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Optimizing transportation network based on ecological suitability

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Title:
Optimizing transportation network based on ecological suitability an innovative nonmotorized approach to integrate transportation with urban ecology
Creator:
Yang, Ruiyuan ( author )
Language:
English
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1 online resource (89 pages) : illustrations ;

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Subjects / Keywords:
Architecture master's research project, M.S.A.S
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government publication (state, provincial, terriorial, dependent) ( marcgt )
bibliography ( marcgt )
theses ( marcgt )
non-fiction ( marcgt )

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Abstract:
With the increasing conflictions between development and ecology, sustainable development has been widely applied to multiple actions. However, only very few research focus on integrating transportation with ecology, where the nonmotorized approaches to address this issue have long been a research gap. This research was conducted to generate an optimized transportation network that consists of both nonmotorized routes based on ecological suitability and existing road network to make transportation network both efficient and environmentally friendly. Multiple transportation assessment approaches, such as topological analysis, ecological impact analysis, and network analysis, were then applied to test its service efficiency based on GIS and Space Syntax. The result shows that the ecologically based transportation network can improve the existing one topologically and satisfyingly serve travel demands in study area efficiently.
Bibliography:
Includes bibliographical references.
General Note:
Sustainable Development Practice (MDP) Program final field practicum report
Statement of Responsibility:
by Ruiyan Yang.

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University of Florida
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University of Florida
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All applicable rights reserved by the source institution and holding location.
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035646120 ( ALEPH )
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LD1780.1 2017 ( lcc )

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University of Florida Theses & Dissertations

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OPTIMIZING TRANSPORTATION NETWORK BASED ON ECOLOGICAL SUITABILITY: AN INNOVATIVE NONMOTORIZED APPROACH TO INTEGRATE TRANSPORTATION WITH URBAN ECOLOGY By RUIYUAN YANG A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE IN ARCHITECTURAL STUDIES UNIVERSITY OF FLORIDA 2017

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2017 Ruiyuan Y ang

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To my country and my family

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4 ACKNOWLEDGMENTS Foremost, I would like to express my sincere gratitude to my committee chair Professor Walters for his patience, motivation and immense knowledge. His valuable guidance helped me to tear the vitals out of a subject, think beyond the appea rance more comprehensive ly and inspired me to a broader world of both career and life. Besides, I would like to acknowledge the rest of my thesis committee: Professor Steiner for her encouragement, insightful comments on specific research directions, and p rofessor Volk, for his enthusiasm, continuous support, and professional guidance in all the time of the research and writing of my thesis. I would also like to thank Professor Latimer for his patience and technical support that contribute to the analysis p art of my research. Finally, I must express my profound gratitude to my family and friends for providing me with unfailing support and continuous encouragement throughout my study.

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5 TABLE OF CONTENTS page ACKNOWLEDGMENTS ................................ ................................ ................................ .. 4 LIST OF TABLES ................................ ................................ ................................ ............ 7 LIST OF FIGURES ................................ ................................ ................................ .......... 8 LIST OF ABBREVIATIONS ................................ ................................ ............................. 9 ABSTRACT ................................ ................................ ................................ ................... 10 CHAPTER 1 INTRODUCTION ................................ ................................ ................................ ........ 11 2 LITERATURE REVIEW ................................ ................................ .............................. 16 Identification Ecological Priority ................................ ................................ .............. 16 Ecological priority research ................................ ................................ .............. 16 Indicator s and tools applied ................................ ................................ .............. 19 Transportation Planning ................................ ................................ .......................... 22 Research development ................................ ................................ .................... 22 Why nonmotorized transportation ................................ ................................ ..... 23 Transportation Network Assessment ................................ ................................ ...... 25 Tools and where applicable ................................ ................................ .............. 25 Topological analysis ................................ ................................ ................... 25 Geometrical analysis ................................ ................................ .................. 26 Impact assessment ................................ ................................ .................... 26 Systematic analysis ................................ ................................ ................... 27 Indicators ................................ ................................ ................................ .......... 28 Topological indicators ................................ ................................ ................ 28 Geometrical indicators ................................ ................................ ............... 29 Systematic indicators ................................ ................................ ................. 32 Summary ................................ ................................ ................................ .......... 32 Research gap ................................ ................................ ............................. 32 Tools and indicators for comparative analysis ................................ ........... 33 3 METHODOLOGY A ND DATA ................................ ................................ .................... 34 Applicable Tools ................................ ................................ ................................ ..... 34 Identify ecological suitability map (ESM) ................................ .......................... 35 Identify traffic demand areas ................................ ................................ ............ 36 Get potential nonmotorized routes ................................ ................................ ... 37 Comparative analysis between OTN and ETN ................................ ................. 38 Data and Sources ................................ ................................ ................................ ... 38

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6 Indicators and Weightings ................................ ................................ ....................... 39 Criteria and Asse ssment ................................ ................................ ......................... 41 To select potential traffic demand areas ................................ ........................... 41 To select nonmotorized route for an OTN ................................ ........................ 42 4 RESEARCH PROCESS AND RESULTS ................................ ................................ ... 4 6 Study Area ................................ ................................ ................................ .............. 46 Overview ................................ ................................ ................................ .......... 46 Population ................................ ................................ ................................ ........ 48 Transportation facts ................................ ................................ .......................... 50 Identify Ecological Suitability Maps ................................ ................................ ......... 53 Data based ESM ................................ ................................ .............................. 54 Tool based ESM ................................ ................................ ............................... 55 Identify Traffic Demand Areas ................................ ................................ ................ 56 Identify Applicable Nonmotorized Routes ................................ ............................... 58 Comparative Analysis ................................ ................................ ............................. 61 Ecological impa ct ................................ ................................ ............................. 61 Topological relationship ................................ ................................ .................... 63 Service efficiency ................................ ................................ ................................ .... 66 Network analysis ................................ ................................ .............................. 66 Context suitability ................................ ................................ ............................. 68 5 CONCLUSION AND DISCUSSION ................................ ................................ ............ 70 Conclusion ................................ ................................ ................................ .............. 70 Optimized routes can improve transportation network topologically ................. 70 Optimized transportation network can serve tr affic demands with efficiency .... 70 Limitations ................................ ................................ ................................ ............... 70 Confliction Between Ecological Priority and Built Environment ............................... 71 Feasibility of Practical Projects ................................ ................................ ............... 72 Further Work ................................ ................................ ................................ ........... 73 For better nonmotorized ro utes ................................ ................................ ........ 73 For facilitating implementation ................................ ................................ .......... 74 APPENDIX 1 IMPACT ASSESSMENT ................................ ................................ ............................ 75 2 CENSUS DATA ................................ ................................ ................................ .......... 77 3 TRANSPORTATION STATISTICS ................................ ................................ ............. 79 LIST OF BIBLIOGRAPHY ................................ ................................ ............................. 80 LIST OF REFERENCE ................................ ................................ ................................ .. 88

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7 LIST OF TABLES T able page Contents Table 1 Indicators to identify ecological priority in precedent studies ............................ 21 Table 2 Transportation research development ................................ .............................. 22 Table 3 Definitions of each indicator in Space Syntax (Hillier & Hanson, 1989) ........... 29 Table 4 Overview of software and tools for each step of analysis ................................ 35 Table 5 Identify potential traffic demand areas ................................ .............................. 37 Table 6 Suitability objectives, indicators, and weightings to ident ify ecological priority areas ................................ ................................ ................................ ....... 40 Table 7 Land suitability classification for nonmotorized routes ................................ ...... 43 Table 8 Suitability objectives, indicators, and weightings to identify priority for nonmotorized routes ................................ ................................ ........................... 44 Table 9 Indicators and Methodologies for TIA Guidance ................................ ............... 75 Table 10 Preferred software for different types of analysis ................................ ........... 76 Table 11 Population change among city/town level in Alachua County ........................ 77 Table 12 Socio Economic data summary 2010 ................................ ............................. 77 Table 13 Journey to Work Mode Split (2000) ................................ ................................ 79 Table 14 Tr avel Time in Minutes (percent of workers) ................................ .................. 79

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8 LIST OF FIGURES Figure page Fig. 1 Ecological conservation area in Alachua County ................................ ................. 1 2 Fig. 2 Ecological conservation area in Alachua County ................................ ................. 12 Fig. 3 Ecological conservation area in Alachua County ................................ ................. 47 Fig. 4 Ecological conservation area in Alachua County ................................ ................. 47 Fig. 5 Population density in Alachua County ................................ ................................ 49 Fig. 6 Census of City/Towns population in Alachua County (2010) ............................... 50 Fig. 7 Population increase in Gainesville ................................ ................................ ....... 50 Fig. 8 Travel mode change in Florida (2006 2015) ................................ ....................... 51 Fig. 9 Nonmotorized travel mode change in Florida (2006 2015) ................................ 52 Fig. 10 Annual average travel mode proportion in state, county, and city scale ............ 52 Fig. 11 Examples of single indicator map for ecological suitability identification ........... 53 Fig. 14 ESM based on cell statistics maximum approach ................................ ............. 55 Fig. 15 ESM based on cell statistics average approach ................................ ................ 56 Fig. 21 Fire corridor in San Felasco State Hammock Preserve ................................ ..... 60 Fig. 22 Recreational activities with limited impact in Paynes Prairie Preserve .............. 60 Fig. 22 Axial map for existing road network, ETN, and OTN considering total depth, total connectivity, and integration ................................ ................................ ....... 63 Fig. 23 The comp arison of total value among four indicators ................................ ........ 64

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9 LIST OF ABBREVIATIONS ESM ESM refers to ecological suitability map, which is produced based on multiple indicators that impact on ecological suitability, and then calculate d the overall value of each cell with weightings as a suitability map ETN ETN refers to the existing transportation network that consists both road network and trails and cycling lanes that connected to the road network. The ETN was the existing condit ion for comparison. OTN The Optimized transportation network consists of two parts: one is existing road network that is the same as in the ETN, the other part is generated based on ecological suitability and screening criteria. Both parts were integrate d together as optimized transportation network and assess the extent of improvement.

