector Plan Development Areas 6

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96 Appendix 7 Dynamic Suitability Criterion with Plum Creek Sector Plan 7

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97 Appendix 7 Dynamic Suitability Criterion with Plum Creek Sector P lan

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98 Appendix 7 Dynamic Suitability Criterion with Plum Creek Sector Plan

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99 Appendix 7 Dynamic Suitab ility Criterion with Plum Creek Sector Plan

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100 Appendix 7 Dynamic Suitability Criterion with Plum Creek Sector Plan

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101 Appendix 7 Dynamic Suitability Criterion with Plum Creek Sector Plan

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102 Appendix 7 Dynamic Suitability Criterion with Plum Creek Sector Plan

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103 Appendix 7 Dynamic Suitability Criterion with Plum Creek Sector Plan

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104 Appendix 8 Model 1 Future Growth Projections 8

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105 Appendix 8 Model 1 Future Growth Projections

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106 Appendix 8 Model 1 Future Growth Projections

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107 App endix 8 Model 1 Future Growth Projections

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108 Appendix 8 Model 1 Future Growth Projections

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109 Appendix 9 Model 2 Future Growth Projections 9

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110 Appendix 9 Model 2 Future Growth Projections

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111 Appendix 9 Model 2 Future Growth Projections

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112 Appendix 9 Model 2 Future Growth Projections

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113 Appendix 9 Model 2 Future Growth Projections

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114 Appendix 10 Model 3 Future Growth Proj ections 10

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115 Appendix 10 Model 3 Future Growth Projections

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116 Appendix 10 Model 3 Future Growth Projections

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117 Appendix 10 Model 3 Future Growth Projections

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118 Appendix 10 Model 3 Future Growth Projections

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119 Appendix 11 Overall Static Suitability and Overall Dynamic Suitability by Decade 11

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120 Appendix 11 Overall Static Suitability and Overall Dynamic Suitab ility by Decade

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121 Appendix 11 Overall Static Suitability and Overall Dynamic Suitability by Decade

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122 Appendix 11 Overall Static Suitability and Overall Dynamic Suitability by Decade

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123 Appendix 11 Overall Static Suitability and Overal l Dynamic Suitability by Decade

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124 Appendix 11 Overall Static Suitability and Overall Dynamic Suitability by Decade

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125 Appendix 11 Overall Static Suitability and Overall Dynamic Suitability by Decade

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126 Appendix 11 Overall Static Suitab ility and Overall Dynamic Suitability by Decade

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127 Appendix 12 2060 Future Land Use Model 1 and Model 2 City Scale Maps 12 Maps

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128 Appendix 12 2060 Future Land Use Model 1 and Model 2 City Scale Maps

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129 Appendix 12 2060 Future Land Use Model 1 and Model 2 City Scale Maps

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130 Appendix 12 2060 Future Land Use Model 1 and Model 2 City Scale Maps

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131 Appendix 12 2060 Future Land Use Model 1 and Model 2 City Scale Maps

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132 Appendix 12 2060 Future Land Use Model 1 and Model 2 City Scale Maps

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133 Appendix 12 2060 Future Land Use Model 1 and Model 2 City Scale Maps

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134 Appendix 12 2060 Future La nd Use Model 1 and Model 2 City Scale Maps

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135 Appendix 12 2060 Future Land Use Model 1 and Model 2 City Scale Maps

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136 Appendix 12 2060 Future Land Use Model 1 and Model 2 City Scale Maps

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137 Appendix 12 2060 Future Land Use Model 1 and Model 2 City Scale Maps

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138 Appendix 12 2060 Future Land Use Model 1 and Model 2 City Scale Maps

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139 Appendix 12 2060 Future Land Use M odel 1 and Model 2 City Scale Maps

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140 Appendix 12 2060 Future Land Use Model 1 and Model 2 City Scale Maps

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141 Appendix 12 2060 Future Land Use Model 1 and Model 2 City Scale Maps

