Metrolina CommunityViz Model Technical Document - Initial Draft

Metrolina CommunityViz Model 16, v. 1.0 Technical Document

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Table of Contents

Section A – General Overview Section B – General Model Characteristics Section C – MCM Base Year Data Management Tool Section D – MCM Future Year Allocation Tool Section E – Technical Appendix

Metrolina CommunityViz Model 16, v. 1.0 Technical Document

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Section A: General Overview

Metrolina CommunityViz Model 16, v. 1.0

The Metrolina CommunityViz Model 16, v. 1.0 (MCM) is the product of a region-wide initiative to develop more consistent and replicable methods for allocating future year socioeconomic data to traffic analysis zones used in the Metrolina Region Travel Demand Model 17, v. 1.0. It normalizes the data collection process, model architecture and data output formats used by three metropolitan planning organizations and two rural planning organizations, and provides more efficient processes and tools (recognizing the inherent relationships between land use, transportation and urban form) for studying the components of a sustainable regional transportation system.

The Metrolina CommunityViz Model 16, v. 1.0 Technical Document summaries the study area, analysis tools and model outcomes that will support other transportation planning studies or processes being completed now or in the future for the region (or portions thereof). The document is organized into five main sections: General Overview ― A brief overview of the study area, scenario planning and scenario planning tools, linkage to other analysis tools, base year conditions in the study area, alternative growth scenarios under study, and ideas for moving forward.

General Model Characteristics ― General information about CommunityViz software, including: system requirements, key terms and definitions, and the official Metrolina CommunityViz Model 16, v. 1.0 location and status.

MCM, Base Year Data Management Tool ― A summary of the Metrolina CommunityViz Model 16, v. 1.0 base year data management tool created using CommunityViz software; including data needs, model architecture, theory and features behind components of the model, data output and calibration activities.

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MCM, Future Year Allocation Tool ― A summary of the Metrolina CommunityViz Model 16, v. 1.0 future year allocation tool created using CommunityViz software; including data needs, model architecture, theory and features behind components of the model, data output and calibration activities.

Technical Appendix ― A compilation of specific data, tables, maps, equations and assumptions used to create the Metrolina CommunityViz Model 16, v. 1.0. Information in the appendix is useful for maintaining the current Model and/or adapting it for other scenario planning initiatives contemplated in the future.

The Metrolina Region CommunityViz Initiative Data Summary Document is a companion to this technical document. It summarizes the data collection/coding process for the Metrolina CommunityViz Model 16, v. 1.0; including 1) an inventory of data and resources used in the models, 2) a summary of outreach meetings/verification activities with project partners, and 3) an appendix with data maps, meeting minutes, etc. important for building model components.

Together, the two documents — the Metrolina Region CommunityViz Initiative Data Summary Document and the Metrolina CommunityViz Model 16, v. 1.0 Technical Document — provide the background information created to support the Metrolina CommunityViz Model 16, v. 1.0.

Study Area Description The study area for the Metrolina CommunityViz Model 16, v. 1.0 (MCM) is expansive, covering 4,623 square miles and 913,719 parcels. The geography includes two states, ten counties, and 81 cities or towns ranging in size from large, metropolitan centers to suburban, bedroom communities to rural crossroads. Environmental features — lakes, rivers, water basins, prime

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agriculture soils, and air quality — bind the region together and blur political boundaries.

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Together, the MCM study area represents a land area larger than three U.S. states (Rhode Island, Delaware and Connecticut) and a population greater than fourteen U.S. States (US Census Bureau, 2010). US Census data also indicates the study area was part of the fastest growing metropolitan region in the United States over one million people between 2000 and 2010, and projections indicate the population could nearly double in the next four decades (2010 to 2050).

The region is home to the world headquarters for seven Fortune 500 companies (2015 rankings), as well as other major employers in medical, manufacturing, energy, financial and transportation business sectors. Over half of the metropolitan region’s workforce lives in one county and works in another, which reinforces the need for more coordinated decision-making processes in regards to land use, housing, transportation, economic development and urban design.

Three metropolitan planning organizations and two rural planning organizations operate within the MCM study area (see Map A1 on pg. A-3).

The MCM study area generally matches the boundaries established for the Metrolina Region Travel Demand Model 17, v. 1.0, with the addition of Anson County and the omission of Cabarrus, Rowan and Catawba Counties.

Project Partners The Metrolina CommunityViz Model 16, v. 1.0 was created with the help and guidance of federal, state, regional and local government agencies working together as a project steering committee.

The following groups were represented on the committee:  

Federal Highway Administration North Carolina Department of Transportation

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       

Charlotte Regional Transportation Planning Organization Gaston-Cleveland-Lincoln Metropolitan Planning Organization Rock Hill-Fort Mill Area Transportation Study Rocky River Rural Planning Organization Centralina Council of Governments Catawba Regional Council of Governments Charlotte Department of Transportation Charlotte-Mecklenburg Planning Department Iredell County Planning Department Union County Planning Department

County-level coordination meetings were also held throughout the region to engage local governments in the data collection and model build processes. Detailed information about these activities is provided in the Metrolina Region CommunityViz Initiative Data Summary Document.

Base Year Conditions The MCM study area is part of a larger metropolitan region that has grown in population every decade for the last 100 years (CONNECT Our Future Regional Scan Document, pg. 10).

Officials estimate 2.12 million people call the MCM study area home in 2015. They also estimate 1.29 million people work in the MCM study area in 2015.

Current county-level population and employment estimates for the MCM study area (2015) endorsed by participating metropolitan planning organizations and rural planning organizations are provided in the technical appendix.