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10 Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for Degree of M as ter of Science in Architectural Studies OPTIMIZING TRANSPORTATION NETWORK BASED ON ECOLOGICAL SUITABILITY: AN INNOVATIVE NONMOTORIZED APPROACH TO INTEGRATE TRANSPORTATION WITH URBAN ECOLOGY By Ruiyuan Yang July 2017 Chair: Bradley Walters Cochair: Ruth L. Steiner, Michael Ives Volk Major: Architecture With the increasing conflictions between development and ecology, sustainable development has been widely applied to multiple actions. However, only very few research focus on integrating transportation with ecology, where the nonmotorized approaches to address this issue have long been a research gap. This research was conducted to generate an optimized transportation network that consists of both nonmotorized routes based on ecological suitability and existing road network to make transportation network both efficient and environmentally friendly. M ultiple transportation assessment approaches, such as topological analysis, ecological impact analysis, and network analysis, were then applied to test its s ervice efficiency based on GIS and Space Syntax. The result shows that the ecological ly based transportation network can improve the existing one topological ly and satisfy ingly serve travel demands in study area efficiently.

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11 CHAPTER 1 INTRODUCTION Wit h the concept of sustainable development becoming extensively acknowledged and commonly applied to practical experience, natural area conservation gains increasing concern. However, we are so cautious about the pre servation that most of the conservation s w ere passively done by avoiding construction and development in such area. Such passive attitude is tolerable in rural areas where natural landscape is dominating, while in urban areas, admittedly, natural patches such as preserves and wetlands play importa nt roles that benefit both ecosystem and human health. Such areas leave unincorp o rated holes in built environment that result in inconvenience for urban life and threaten to vulnerable urban ecology. Such confliction is particularly prominent when comes d own to the transportation network. Optimistically, road network planning, or most of the network plan, such as route selection, is designed to avoid natural areas to mitigate environmental impact considering patch size and human impact. On the one hand na tural areas contain the Fig. 1 The Hogtown Creek is cut o ff by two major roads Fig. 2 The I 75 run across Paynes Prairie Preserve

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12 essential ecological value s to allevi ate the heat island effect, purify air quality, conserve water, as well as provide accessible places to interact with nature and have recreational activities. On the other hand, the lack of acces sibility and the ineffective of walkability (mainly results from its large size and long distance) make it hard for urban natural areas to function well as it could be. However, when facing the confliction with developmen t, the ecological health always ha s to compromise to human development ( Fig. 1 ) or regional connection ( Fig. 2 ). Various kinds of efforts are being taken to minimized ecological impact, such as expand the width of wetland by adding space for creek branches to protect its moisture holding capacity (e.g. the Road Ecology Program) and makes great functions of wildlife crossings as e nvironment al mitigation infrastructure (e.g. ARC Wildlife Crossing Competition) Nevertheless, these actions are mostly done by related professions, such as designers, ecologists, and civil engineers, while very few of the public would concern about certain issues. To the most basic reason, people only care what matters to them based on acquired knowledge, thus to make urban natural area visible is essential to let human aware of the importance of protection and conservation through tourism, education, and participation, where transportation network lays the foundation for all the abo ve actions. Hence, it is urgent and necessary to optimize urban transportation network with limited ecological impact. In order to cope with such issue this study selects non motorized network as a probe to integrate transportation with urban ecology, ex plore implicit relationships between these two systems and try to find a potential solution for a better transportation network Error! Reference source not found. Fig. 3 shows the road map of this thesis,

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13 w hich can split into five chapters. The Literature review gives an overview of research gap and referenceable precedent research on suitability identification and transportation network assessment. The Methodology chapter explains deliberately on adaptive m ethods for identify ing ecological suitability, select potential transportation routes, and assess optimized transportation network as well as each transitional step that is connecting these parts, such as how to select potential routes for an optimized ne twork and how to make the optimized routes implementable. Data and resources are also components for this part. While the fourth chapter elaborates research process and related results, which has detailed explaination in the next paragraph. The last chapte r is discussion and conclusion based on the forehead four chapters and explains future works. Fig. 3 Roadmap for this research

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14 T he research process consists of two sessions The first part was oriented to analyze and identify two major clue s, respectively were ecological priority and tr ansportation priority, working simultaneously. The ecological identification result formed up an ecological priority map based on Geographic Information System (GIS), using multiple resources of statistic data to find potential areas with less ecological c onservation priority for nonmotorized routes construction. While the tr ansportation priority identified transportation demand and selected potential corridors for optimizing existing transportation network, which could then represented as transportation de mand priority maps at both regional scale (Alachua County) and city scale (City of Gainesville). Then overlay the two maps with screening criteria to get nonmotorized corridors as the basis for the optimized plan. The second session focused on assessing bo th existing transportation network and optimized transportation network to evaluate the extent of how much the transportation network w as improved as well as the suitability to the contextual condition. This study also adapted multiple indices and c riteria for assessment from thr previous research and projects. Based on these supports, this study offers several suggestions for future work. The efforts taken in this research was trying to figure out whether the nonmotorized routes that identified from ecolog ical sensitivity can improve the existing transportation network while adaptive to contextual condition and how this could be helpful and referenc e able for the future planning.

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15

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16 CHAPTER 2 LITERATURE REVIEW This study researches on the implicit int errelationship between urban ecology network and transportation network, based on the suitable area identification that with both least impact on ecology and most potential for construction in order to add in non motorized routes to existing transportation network, and find out the possible optimization for the future transport construction and the innovative development direction for nonmotorized transportation. The objective focuses on dealing with ecological issues in urban transportation and integrate s both networks towards sustainability. This chapter was conducted following the roadmap of research design: the ecology analysis and conservation priority identification as the basis for the selection of nonmotorized transportation routes, and then apply c omprehensive indicators to a comparative research among existing transportation network and optimized transportation network for potential ecology transportation integration and better urban nonmotorized network. Identification Ecological Priority Ecolo gical priority research Urban ecology issues have been heated discussed for decades (Zapparoli, 1997) (Guntenspergen, 1997) ( Sukopp, 1998) either from investigating ecological patterns or from the ecosystem perspective. This results from the following reasons which were supported by different field of research such as cooperating urban development based on the high concordance between biodiversity conservation priority and ecosystem

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17 service value (Turner et al., 2007) contributing to spatial eco balance (Lenz & Beuttler, 2003) and optimizing the spatial connections to better utilize activity diversity and travel options (Neutens, Versichele, & Schwanen, 2010) Identifying ecological priority is considered as a common basis for different purposes among a diverse field of research which was summarized into three major objectives: for a better future development, for the regional ecological network, and for vulnerable area conservation. Modeling and scenario planning are two common approaches to address future development based on large datasets and multidisciplinary cooperation. One kind of major practical attempt is the oriented precautionary actions by simulating development (Stevens, Dragicevic, & Rothley, 2007) supporting zoning optimization (Geneletti & van Duren, 2008) and pr edicting trends and visions for precautionary actions (Florida, 2005) Another is to fight against ecological issues that come along with urban development T he expansion caused deforestation (Soares Filho et al., 2006) agricultural impacted potential pollutants (Behera & Panda, 2006) as well as corresponding measures such as green infrastructure design (Snall, Lehtomaki, Arponen, Elith, & Moilanen, 2016) are three typical examples Also land suitability analysis is another essential approach to assess the environmental impact (Shen, Xiao, Zhou, & Bao, 2005; Wu, Jelinski, Luck, & Tueller, 2000) and to improve built environment (MENG & FAN, 2011) Such studies provide diverse possibilities for future development, where the research direction is pro mising and widely discussed but lack or transportation related concerns and explorations.

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18 The r egional ecological network is usually classified either by large scale programs or existing boundaries. Greenway has been considered as an effective ecological c arrier as a program or project for regional network since the Greenway movement initiated by Olmsted in 1980s and 1990s (Little, 1995) (Jongman, 1995) and widely applied to Europe (Jongman, Klvik, & Kristiansen, 2004) and the United States (Fabos, 2004) For instance, Florida has engaged in such efforts since 1998 and was adaptive to current and future development (Florida Department of Transportation, 2017) While biodiversity is one of the essential indicators to identify the priority for conservation (Groves et al., 2002) and represent as science based prove for conservation planning (Fer rier, Biology, & Apr, 2007) Meanwhile, the watershed is also commonly used as analysis boundary to identify soil and water condition (Biswas, Sudhakar, & Desai, 2002) and support land planning (Randhir, O'Connor, Penner, & Goodwin, 2001) .These objectives are incorporative to regional planning considering connectivity (Gurrutxaga, Lozano, & del Barrio, 2010) biodiversity (Groves et al., 2002) The regional perspective makes up for traditional development, using ecological units rather than political management boundaries, to facilitate regional cooperation while taking care of ecological health. Thi s worldwide trend to facilitate regional cooperation implies potential opportunities for transportation to go green and sustainable to connect multiple urban areas, where nonmotorized routes gradually play an essential role to incorporate transportation wi th ecology. To protect conservation area, various perspectives and multiple approaches have been applied to the planning process to identify suitability Zhang emphasizes the importance of balance ecosystem service (Zhang, Fu, L, & Zeng, 2015) Genele tti