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142 Works Cited

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143 Works Cited Alachua C ounty Florida. (2015). Plum Creek Envision Alachua Sector Plan. Retrieved from Alachua County Florida Growth Management: https://growth management.alachua.fl.us/development_services/plumcreek/documents/09162014WorkshopQ uestionResponses.pdf Alachua County Growth Management. (2015). Plum Creek Envision Alachua Sector Plan. Retrieved from Alachua County Growth Management: https://growth management.alachua.fl.us/development_services/plumcreek/documents/plumCreekQuestions 092214meeting.pdf Allison, D. (2014, Ap ril 30). Plum Creek Timber Co. developing 2,000 acre 'mega site' in south Georgia. Retrieved April 2015, from Atlanta Business Chronicle: http://www.bizjournals.com/atlanta/news/2014/04/30/plum creek timber co developing2 000 acre mega.html Burchell, R. W . (2005). Sprawl costs: economic impacts of unchecked development. Washington, DC: Island Press. Bureau of Economic and Business Research (BEBR), University of Florida. (2014). Projections of Florida population by county. Gainesville, FL: BEBR. Bureau of E conomic and Business Research (BEBR), University of Florida. (2015, January 20). Florida Estimates of Population 2014. Retrieved from Office of Economic and Demographic Research: http://edr.state.fl.us/Content/population demographics/data/ Carr, M. H., & Z wick, P. D. (2006). Florida 2060: A Population Distribution Scenario for the State of Florida. Gainesville, Florida: University of Florida GeoPlan Center. Carr, M. H., & Zwick, P. D. (2007). Smart landuse analysis: The LUCIS model landuse conflict identi fication strategy. Redlands, CA: ESRI Press. Community Affairs. (2011, September). The Development of Regional Impact Process . Retrieved June 2015, from The Florida Senate: http://www.flsenate.gov/PublishedContent/Session/2012/InterimReports/2012 114ca.pdf D.N. Bengston et al. (2005). An analysis of the public discourse about urban sprawl in the United States: Monitoring concern about a major threat to forests. Forest Policy and Economics , 745 756. Deyle, R. E., & Smith, R. A. (1998). Local gonvernment comp liance with state planning mandates: The effects of state implementation in Florida. Journal of the American Planning Association, 64 (4) , 457 469.

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144 Works Cited Envision Alachua. (2015). Envision Alachua Sector Plan Application. Retrieved from Envision Alachua: http:// www.envisionalachua.com/files/managed/Document/597/IV_A_CONSISTENCY_WITH_TH E_COMPREHENSIVE_PLAN.pdf Envision Alachua. (2015). Envision Alachua Sector Plan Application. Retrieved from Envision Alachua: http://www.envisionalachua.com/files/managed/Document/6 12/IV_H_1_PHASE_1_SUMMARY. pdf Fla. Stat. 163.3164. (2012). Fla. Stat. 163.3245. (2014). Fla. Stat. 380.06. (2014). LaRue, T. (2015, January 05). The Top Selling Master Planned Communities of 2014 . Retrieved from RCLCO: http://www.rclco.com/advisory t op selling mpc 2014?utm_source=January+6%2C+2015+ +Top Selling+MPCs+of+2014&utm_campaign=Advisory RCLCO 2014 Top MPC 2015 01 06&utm_medium=email Nicolaides, B. M., & Wiese, A. (2006). The Suburb Reader. New York: Routledge. Nocatee. (2015). Nocatee . Retrie ved from Nocatee: http://nocatee.com/ O'Brien, M. G. (2010). Heartland 2060: Integrating Conservation and Development in South Central Florida. Master's Thesis, University of Florida. Osceola County. (2015). Celebration DRI . Retrieved from Osceola County: http://www.osceola.org/agencies departments/community development/offices/planningoffice/dcidri maps documents/celebration dri.stml Osceola County. (2015). Harmony DRI . Retrieved from Osceola County: http://www.osceola.org/agencies departments/community development/offices/planningoffice/dcidri maps documents/harmony dri.stml Pittman, C. (2002, July 07). One Man's Crusade . Retrieved from St. Petersburg Times Online: http://www.sptimes.com/2002/07/07/news_pf/State/One_man_s_crusade.shtml Plum Creek. (201 5). Case Study: Marion County, Florida. Retrieved April 2015, from Plum Creek Conservation: http://www.plumcreek.com/PlumCreek/media/Library/PDFs/Resources/Fact Sheets/FL Marion County.pdf Plum Creek. (2015). Development . Retrieved April 2015, from Plum Cr eek: http://www.plumcreek.com/land/development

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145 Works Cited Plum Creek. (2015). Plum Creek in Florida . Retrieved April 2015, from Plum Creek: http://www.plumcreek.com/about/our land working forests/florida Powell, D. L., Hunter Jr., G. K., & Rhodes, R. M. (2014). Sector Plans. Tallahassee, FL: The Florida Bar. Squires, G. D. (2002). Urban sprawl: causes, consequences & policy responses. Washington, D.C.: The Urban Institute Press. The Florida Senate. (2011, September). The Development of Regional Impact Process. Re trieved 02 02, 2015, from The Florida Senate: http://www.flsenate.gov/PublishedContent/Session/2012/InterimReports/2012 114ca.pdf -