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19 promote the sub zoning method to preserve conservation area (Geneletti & van Duren, 2008) Austin contributes to urban ecology by science based modeling for species distribution (Austin, 2007) Lopez team promote a context base d model from landscape approach (Lpez Arvalo, Gallina, Landgrave, Martnez Meyer, & Muoz Villers, 2011) Other researchers choose to protect vulnerable areas by investigating specific species to identify the conservation priority (Peterson, Egbert, Snchez Cordero, & Price, 2000) This type of studies provides a broad range of methods and tools to identify the ecological priority for conservation based on a portable data base, which is made up of a variety of indicators, for this research to select proper evaluation systems for identifying ecological suitability areas for potential nonmotorized routes. As a summary existing research for identifying e cological p riority is either from the data based perspectiv e that is too critical or applied the result to multidisciplinary research which did not involve much in transportation issues. Indicators and tools applied Defining research priority for ecology was initiated by Ecolo gical Society of America since 1988 (Lubchenco et al., 2016) and developed into two major research directions as the basis (Orsi & Geneletti, 2010) One considered the demand and urgent of the areas where conservation is needed; the other investigated the feasibility to achieve such pre servation (Suding, Gross, & Houseman, 2004) Indicators for the first research direction were more likely to be physical stressors (Messer, Linthurst, & Overton, 1991) which was initially promoted by the U.S. Environmental Protection Agency in Environmental Monitoring and A ssessment Program (U.S. EPA, 1988) For instance, soil condition is tested to play a significant role in watershed health (Khan, Gupta, & Moharana, 2001) While the latter that has be en

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20 done by precinct research (Orsi, Geneletti, & Newton, 201 1) where the feasibility to ecological conservation and the initiated cost were considered to have an alternative action that draws an overall optimal option (Carwardine et al., 2008) Both research directions could be addressed from two types ( Table 1 ). One type attempted from single issue analysis, such as ecological and socio ecological concerns, that takes one or two representative indicators as an index run delicate deep quantitative research to reveal the interrelationship between indicator and suitability, and their potential impacts on either built environment or pl anned development. These precedent experiences offer overview of various optional indicators that essentially impact on ecological suitability and conservation priority, including biodiversity (Ferrier et al., 2007) soil and water condition (Tripat hi, Panda, & Raghuwanshi, 2003) hydrological vulnerability (Chung & Lee, 2009) habitat (G uisan & Zimmermann, 2000) ecosystem service (Naidoo et al., 2008 ; Snall et al., 2016; Metcalfe e t al., 2015) conservation area (Moilanen, Leathwick, & Elit h, 2008 ; Naidoo et al., 2008) species richness and land use (Durn et al., 2014) green infrastructure (Snall et al., 2016) and so on. The other type conducts systematic research to classify multiple indicators as an assessment model and apply the result of evaluation into practical issue either in projects (Jon Oetting, Tom Hoctor, & Michael Volk, 2016) or research (Vimal et al., 2012; H. Xie, Yao, & Wang, 2 014) This type of experiences can provide science based supports for improvement with proper selection and adaptation. Orsi and Geneletti had a good example to solve deforestation issue by supply reforestation options based on suitability maps and design options (Orsi & Geneletti, 2010)

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21 Table 1 Indicators to identify ecological priority in precedent studies Type Indicators Objectives Single Issue Biodiversity Map spatial pattern Soil Identify spatial prioritization Water Landscape connectivity Hydrological vulnerability Spatial ranking Habitat distribution Predictive models and qualification Ecosystem service Quantify ecosystem map Evaluate spatial priority for fisheries Conservation area Assess existing conservation area Species richness and land use New indi cators for identification Green infrastructure Integrate with ecosystem service Systematic Classification Biodiversity Identify Critical Lands and Waters Landscape Surface water Groundwater Marine Rare or remarkable species (Vimal et al., 2012) Extensive areas of high ecological integrity Landscape diversity Water security Maintain ecological security Biodiversity Disaster avoidance and protection Recreation security

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22 Transportation Planning Research development Thomas firstly promoted the importance of transportation development by sta ting (Thomas, 1956) Road network has been weighted a lion share of transportation research for decades. As par t of the required civic infrastructure, it makes physical connections for increasing productivity in a region and efficient transportation network effects (Garrison & Marble, 1962) which also has impacts on social connections and the economic and political decisions that lead to land use change (Coffin, 2007) The field of transportation research gradually broadens with the integration with multidisciplina ry studies, from economic improvement to ecological concern ( Table 2 ). Table 2 Transportation research development Time Research direction Objectives 1960s Transportation and economy Lan d use layout 1970s Wildlife biology Species Habitat 1980s Environmental Sustainable transport Transportation Geography Network analysis 1990s Ecosystem, L andscape Road ecology Since the 1990s environmental concerns are aware of the importance reg arding first proposed by landscape ecologist (Forman & Alexander, 1998) which marks an emerging subject that investigating various ecological impacts. These impacts, such as the disturbance of ecosystem components, process, and structure, are supported by multiple st udies, to have a close relation to engineering construction and other human

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23 development activities (Coffin, 2007; Forman & Alexander, 1998; Trombulak & Frissell, 2000) Researching on road ecology helps to identify the factors of influence and assess the impact that caused by these road network factors (Coffin, 2007) The effects of roads on abiotic components of ecosystems are va r ious, such as changes to hydrology condition (Grant et al., 2003; Jones, Swanson, Wemple, & Snyder, 2000; Trombulak & Frissell, 2000) and noise effects (Forman, 2003; Slabbekoorn & Peet, 2003) Moreover, roads usually act as barriers to animal movement (Dodd, Barichivich, & Smith, 2004; Forman, 1998; Kerley et al., 2002; Smith & Dodd Jr, 200 3) and result in landscape fragmentation (Canaday, 1996; Develey & Stouffer, 2001) However, due to all these advers e effects, when facing ecological issues, the road network was built to avoid ecologically sensitive areas. These linear constructions separate human with nature not only physically, but also disrupt the ecological equilibrium which deprives places for recreation and education that benefits mental health. Such background made it possible for nonmotorized travel to play an essential role in transportation. Why nonmotorized transportation Nonmotorized transportation (NMT) refers to travel approach es that do not use motorized power to move, such as walking, cycling, scooter and handcart use. This type of transport ation was considered as sustainable transportation as it has limited ecological impact Xie set one of the criteria for an eco city, which has robust transportation infrastructure with minimized car and motorcycle used (H. Xie et al., 2014) Haghshenas reviewed indicators for sustainable trans portation and formed up a database for transport modeling (Haghshenas & Vaziri, 2012) while Goldman started

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24 from policy perspective, emphasized the importance to consider nonmotorized transport for mobility, Intelligent Syste m Management, and Livability (Goldman & Gorham, 2006) Besides environmental concern, the efficiency of nonmotorized tr ansportation is also a remarkable indicator for identifying the urban pattern. Based on behavior research, people tend to have a higher ratio of nonmotorized travel when living in places with higher density, greater connectivity and more mixed use land us e types (Saelens, Sallis, & Frank, 2003) It is also applicable to transportation infrastructures such as local topography and sidewalk availability, due to the high attractiveness to nonmotorized travel modes (Rodrguez & Joo, 2004) Moreover, the increasing nonmotorized travel improves the health and safety in mid sized cities due to the exercise on the way (Milne & Melin, 2014) and the potentially increased social opportunities (Gehl, 2011) Meanwhile, it also brings economic benefits such as reducing car trips (Bell ingham, Washington) and saving the cost of tourism spending (Burlington, Vermont). Nonmotorized transport has been integrated with land use to improve public health (Frank, 2000) and quality of life (McNally & Kulkarni, 1997) Negative health impacts that result from incr eased motor vehicle travel will potentially mitigate by shif ting to nonmotorized modes (Litman, 2003) Overall, the nonmotorized transportation is a crucial entry point for improving existing transportation network, as its benefits for ecological sustainability, sustainable development pattern and human health improvement.

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25 Transportation Network Assessmen t V arious studies have tested available tools and models among indicators from different perspectives to get a quantified result t o evaluate the efficiency and robustness of a transportation network T hese attempts can split into four major types: topologi cal analysis, geometrical analysis, impact assessment and systematic analysis. Tools and where applicable Topological analysis The topological analysis is one of the common approaches for network analysis due to the capability of evaluation that can regard less of the actual scale. It has not only been tested by scale free model through mathematical ways (Barabsi & Albert, 1999) b ut also be applied to other research field s such as biology (Watts & Strogatz, 1998) economy, and engineering. Space Syntax is a topolog i cal relationship based tool, which is common ly used in social networks and primarily considered as a conceptual theory and analytical method for urban design, architecture, and interior space design that contributes to understanding their morphological logic (Hillier & Hanson, 1989) After this starting point, its practical use was widely applied to urban design proposal considering the building street relation, open space location, and network analysis (Jiang, 2007; Jiang, Claramunt, & Klarqvist, 2000; Kim & Sohn, 2002) W hile its practical suitability also expanded along with multidisciplinary research that either combining urban design with monographic studies such as transportati on optimization and movement prediction (McCahil & Garrick, 2008; Raford & Ragland, 2004) or further analyzing the relationship between human societies and inhabited space in diverse forms (Bafna, 2003)

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26 For this research, S pace Syntax is the major tool that applied to analysis the topological relationship among each of the transportation network components, considering nodes (intersection) and lin ks (routes). Axial map lay the basis for topological relationship analysis by identify multiple indicators when importing different value of analysis radius as the variable Geometrical analysis Based on preced ent projects and literature review, researchers proposed supplemental measurements such as entropy, connection patterns and continuity of a transportation network (F. Xie & Levinson, 2007). Other studies focus on the Urban form, such as land use types and transportation facilities that have a significant impact on transportation structure (Chen et al., 2011). The concept of space time prism was proposed based on the Geographical Information System, which determines the location of travel and activities wit h the bounded limitation of space and time (Miller, 1991). In addition, network analysis is essential when considering geography (Haggett & Chorley, 1996). Impact assessment Traffic impact assessment (TIA) has been widely applied to multiple places and dep artments (Road and Traffic Devision 2007) (Land Transport Division, 2015) (City Council, 2017) which assesses the potential traffic impact based on historical traffic da ta and potential traffic changes according to the proposed plans. These works targeted at improving trip distribution and network service based on the prediction of traffic growth ( Table 9 ). Moreover, multimodal co nsiderations were specified by pedestrian, bicycles and transit vehicles in the updated traffic impact studies

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27 (Transportation Planning Organization, 2014) The traffic impacts usually result from the change of junction, access, or road condition. Environmental impact is another assessment perspective. For example, Europe and Japan engaged in assessing the impact of Intelligent Transport Systems (ITS) by tracking and calculating CO 2 emission (EC METI Ta sk Force, 2009) Considering user optimizing and system optimizing flow pattern as assessment index for transportation network is another approach (Nagurney, Qiang, & Nagurney, 201 0) One of the essential examples is Strategic Environmental Assessment (SEA) through COMMUTE framework by a set of environmental indicators, which applied to the Trans European Transport Network (TEN T) since the start of 2014 ( Mr Hermann Heich, TV Rheinland, 2000) S ystematic analysis The four step travel model consists of four basic elements, respectively are trip generation, trip distribution, mode choice, and trip assignment. It is widely used to assess transportation net work (McNally, 2007) and predict transportation service efficiency (Boyce, Zhang, & Lupa, 1994; Chen et al., 2011) In addition Ortuzar provided information, methodolo gy tools, and skills to modeling in a comprehensive way (de Dios Ortuzar & Willumsen, 1994) Based on this framework, transportation related analysis can either evaluate existing transportation network or improve transportation network in the future to serve traffic demands better. In order t o deal with the uncertainty decision making tool for sustainable transportation system was promoted based on multicriteria (Awasthi, Chauhan, & Omrani, 2011) Multiple factors, considering traffic flow, travel pattern and the related cost to identify importance value for assessment (Ryan & WATTS, 2008) Economic

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28 concern was also considered by cost benefit analysis to minimize the necess ary cost (Jonsson, 2008; Kunreuther, Grossi, Seeber, & Smyth, 2003) Network analysis is another set of powerful tools based on Geographic Information System (GIS) platform to assess service efficiency that can support transportation network analysis. Service Area is created to evaluate the accessibility of facilities, which varies from different impendence such as time of travel and travel distance. It also implies the attractiveness of these tr ansportation facilities While the cost paths along the network (ArcMap, 2017) For the result of OD matrix, even though the connection was in straight line graphically, the values of the length of th e least cost routes in the attribute table Indicators Topological indicators For Space Syntax based analysis, some frequently used indicators respectively are integration, depth, choice, connectivity, and node count. Each of which has its concepts explain ed in Table 3 (Bill Hillier, 1986) and the four indicators that were ap plied to this research have more detailed explanation below. Mean depth Mean depth is calculated by assigning a depth value to each space according to how many spaces are away from the original space and then sum these values and divide them by the numbe r of spaces in the system. Integration

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29 Integration is a normalized measure of distance from any a space of origin to all others in a system. In general, it reflects the closeness from one origin space to all other spaces, and to what extent the origin can be seen as the measure of relative asymmetry (or relative depth). Connectivity Connectivity calculates the total number of spaces that are immediately connecting an origin space, which reflects the importance of one transportation segment among the surro unding region and the accessibility to the origin. Total depth The higher total depth value of one transportation route is, the more far away it is and more t urns need to take to access it. Table 3 Definitions of each indicator in Space Syntax ( Hillier & Hanson, 1989) Indicators Definition Integration A normalized measure of distance from any a space of origin to all others in a system. Total Depth The sum of the topological depth from any a node to all the others. Choice measures how li kely an axial line or a street segment it is to be passed through on all shortest routes from all spaces to all other spaces in the entire system or within a predetermined distance (radius) from each segment. Connectivity Refers to the number of spaces i mmediately connecting an area of origin. Node Count The number of lines (or segments) encountered on the route from the selected line (or segment) to all others. Geometrical indicators Accessibility

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30 The Accessibility indicator can further divided into l ength, time, or costs that measure the ease of access to evaluate the efficiency of a network and the mobility the network can provide (Gutierrez, Monzon, & Piero, 1998) Accessibi lity Analyst incorporates a lot of measurements, such as cumulative opportunity measures, gravity type measures, and utility based measures (Liu & Zhu, 2004) Accessibility is one of the esse ntial characteristics in transportation research field. For decades, researchers apply accessibility to reveal the relationship between transport and land use that benefits urban planning (Liu & Zhu, 2004) Meanwhile, it also works as a major factor in efficiency analysis for transportation network and infrastructure planning (Gutierrez et al., 1998) as well as to analyze and distribute the travel demands on public trans it (O'Sullivan, et al. 2000). Moreover, accessibility is also used to reduce social inequity, provide new road infrastructure (Curl, Nelson, & Anable, 2011) and evaluate regional impact from new transport construction (Linneker & Spence, 1996) Mobility An efficient transportation is targeted to make it affordable and fast t o move both people and goods (Sohail, Maunder, & Cavill, 2006) To be more specific, the mobility measures the quality of movement and the quantity of objectives that have been moved (Zuidgeest, 2005) Mobility usually associated with accessibility to defined the ease with which certain destinations can be reached from a particular origin using a specific mode of transport The mobility of a transportation network can improve the possibility that a destination can be acces sed within a certain time or

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31 distance depending on the spatial distribution of activities, the origins of demands and transportation system connecting the origins and destinations. Equity Equity is used to identify whether the distribution of transportatio n is appropriate (Litman, 2002) which can split into horizontal and vertical types (Bogale, 2012) Transportation infrastructure availability Transportation infrastructure consists of basic engineer elements ranging from road length and width (especially per unit zoning or unit po pulation), public transport hubs to street furniture. All these components can affect the accessibility and mobility of a transportation network, considering the density, service area, distribution. Links and nodes are two basic structural elements (Taaffe, 1996) Spatial mismatch The concept of spatial mismatch is originally proposed to assess the employment availability since the 1960s I t target ed at the analysis of the spatial difference between demand and supply. One criti cal application in transportation research is to analysis the option of transportation mode. Most of the existing sources focused on the relationship between transportation and economic al as a basis to identify transportation development demands. Joseph in volved income level into consideration for spatial mismatch to improve public transportation (Lau, 2011) Paul identified spatial mismatch by simulating employment and car ownership (Ong & Miller, 2005) team estab lished an equilibrium model to indicate distribution differences between urban and rural areas (Coulson, Laing, & Wang, 2001)

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32 Systematic indicators Goldman & Gorham provided more flexible and integrated options of travel by identifying other four indicators from a system oriented approach, respectively are New Mobility, City Logistics, Intelligent System Management, and Livability (Goldman & Gorha m, 2006) .Some of these strategies, such as vehicle sharing, new service paradigm, and comprehensive bus system management are inspiring and applicable for this research. While Paulley and his colleagues commenced from the socioeconomic aspects considering the quality of public transportation service, income, and car ownership (Paulley et al., 2006) Systematic analysis is more suitable for research that focuses on or combines with non spatial factors such as social works and policies, hence the indicators are not appropriat e for this studies in the current progress. Summary Research gap Existi ng transportation usually tends to negatively avoid ecological sensitivity areas to mitigate the ecological impact, while the nonmotorized routes usually built in natural places in urban areas or act as commuter ways for connecting different destinations. This negative transportation development leaves huge blanks to be improved either by providing healthier regional connectivity routes or improve accessibility to traffic attractors. Ecological conservation priority and suitability analysis have long been d iscussed for decades, these works either focus on single issues that may affect ecosystem to being considered as a

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33 foundation for practical research such as helping with decision making and instructing a plan However, when integrating with transportation, the only research direction that can be researched is road ecology. Admittedly, nonmotorized ways have a much smaller ecological impact than roadways, they are newly developed and still ext remely worth exploring. Tools and i ndicators for comparative analysis For county level research, this study used topological analysis to test whether the optimized transportation network can improve regional topological relationship to facilitate nonmotori zed travel. Connectivity, integration, Total Depth, and Mean Depth are four indicators for the comparison. Impact assessment is also applied at this scale by overlaying the existing transportation network and ecological suitability map. In addition OD mat rix is applied to check the accessibility by least cost and reflect the concentration extent within the study area. While at the city scale, the transportation network has denser distribution and easier to assess the service efficiency. This research took Gainesville as an example evaluating the Service Area tool to see the service coverage and how far the traffic attractions can impact within different scenarios of travel time. Meanwhile, this study zoomed into areas as typical cases to test the generaliz ed context suitability.

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34 CHAPTER 3 METHODOLOGY AND DATA This study is designed as a multidisciplinary research that integrating ecological network and transportation network towards sustainability. Three sessions are arranged progressivel y to conduct the study to approach the final goal, optimizing transportation network (OTN) through an ecology sustainable way. The first part was to identify potential nonmotorized routes for the optimized for the study area from an ecological perspective considering vario us parameters and multiple screenings that could limit the ecological impact. While the following part consis ts of a comparative research th at asses se s the difference between ETN and OTN and a series of evaluation that assesses the service efficiency of OT N to see whether the ecologically based transportation network can serve development demand efficiently. These two sessions lay a foundation for the comparative analysis of the existing transportation network and optimized transportation network to see wh ether the ecological approach contribute s to improv ing the existing transportation network while adaptive to the context. Applicable Tools Geographic Information Systems (GIS) and Space Syntax (SSX) software are two platforms for conducting this research. GIS is mainly used for Raster analysis and network analysis to get a data based systematic result, while the SSX is applied to focus on the topological relationship of transportation network analysis based on topo graphics.

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35 Table 4 provides an overview of multiple tools and functions and related objectives based on each of the software respectively, each of the tools was following the research process Each step and tools applied are listed below. Table 4 Overview of software and tools for each step of analysis Software Platform Tools Analysis Geographic Information System Raster Calculator Ecological Suitability Map (Local) Cell Statistics Ecological Suitability Map (Overall) Map Editor Potential areas for commuters, visitors, and sportspeople Cost Connectivity Potential New Routes Euclidean Distance Proximity to existing transportation network OD Matrix Least cost routes among multiple origins and destinations Service Area Acces sible coverage and service area that can be reached with time or distance impedance Space Syntax Axial Map Linear assessment Depth Map Depth assessment Segment Map Integrity and connectivity assessment Identify ecological suitability map (ESM) Rast er calculator is an essential step to get the ecological suitability map at the local scale, multiple indicators that represented in shapefile (a GIS data format) was collected from the local level and reclassified into 1 9 scale classification with proper weighting that has been discussed by the committee based on prior experiences for the calculation. The results are represented as ecological suitability map, where the higher the ecological value is, the more essential the priority is. This local scale ec ological

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36 suitability map (ESM) is then combined with state scale ESM using cell statistics tool by both maximum and average approach to get the overall ecological suitability maps. The cell statistics maximum approach took the maximum value wherever the va lue is different between the ESM from two scales to ensure high priority will be protected during the following development. While the cell statistic average approach took the mean value of both county scale and city scale that balance the effect from the different measurement. Identify traffic demand areas Based on the types of destination and purposes of travel, Table 5 shows parameters fo r the various potential purpose s of travel and characteristics of each kind of t he trip option. This research selects three major travel purposes that happen within the study are, respectively are commuting recreation, and education (usually combines with tourism). Commuting and recreational purposes of travel happen concentrate based on land use due to the function of zoning and property ownership. While tourism activities usually happen at places that are developed for such function (e.g. preserve), and these areas also have high potential to contain educational functions to lea d people to be aware of the importance of ecological conservation. Hence land use and conservation area are two indexes for identifying potential traffic demand areas These purpose oriented destinations are collectively called as the traffic attractions d ue to the attractiveness to various groups of people. Travel characteristics will be considered as one of the parameters to select nonmotorized transportation routes. Such areas are identified based on land use planning wi th functional area (e.g. get rid o f the parking lot) that merge into one layer and then reclassify them into unified

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37 calculation scale with proper weighting to identify potential traffic demand areas in GIS raster calculator to get the traffic demand priority map. Table 5 Identify potential traffic demand areas Index Purpose Parameter Subdivision Travel Characteristics Land use Commute Residential land Point to point Institutional land 170 institutional 179 institutional under construction Commercial lan d 143 professional service 144 cultural and entertainme nt 145 tourist services 149 commercial and services under construction Recreation Green space 180 recreational 185 park and zoos 187 stadiums 189 other recreational 190 open land Accessibility to e xisting network Multiple use Mixed use 147 mixed commercial and services Conservation area s and park s Education Conservation area Accessibility Free path inside Education Tourism Wetland Parks Get potential nonmotorized routes Cost connectivity tool is recently updated new feature in GIS 10.4 or later version, which is applied to produces the least cost connectivity routes among multiple areas. This research makes use of the principle of the tools, based on ESM, the higher

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38 the ecolo gical priority is, the higher cost should be. Hence the map of potential nonmotorized routes map was produced by the least ecological priority routes. T wo more steps were applied t o select nonmotorized routes. O ne is to identify the proximity to both traff ic attractors and existing transportation infrastructure ; the other is to analysis the land suitability based on land use type. Based on these two screenings, the final nonmotorized routes wa s integrated into existing road network as the optimized transpor tation network (OTN). Comparative analysis between OTN and ETN Both OTN and ETN are export from ArcGIS as DXF files, import to AutoCAD to check connectivity, and then import into Space Syntax for analysis based on the converted Axial Map. The Axial Map was adapted according to the transportation network (right of way and turning radius). For road network, the axial lines were adapted from road centerline For nonmotorized routes, the axial lines were adapted from the path polyline due to the scale. The axi al roadway lines are the same in ETN and OTN. While the nonmotorized routes are different: the existing nonmotorized axial lines were adapted from existing trials that connecting to major roads, the optimized nonmotorized axial lines were integrated with t he ones that generated based on ecological identification while adaptive to existing trails. Data and Sources Transportation base map is drawn by the author based on the GIS export and been verified and revises based on the Google aerial map. The GIS and the Google map were tools to eliminate and clean the transportation network data.

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39 Data for GIS analysis wer e unified into shapefile files, either in Raster or Vector. Most of the shapefile came from Florida Geographic Data Library (FGDL) and applied to the local scale ESM, while ecological priority map at state scale was retrieved from the final report of Critical Lands and Waters Identification Project (Oetting, J., Hoctor, T., & Volk, M., 2016) that based on indicators that hav e been classified into biodiversity, landscape, and surface water resources, for statewide and regional analysis. These two scales of results are integrated as a final ESM to improve the validity. For the transportation part, traffic att r actions are identi fied based on land use and land cover (LULC) data (Florida, 1999) and conservation areas (from FGDL), which are then adapted from Google map to make sure the the current information is u pdat ed The shapefile data for existing transportation network, including roads, trails, and bicycle lanes, are collected as secondary data from existing GIS database. As for SSX analysis, both transportation ne tworks (ETN and OTN) are export into DXF format, edit by AutoCAD to meet the requirement to run the topological calculation, and then import into SSX as an axial map that is ready for analysis. This part focus on comparative analysis based on the preceding steps. Indicators and Weightings This research classified single issue indicators into a two layer hierarchy framework, which gets rid of secondary indicator such as the distribution map for ecosystem service value that based on land use, green infrastruc ture. The six classes respectively are landscape, habitat, watershed, conservation, green space, and land type, each of them has a subdivision with one or more indicators. These indicators are selected based on precedent research and feasibility of data so urce.

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40 The weighting is ranked by the accessibility of each type and finally set by multiple times of attempts and discussion. For instance, habitats usually have larger areas that could go through as a shortcut for nonmotorized traveler while road traffic may have a long way detour. In addition their vulnerability to human impact also makes the habitat index has the highest weighting. There are many reasons to support the vulnerability, take an extreme case as an example animals are flexible and can migra te to another habitat that is more suitable for their life once the migration happens the original habitat either degradation or become an only landscape that is relatively quiet and still. Hence the Landscape index ranks following. Table 6 provides the proportion of each indicator under index classification and weighting for each index. Still, take habitat as an example the index of habitat account for 25% of overall weighting for suitability calculation among o ther indexes, while the proportion column represents sub weighting under this 25% part, thus the weighting of the potential habitat richness is 25% 25%= 6.25%. Table 6 Suitability objectives, indicators, and weightings to identif y ecological priority areas Index Weighting Indicator Proportion landscape 20 landscape integration index 35 landscape resource priority 35 natural community 30 habitat 25 potential habitat richness 25 biodiversity 25 habitat conservation are a 25 strategic habitat conservation area 25 watershed 15 surface water resource priority 25 groundwater recharge area 20 floodplain 25 wetland 30 conservation 15 FLMA 100

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41 green space 10 greenway 100 land 15 land use 40 land cover 60 Cr iteria and A ssessment To select potential traffic demand areas Due to the limitation, considering the typicality of sample areas, as well as the potential demand and effect for both ecology and transportation, the acreage of mixed use clusters were seen as a n essential factor to select potential areas among the variety traffic attractions On the one hand mixed use can attract more people and potentially trigger more activities. For instance, one family plans to eat in the restaurant, if there is a park or supermarket nearby, they would possibly go for a walk or shopping while back home if there is only a restaurant. On the other hand, large area, especially large conservation areas interdict the construction of road traffic, thus have more demands for nonm otorized traffic to improve the transportation network. Based on the travel purposes listed in Table 5 ten kinds of level 3 land uses are selected, including Commercial and services, commercial and services under construction, institutional, open land, Recreational, other recreational, Parks and zoos, Residential high density (six or more dwelling units per acre), Residential high density under construction (six or more dwelling units per acre) under construction), and Tourist services. Then combine with Basemap and Reference to create a new layer that identifying mixed use clusters. These clusters are then further screened by areas that larger than 150 acres as the sample and export to a new layer as potential tra ffic attractive area based on land use.

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42 The other part of potential traffic attractive areas is identified based on existing conservation areas that work for tourism and educational purpose. Using Calculate geometry to update the values of area s by acres of conservation land, from which potential areas are identified by acr e age that larger than 1000 Three places that locate in northwest part of Alachua County that is less than 1000 acres were included because they are crossing the political boundary, whe re the calculated areas within the study area are smaller than while the total acres of these conservation areas can meet the acreage criteria. These two kinds of potential traffic demand areas are then merged as the input feature called traffic attraction and then run Cost Connectivity based on the ecological value to get potential nonmotorized routes. To select nonmotorized route for an OTN Two screening criteria are applied to select nonmotorized routes, respectively are land use type (considering owne rship that affects public accessibility) and proximity to existing nonmotorized routes. This research reclassifies land use into five classes in 1 9 scale, based on land use type level1 and level2 when needed ( Table 7 ). The higher value represents higher suitability for nonmotorized routes. Agriculture, R angeland and upland forests were the most suitable types of nonmotorized routes for a healthy environment and less construction. Commercial and services, Instituti onal, and high density residential were secondary suitable H owever the demand for more privacy made Residential lands rank in class 5. Open land ranked in the same class because of the necessity to reserve for future development, thus at a medium level s uitable for nonmotorized routes. Water and wetlands were exception

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43 areas for nonmotorized routes construction because of the highest level of conservation priority, while u tility lands were not suitable due to the security and management requirement. The r est of the land use types were put into class 3. All land use types except Class 1 were potential location s for nonmotorized routes ; other classification values are applied only when multiple routes are available connecting same destinations to select a be tter path Table 7 Land suitability classification for nonmotorized routes Level 1 Level 2 Class Agricultural / 9 Barren land / 9 Rangeland / 9 Upland forests / 9 Transportation, communication, and utilities Transportation 3 Communication 3 utilities 1 Urban and built up Commercial and services 7 Industrial 3 Institutional 7 Open land 5 Residential, high density (six or more dwelling units per acre) 5 Residential, low density (two or less dwelling units per acre) 3 Residential, high density (two to five dwelling units per acre) 3 Water 1 wetlands 1 Next screening is identifying the proximity to existing transportation network. To calculate the proximity to existing nonmotorized routes, this resear ch run Euclidean Distance tool, using quantile classification to get the result. The reason for using quantile classification results from the diminishing impact from existing routes, thus the more adjacent to the existing route, the less demand for a new route construction.

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44 Meanwhile, nonmotorized routes can combine with road network under the prerequisite of concerning about safety for nonmotorized travelers. Commuters use nonmotorized routes more than other purposes of travel because commuting is nece ssity activity while others might be spontaneous activity. Hence this indicator has the highest weighting. However, the proximity to low traffic area could be either be a lack of or unnecessary for traffic development T hus this indicator has a lower weigh ting. Other indicators have the same weighting result from being no big difference in importance for traffic demand. Table 8 Suitability objectives, indicators, and weightings to identify priority for nonmotorized routes Suitabilit y Objective Weighting Indicators Proportion Identify areas proximal to low traffic roadways 15 Annual Average Daily Traffic 15 Identify areas proximal to mixed use lands 20 Adapted from the Google map, attractor 20 Identify areas proximal to existin g nonmotorized trails Identify areas suitable for nonmotorized routes based on land use Areas with traffic Attraction 65 For commute 25 For recreation 20 for education and tourism 20

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45

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46 CHAPTER 4 RESEARCH PROCESS AND RESULTS Study Area O verview The study area, Alachua County, locates North Central Florida, with a total area of 969 square miles (620160 acres), and has a diverse culture, local music, and artisans. The county has about 100,000 acres of conservation lands that supporting th e health of the ecosystem where some of the conservation areas are shared with adjacent counties (e.g. Columbia County that located at northwest) from a regional perspective Gainesville, the county seat and the largest city in this county contains multi ple institutions, such as University of Florida and Santa Fe College, was awarded by National Geographic Adventure magazine as one of the 2007 "best places to live and play" in the United States 1 containing 71 parks and natural areas. The county has a mul tiple layer road system, which is served by northwest southeast Interstate 75 (I 75), several Florida State Routes (such as US27, US41, US301), other county roads and local streets. While in more urbanized areas, such as Gainesville, grid system forms up t he core pattern for the transportation network with northwest, northeast, southeast, southwest four quadrants. Even so, dealing with urban ecology is one of the critical issues that a complete transportation network w as fac ed with especially the routes that are connecting traffic attractions. Typically, the transportation routes are distributed to avoid the ecological ly sensitive area at the very beginning of planning process to minimize the ecological 1 "The Best Places to Live + Play: Cities" National Geographic Archived from the original on April 16, 2008 Retrieved 2008 04 16

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47 impact. However, this results in the insufficient co nnection of road networks such as only one street connecting a residential area to a major road due to the wetland at the other sides of the property, which further impact on the trip options and convenience of travelers. Fig. 4 show s the distribution of ecological area, including wetland conservation areas urban parks, and community gardens, and their relation to the urban transportation network. Most of these areas, especially those have larger areas, left hol es while only several of them are connected to existing road network by trails. Thus, to integrate transportation planning with urban ecology, the connection between natural area and road network is an essential process that needs to be addressed Moreover according to the final report of Alachua County Countywide Recreation Master Plan Phase 2, an interconnected system of greenways and trails is one of the top 10 countywide recreational desires (Robert M., 2005) which indicate d the high public desire that in concordance with the objective of this research. Fig. 4 Ecological conservation area in Alachua County

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48 Considering of the vulnerability of urban ecology, this study researches on the nonmotorized routes concerning both minimize environmental impact and improve accessibility a nd connectivity of transportation network as an optimized transportation network Admittedly, this issue has been considered by multiple departments, however, from the previous actions and fiscal year plan, there are still many things to do to improve the transportation network. On the one hand ongoing regional transportation connection projects mainly focus on road traffic when considering accessibility. Significant Projects is a representative example (Transportation Improvement Program, 2017) On the other hand, multiple nonmotorized projects only concern within Gainesville Urbanized area rather than the connection among the surrounding region, such as Bicycle and Pedestrian Projects (Transportation I mprovement Program, 2017) Bicycle/Pedestrian Priority (List of Priority Projects, 2017) and Bicycle/Pedestrian Advisory Board (Public Involvement Plan, 2017) Transit Ridership Monitoring Repor t (Annual Transit Ridership Monitoring Report, 2017) In addition to taking advantage of bicycle culture near the university this research focuses on the direction that was forgotten by the authorities, to identify potential n onmotorized routes that are connecting among urban clusters and conservation areas at the regional scale to optimize transportation network. Population Alachua County has an uneven distribution of population density ( Fig. 5 ). Urban centers and community clusters attract more population and contain more human activities than rural areas that are unincorporated. I n order t o balance thr equity of accessibility while saving road construction cost new nonmotorized route s are an

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49 indispensable part of the transportation network to connect traffic attractions among the study areas. Gainesville has long been the top population place in Alachua County ( Fi g. 6 ) and its population kee ps increasing according to the historical census statistics ( Fig. 7 ). To optimize the existing transportation infrastructure for better service coverage and higher efficiency is an additional essential part. Fig. 5 Population density in Alachua County

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50 Fi g. 6 Census of City/Towns population in Alachua County (2010) Fig. 7 Population increase in Gainesville Transportation facts Alachua County has 80% Single occupant vehicle for travel since 2014, while the Transit mode share to work is only 2.1% (DATAUSA, 2015) However, the mean 0 20,000 40,000 60,000 80,000 100,000 120,000 140,000 Gainesville Alachua High Springs Newberry Archer Hawthorne Waldo Micanopy LaCrosse Unincorporated Gainesvill e Alachua High Springs Newberry Archer Hawthorn e Waldo Micanopy LaCrosse Unincorpo rated Census 2010 124,354 9,059 5,350 4,950 1,118 1,417 1015 600 360 99,113 95,447 118,634 124,354 90,000 95,000 100,000 105,000 110,000 115,000 120,000 125,000 130,000 Census 2000 Census 2005 Census 2010

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51 commute time in Alachua County is only 26.4 minutes, which is compatible to develop nonmotorized transport. From the old travel mode in the State of Florid a private motor vehicles such as cars, trucks, and vans kept the dominant position, but with a decreasing trend ( Fig. 8 ). Other kinds of travel modes show a clear increase, which implies the potential for developi ng nonmotorized transportation ( Fig. 9 ). However, when comparing with the average level of the state the study area has nearly three times of nonmotorized traveler than that of Florida ( Fig. 10 ). Such changing trend of travel mode also verified the demand of developing nonmotorized transportation infrastructures. Fig. 8 Travel mode change in Florida (2006 2015) 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 Car, truck, or van drove alone Car, truck, or van carpooled Public transportation (not taxi) Walked Bicycle Other means Worked at home

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52 Fig. 9 Non motorized travel mode change in Florida (2006 2015) Fig. 10 Annual average travel mode proportion in state, county, and city scale 0.00% 2.00% 4.00% 6.00% 8.00% 10.00% 12.00% 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 Public transportation (not taxi) Walked Bicycle Other means Worked at home 0.00% 10.00% 20.00% 30.00% 40.00% 50.00% 60.00% 70.00% 80.00% Drive Alone Carpool Public Transit Other Walk or Bike Drive Alone Carpool Public Transit Other Walk or Bike Florida 78.80% 12.90% 1.90% 4.10% 2.30% Alachua County 74.70% 12.70% 2.40% 4.20% 6.00% Gainesville 69.80% 12.20% 3.20% 3.90% 10.90%

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53 Identify Ecological Suitability Maps Local scale ecological suitability map was th e result by ov erlaying six classifications with multiple indicators, respectively are landscape, habitat, watershed, conservation, green space, and land use ( Table 6 ). Each of the indicators was classified into 1 9 scale as sing le maps for the overlay calculation where higher level refers to the higher ecological value (example in Fig. 11 ). Fig. 11 Examples of single indicator map for ecological suitability identification

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54 Data based ESM In order to get more precise analysis the original ecological suitability maps w ere generated based on two scales: the local scale data that is localized and specific to the context based situation ( Error! Reference source not found. ), and the regional scale map that more suitable for research at regional scale ( Error! Reference source not found. ). Local ESM is calculated based on using raster calculator, while the CLIP project provided the regional ESM The symbology of suitability maps was r e classified into five levels color range for the following analy sis The ecological value (conservation priority) increases from blue to red. The calculation of local scale ESM was comprehensive, but the weighting of each index was adapted based on the summary of literature review and the discussion with committee memb er s While the state level ESM was tested and verified after four updated project versions. Overall, the regional ESM consider ed riparian factors more important H ence the linear water flows are more clearly shown in Error Reference source not found. with higher priority.

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55 Tool based ESM These two maps result from Cell statistics tool based on the unified classification and symbology by two approaches. One is the Cell Statistics Maximum approach, which referred to get the higher value of whi chever layer the data came from to make sure high ecological priority areas were protected no matter what process was done to get the result. The other one is the Average approach, which calculated the mean value of both layers to treat with local priority and regional priority evenly. These two maps were prepared as t he basemaps for the following selection when portable nonmotorized routes were identified Fig. 12 ESM based on cell statistics maximum approach

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56 Identify Traffic Demand Areas Traffic attractions are the most obvious indicators of traffic deman d and could be identified easily for the purposes of travel and the density of traffic attractions. This research identified three major types of travel purpose, respectively are commut ing recreation, and education, based on land use type Commuter attrac tive areas concentrate on convenience that is directly connecting origins to destinations, and the two endpoints of each route are either the high density dwelling districts or working Fig. 13 ESM based on cell statistics average approach

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57 places such as institutional lands. While recreational attractions cons ist of multiple land use types, including commercial and services, parks, open spaces, and so on. Educational is a concept of tourism development that can potentially appeal people to get aware of the importance to protect ecology and living environment H ence this purpose of travel focuses on conservation areas. Based on the fact that all these types do not have impacts on potential routes producing all these area s are eventually selected and merged into one layer to identify mixed use cluster within the study area when overlapping among three kinds of travel purposes. Fig. 14 Potential traffic attractions in Alachua County

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58 This research applied both generalized land use type with mixed use and ecological areas and then merged them into one layer. Urban mixed use areas that more than 150 acres and ecological areas tha t are larger than 1000 acres were selected as potential nonmotorized traffic attractions ( Fig. 14 ). Identify A pplicable Nonmotorized Routes Based on the evaluation of ecological suitability and the ide ntification and selection of potential traffic demand areas, cost connectivity tool was applied to get the least ecological impact routes with road network as a location reference. Fig. 16 and Fig. 15 respectively represents the nonmotorized routes that calculated based on the two too based ESMs. Fig. 15 Potential nonmotorized routes from ESM based on cell statis tics maximum approach Fig. 16 Potential nonmotorized routes from ESM based on cell statistics average approach

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59 Two more screening steps were conducted to select from the two routes options to get the final nonmotorized route. The first ste p is objected to identifying the proximity to existing transportation network ( Fig. 18 ) and potential traffic demand areas ( Fig. 17 ) to ensure the service efficiency and av oid duplication as the prerequisite to prevent duplicate construction The next step follows up is to analyze land suitability based on land use type, considering the public accessibility and frequency of utilization. Based on this part, the final nonmoto rized routes were selected and then integrating with existing trails that have a limited ecological impact to form up the optimized transportation network. When applying optimized nonmotorized routes, this research identifies shortcut for commuters to travel efficiently from origin to destination comparing to the road traffic. This type of routes is more suitable for cycling, which is faster and less sensitive to surrounding landscape. While for recreational and educational routes, multiple choices Fig. 17 Distance to traffic a ttractions Fig. 18 Distance to existing trails

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60 and adaptiveness to the context are more important, especially in a conservation area, since several micro modifications have less ecological impacts than a single huge construction. These two type s of routes are more suitable for pedestrian and trials. For instance, the San Felasco State Hammock Preserve is planned to function both for nature and recreation, one thirds of the area is used to provide outdoor adventure, such as hike trails, off road bicycles, horseback rides. Moreover, the reserved fire corrid or also leaves space for nonmotorized routes that have limited ecological impacts ( Fig. 19 ). While Paynes Prairie Preserve a s Floridas first state preserve and Natio nal Natural Landmark, contains more than 20 di stinct biological communities with extremely high conservation value. Only a few trails and several annual events open in this area ( Fig. 20 ). Such highly ecologically sensitive areas are more suitable for hiking t rails and rather than com Fig. 19 Fire corridor in San Felasco State Hammock Preserve Fig. 20 Recreational activities with limited impact in Paynes Prairie Preserve

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61 Comparative Analysis Ecological impact Identify the confliction between existing trails and the ecological ly sensitive areas is essential to compare the ecological impact from ETN and OTN. Optimized routes were generated based on the principle to avoid high ecological conservation priority areas with limited impact while existing trails have confliction with ecological priority. In order to have these confliction areas identified this research set ecological suitability map w ith black to white stretch symbology where white color represents the highest priority, and then overlay the existing trails to see where conflictions fall ( Fig. 21 ). 41 out of 123 existing trail records were built or partially constructed in the highest Fig. 21 Distribution of existing trails and ecological priority areas

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62 ecological priority area, which is nearly 35% percent of trails. Let alone the trail length since trails in the preserves are much longer length than in urban area. This lead to the spatial mismatch that some of th e existing trails located in the ecological ly sensitive area s which may have different extent of the ecological impact. For instance, paddling trail in Newmans Lake is less impacted than multi use trails that are going through the Paynes Prairie Preserve. T he optimized nonmotorized routes that identified based on ecological priority has avoided such areas to minimized ecological impact.

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63 Topological relationship This research selected three major indicators, respectively are connectivity, integration, and depth, for topological analysis that produced results for both graphical comparison s that ranked the level of hierarchy relation and statistical comparison s that visualized the statistic data with tables. The results show no big difference in network Fig. 22 Axial map for existing road network, ETN, and OTN considering total depth, total connectivity, and integration

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64 hiera rchy and implicit service efficiency level, but the actual quantity of interrelationship improved a lot from ETN to OTN. Fig. 22 show the importance of service hierarchy among three networks considering depth, co nnectivity, and integration. T he color refers to a higher level when closer to red, while the blue color means the lowest value. The result of the graphical comparison show s that existing nonmotorized routes did not change the rank ing level of each segment of major road, while the optimized nonmotorized routes increased 1 2 level of road network importance when with certain density (e.g. the Paynes Prairie area). Overall, among all three indicators, the most efficient part of network concentrated in Gainesv ille area, and the High Spring and Alachua area took the second place. However, the extent of improvement is evident when visualizing statistical data. Because the exact value of information is clearer to show the difference, this part further Fig. 23 The comparison of total value among four indicators 0.00 200000.00 400000.00 600000.00 800000.00 1000000.00 1200000.00 MeanDepth Integration TotalConnectivity TotalDepth MeanDepth Integration TotalConnectivity TotalDepth Road Network 17964.76 401.94 557577 438798 Existing transportation Network 25655.28 479.96 692817 523165 Optimized Transportation Network 26523.89 610.69 1046976 743710

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65 divided the depth indicator into total depth and mean depth for the comparison The values are calculated by Sum and Ave function to get the result of both total value and the average value of each indicator. Fig. 23 shows th e total value of network topological relationship, each of the value has significant growth from single road network to existing transportation network and then to optimized transportation network Nevertheless, the average value is quite different, whi ch result from the context background and interrelationship with other factors ( Fig. 2 4 ). The average mean depth value of both ETN and OTN are higher than that of road network because the nonmotorized routes expand ed accessible areas that were not able to reach by road network. The lower value of OTN Total Depth with optimized nonmotorized routes result from the better connection to the road network, while the existing nonmotorized routes have poor linkage to the ro ad network. The total value has concordance result as the average value of connectivity. The average values of integration have the same trend Fig. 24 The comparison of average value among four indicators 0 200 400 600 800 MeanDepth Integration TotalConnectivity TotalDepth MeanDepth Integration TotalConnectivity TotalDepth Road Network 18.97 0.42 588.78 463.36 Existing transportation Network 21.22 0.40 573.50 432.73 Optimized Transportation Network 19.26 0.44 760.33 540.09

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66 as the total value of integration. OTN has the highest average value of depth because it broadens the coverage of network service area so that more places that used to be far away are now accessible. Service efficiency Network analysis OD Matrix was applied to assess the least cost route among multiple origins and destinations. This research firstly calculated the centroid of each city limit polygon as origin points, and then used the polygon centroid of each traffic attractions as destination s to ran the OD Matrix. Fig. 25 OD Matrix in Alachua County based on the optimized transportation network

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67 The result in Fi g. 6 shows that the only origin that was not connected to the traffic attractions was the centroid of the town that managed by the adjacent county T hus all the cities and towns in Alachua County is well connected to traffic attractions with reasonable cost. While the only destination that is no t connected to any origin urban area located in the Paynes Prairie P reserve which has good accessibility when consider ing the real boundary rather than a centroid point For connection density aspect, it is evident that Gainesville, Alachua, Lacrosse, Wal do, and Hawthorne has centralized attractiveness among surrounding areas. Traffic attractions between the Gainesville and Alachua are more attractive and have higher potential to develop n onmotorized routes because they connected to three of the major Fig. 26 Serv ice coverage with time impedance in Gainesville

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68 citi es in the study area, respectively are Gainesville, Alachua, and Lacrosse. Such highly functional areas result in accord with the location of the optimized nonmotorized routes that were generated based on ecological suitability. When zooming into the city scale, this research set impedance of cycling travel time under four span s every 25 minutes in an hour (15, 30, 45, 60 minutes) with 16km/h to see the service areas that the traffic attractions can impact and be accessed. 46.03% of the Gainesville area ca n access traffic attractions within 15minutes by bike, 23.12% of the areas can access traffic attraction in 15 30minutes ( Fig. 26 ). Thus the half an hour service coverage, as the most urbanized area s in Gainesvill e with a high density of transportation routes is holding nearly 70% of the Gainesville city limit area. Such 30 minutes cycling time is acceptable for most travelers. The rest areas that are far away or with un urbanized land use are accessible within on e hour. Context suitability One typical example that has confliction between transportation and urban ecology in Gainesville is Hogtown Creek watershed. Multiple actions and strategies have been taken to reach the environmental, educational, and transporta tion goals (Gainesville (Fla.), 1994) however, even though trails were considered factors the concern o f the previous plan was focused on the confliction between the roadway and ecological conservation. Three trails at midst ream of Hogtown Creek were selected ( Fig. 27 ). By comparing with previous plan and existing condition trail 1 remains the same in the optimized nonmotorized route, which declares that this trail is eco friendly T rail 2 (Ring Park Trail), is slightly changed from going all the way along the creek to a detour at the north end where located between a lodge and residential complex. This makes the trail

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69 2 have larger service coverage while connecting to NW 16 th Ave at which is 60 meters away from a bus stop. This case shows the improvement of the continuous efforts. However, the reason that two existing trails are ecological friendly may result from the existing condition thus the trail path with low ecological sensit ive might because construction was already there. Trail 3 was newly added to the east of the midstream of Hogtown Creek, connecting from the southeast an institutional land, to the northwest mixed use community center. Most of the route segment is suitab le to the context, while several parts were going through low density residential that may need community participation for the decision making process. Fig. 27 Typical examples for context suitability analysis

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70 CHAPTER 5 CONCLUSION AND DISCUSSION Conclusion Optimized routes can improve transportation network top ologically The research process verified the research hypothesis by the topological relation that the optimized nonmotorized routes that produced based on ecological suitability can enhanc e transportation network The Depth, Integration, and connectivity i ndicator provider support that transportation network has better logic than the existing transportation network This part of conclusion was drawn based on analysis from the ecological perspective that supporting ecological benefits. Optimized transportati on network can serve traffic demands with efficiency Based on the first part, the eff ectiveness of the optimized transportation network has been tested by network analysis that all the traffic attractions can be reached with least cost route, and 70% of th e urbanized study area s are accessible with in half an hour by bike. Limitations Th e boundary of the study area limited potential regional corridor to connect with ecological conservation areas. A buffer with certain width outside the study area would contr ibute to th e regional connection and cooperation. Moreover, the data for both analysis and assessment came from secondary resources, while the lack of field work may cause inaccuracy and less credibility T he first hand resources are potentially helpful to verify analysis logic in turn.

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71 The other limitation happened in service efficiency part, where OD Cost Matrix was generated based on point features with the centroid of each oriented polygon, rather the actual shape and location of each polygon objects. T his lead to the necessary process to check with existing condition and context information. For instance, the Paynes Prairie P reserve has good transpor tation connection while its centroid point was dis connected to the origin ( Fig. 25 ) Confliction Between Ecological Priority a nd Built Environment Existing transportation network are generally designed and constructed according to the demand of human with maximum benefits: topographic and soil conditions were consider ed to save economic expense convenience to access and right of mental health were considered as prerequisites to select a location for transportation routes. Even though the designers and engineers have been increasingly aware of the importance of ecologi cal conservation, ecological benefits need to make a compromise when facing confliction with over rapid development and human desires. The study area, Gainesville, as major cultural and educational center of the region, was the one that did better jobs for ecological conservation than many other places. However, the conflictions between transportation and ecological areas are still quite common based on the tool based ecological suitability map. T o deal with these conflictions, strategies and regulations ar e indispensable to minimize the existing effects and avoid more future impacts. On the contrary, since the optimized routes were generated, the transfer of function from old to new should be done gradually while recovering the ecosystem and ecological capa city of the affected areas where existing un eco friendly routes are.

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72 Another notable dilemma is that the ecological suitability map was generated based on the existing condition, which means the high ecological conservation priority areas are located in e cological areas with limited human impact but might have more threaten ed if no actions were taken. H owever, the ecological area s that should be protected but already been destroyed by development are not likely to be recovered anymore. This research is a r eminder of such irreversible process. Feasibility of Practical Projects In order to make results acceptable and understandable for professions, public, and government this research was conducted based on widespread concerns of the context condition, inclu ding the ecological zoning, land use types, socioeconomic and census statistics, and existing constructions. However, other factors such as topographic information and construction cost were considered but not listed in the calculation process. This result from the principle to focus on ecological conservation orientation to figure out whether and to what extent the transportation network will be improved if temporarily get rid of the human benefits, thus produce nonmotorized routes from ecological assessme nt and evaluate the service efficiency by developing demands. In addition to the precautionary concerns, predictive modeling that evaluates the potential impact is essential to help with decision making and contribute to the follow up maintenance and manag ement. Some examples of such modeling are listed but limited to how the increased route density will affect the activity area, how the improvement of transportation infrastructure will affect the travel mode option, and what are the

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73 preferred nonmotorized connection types to integrate with existing transportation network. Further Work For better nonmotorized routes In addition to the ecological parameters, topographic information is essential to identify OTN suitability for nonmotorized routes more accurate ly suitable to the different type s of nonmotorized travel. Other factors such as the construction cost and parcel ownership are necessary to asse ss the feasibility. Overlapping cost map and ecological suitability map with proper weighting will be more comp rehensive to consider non human factors for identifying nonmotorized routes. Another dispensable part is the design context. This research examin ed the existing condition such as land use type and the proximity of existing transportation infrastructure, wh ile the socioeconomic factors, such as the community wiliness and economic benefits, were not included. Moreover, most analyses are conducted at the regional scale and city scale, while the suitability of the optimized nonmotorized routes to the real world needs to be verified delicately by zoom into the particular scale and the routes for implementation should be more accurate by integrating with contextual information. Meanwhile, the potential impact should be predictively analyzed by data based research For instance, gravity model could be applied to assess the localized effect of the optimized nonmotorized routes due to the uneven distribution from graphic perspective, LUCIS can be applied to see the relationship between transportation and

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74 land use, tr affic impact assessment and scenario planning could be adapted to predict the volume of nonmotorized travel in the optimized transportation network. For facilitating implementation In addition to identify ing the potential routes for nonmotorized transporta tion from the spatial aspect, connection to other types of transportation infrastructure is also important. For instance, good connection to public transportation to make it convenient for nonmotorized travelers to travel across the county could significan tly reduce the use of single rider vehicles. In addition innovative designs and creations are essential to minimize the confliction. Applying intersections where conflictions happen between road traffic and ecological migration corridor is another common strategy that has been widely applied Such innovation can also be addressed by separating activity areas, make use of the utilized time and occupancy period. Moreover, policies and regulations should come along with the whole life cycle of the optimized t ransportation network, from design to construct, and then to maintenance and management to improve sustainability and facilitate the reconciliation between development and nature.

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75 APPENDIX 1 IMPACT ASSESSMENT Traffic impact indicators and methodologies are high diversity among different cities, while the software applied are basically the same: Table 9 Indicators and Methodologies for TIA Guidance Location Indicators for Capacity A nalysis Methodology for Trip distribution Tas mania Road safety; Internal layout; Street furniture; Parking; Access for disabilities; Makes assumptions about the development Tai Po, Hongkong Annual traffic account; Peak hour traffic; Hourly trip; Junction; Internal paths; Transport model based on tra vel characteristics City of Harrisburg, PA Safety; Circulation patterns; Traffic control needs; Transit needs or impacts; Transportation system management; Neighborhood impacts; Parking facilities; Pedestrian and bicycle movements; Service and delivery ve hicle access; Analogy; Trip distribution model; Surrogate data. St. Lucie County City of Fort Pierce City of Port St. Lucie Geometry, including lane widths and turn lane lengths Heavy vehicle factor Directional factor Peak hour factor (PHF, no exceed 0.95 ) analysis to reflect unconstrained demand conditions Existing signal timing Segment length Class of roadway Maintenance jurisdiction Area type Posted speed LOS standard Scenario planning Level of service standard Multimodal considerations Mitigation optio ns

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76 Table 10 Preferred software for different types of analysis Type of analysis Preferred software Unsignalized intersections Highway Capacity Software (HCS) Signalized intersections Synchro software (latest version) Highw ay Capacity Software interrupted flow road segment Synchro software (latest version) Uninterrupted flow road segment HighPlan (latest version from FDOT) Other analysis Local government provision

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77 APPENDIX 2 CENSUS DATA Historical population census fr om 2000 to 2010 was collected every five years to show the demographic trends. Table 11 Population change among city/town level in Alachua County Community 2000 Census 2005 Census 2010 Gainesville 95,447 118,634 124,354 Alachua 6,098 7,402 9,059 High Springs 3,863 4,432 5,350 Newberry 3,316 4,261 4,950 Archer 1,289 1,230 1,118 Hawthorne 1,415 1,396 1,417 Waldo 821 832 1015 Micanopy 653 629 600 LaCrosse 143 186 360 Unincorporated 104,910 100,012 99,113 TOTAL 217,955 239,0 14 247,336 Table 12 Socio Economic data summary 2010 Permanent Population 247,336 Total Population 251,951 Permanently Occupied Dwelling Units 99,089 Transient and Permanently Occupied Dwelling Units 101,996 Total Service Employment 91,399 Total Commercial Employment 32,669 Total Manufacturing Employment 4,048 Total Other Industrial Employment 9,478 Total Employment 137,594 Permanent Population per Permanently Occupied Dwelling Unit 2.50 Total Population per To tal Occupied Dwelling Unit 2.47 Total Employment per Permanent Population 0.556

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78 Service to Total Employment 0.664 Commercial to Total Employment 0.237 Manufacturing to Total Employment 0.029 Other Industrial to Total Employment 0.069 Internal Per son Trips per Permanently Occupied Dwelling Unit 11.63 Internal Person Trips per Total Occupied Dwelling Units 11.29 Internal Person Trips per Employee 8.372

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79 APPENDIX 3 TRANSPORTATION STATISTICS Table 13 Journey to Work M ode Split (2000) Geographic Area Travel mode Drive Alone Carpool Public Transit Other Walk or Bike Gainesville 69.8% 12.2% 3.2% 3.9% 10.9% Alachua County 74.7% 12.7% 2.4% 4.2% 6.0% Florida 78.8% 12.9% 1.9% 4.1% 2.3% Table 14 Travel Time in Minutes (percent of workers) Geographic Area 0 9 10 19 20 29 30 44 45+ Gainesville 18.6% 49.6% 18.2% 7.7% 5.9% Alachua County 14.6% 40.1% 23.4% 14.2% 7.8% Florida 11.2% 30.0% 21.6% 22.3% 14.9%

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