Anticipated Growth Trends The MCM study area grew tremendously over the last decade, influenced by strong job growth, vast amounts of undeveloped land, and the influx of new residents from outside the region. Growth is expected to accelerate through the next few

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Map A1: Study Area Map for the Metrolina CommunityViz Model 16, v. 1.0

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MCM Study Area — Base Year Condition Profile (2015)

decades because of the region’s affordable housing, relative low cost-of-living, temperate weather, and emerging business growth sectors. Forecasters anticipated X.XX million people will call the MCM study area home by 2045; an increase of XX% from 2015. Employment is expected to increase to X.XX million in 2045; an increase of XX% from 2015.

County-level growth forecasts for the MCM study area (2020 to 2045) endorsed by participating metropolitan planning organizations and rural planning organizations are provided in the appendix of this document.

Scenario Planning Overview Scenario planning represents the next generation of analytical processes created to evaluate the influence of different development types, locations, patterns and intensities on the efficiency of a proposed transportation system. Visualization

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of the interaction between land use, urban form and transportation decisions, as well as the causational factors that explain the push-pull relationship between them, provides community leaders with the information needed to evaluate the consequences of potential actions.

Building on this momentum, the Federal Highway Administration, Environmental Protection Agency, and other federal agencies are actively promoting the use of scenario planning by state departments of transportation, metropolitan planning organizations, rural planning organizations, and local governments to better integrate transportation and land use decisions for preparing a Metropolitan Transportation Plan or Comprehensive Transportation Plan.

Evaluating the relationship between land use, urban form and regional travel behavior in a scenario planning analysis produces several benefits. When considered together, decisions and

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MCM Study Area — Future Year Condition Profile (2045)

making the possibility of real choices for various modes of travel both accessible and attractive.

investments regarding all three elements can have a significant impact on the Metrolina Region: 

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The impacts to sensitive land uses may be minimized when facilities identified for transportation investments are located after considering appropriate land use patterns and development intensities for the area.

Prime locations for development may be stimulated if transportation investments consider available capacity or appropriate mobility options.

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Complementary activities may be placed next to existing or planned transportation infrastructure, making the most of land use opportunities and transportation investments.

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The quantity and location of travel demand may be influenced by land use decisions,

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New development locations, types, patterns and intensities in an area could significantly improve transportation system performance without spending significant transportation dollars (stretching existing system capacity with demand-side solutions before making expensive investments).

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A study of land use, urban form and travel behavior in a single theater brings together all the decision-makers for instilling real change — local governments, state departments of transportation, regional planning agencies, the development community, special interest groups, etc.

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What is CommunityViz? CommunityViz is an extension of ESRI’s ArcGIS desktop software that facilitates the visualization and comparison of alternative development scenarios. It was originally developed by the Orton Family Foundation, a non-profit group that focuses on technology and tools for more-informed community decision-making.

There are two components of CommunityViz software. The first is Scenario 360, which is a two-dimensional map and data analysis component of the software. It adds the functionality of a spatial spreadsheet to ArcGIS for Desktop software, similar to how a spreadsheet program like Microsoft Excel handles numerical data. Dynamic calculations embedded in the spatial spreadsheet are controlled by user-written formulas that change value as referenced input values change. The impact of physical development or policy decisions under consideration may be measured side-by-side in two or more growth scenarios contemplated in the software.

The second component of CommunityViz software, Scenario 3D, is a visualization tool that constructs threedimensional models of buildings, roads, landscapes, or entire communities using two-dimensional information generated in the Scenario 360 analysis.

More information on CommunityViz and its capabilities for regional planning is available on their website (www.communityviz.com) or The Planner’s Guide to CommunityViz published by the American Planning Association in 2011.

Ultimately, the scenarios themselves are fictitious stories about the future. They are not forecasts or predictions, but possible futures that may come to pass based on what already exists, emerging trends, or the community’s desires to change course for the future. The essential requirement of any growth scenario was that it be plausible, within the realm of what exists or what could be.

Relationship to the Metrolina Region Travel Demand Model One of the tools available for studying long-term impacts to the regional transportation system is the Metrolina Regional Travel Demand Model (MRM), which is a computer program that forecasts future year demand on existing and planned transportation facilities using anticipated land use, demographic information and travel patterns unique to the region. Planning horizon years in the travel demand model consider

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conditions 10, 20 and 30 years beyond base year conditions. Approximating future year conditions on the transportation system helps transportation officials assess the implications of growth, compare alternative transportation solutions, and provide a framework for measuring the impact of policy decisions.

The foundation for the MRM travel demand model is socioeconomic data — including population, housing, students and employment estimates — organized into distinct geographic subareas referred to as traffic analysis zones (TAZs). Collectively, this information represents the assumed growth and development potential for the Metrolina Region. Demand on the transportation system (trip generation) is calculated directly from the model’s socioeconomic data.

Before the Metrolina CommunityViz Model 16, v.

1.0, updating socioeconomic data for the MCM

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Metrolina CommunityViz Model 16, v. 1.0

portion of the MRM study area was time intensive, and the top down – bottom up, manual process created significant challenges for allocating future year growth in the region. Specifically, it 1) created a miss-match between demand and supply statistics for growth allocation in some growth categories and in some parts of the region, 2) marginalized some of the unique conditions for cities and towns in the region, 3) used a nonstandardized methodology for translating local plans and ordinances into buildout potential for the region, and 4) used a non-standardized methodology for determining growth hot spots (areas most likely to develop by horizon period) throughout the region. The manual process also limited the ability to evaluate the effects of alternative development patterns on the efficiency of the regional transportation system.

Socioeconomic data allocated in the Metrolina CommunityViz Model 16, v. 1.0 (traffic analysis zone level reporting) will stream line the workflow for running the Metrolina Regional Travel Demand Model 17, v. 1.0. Output data will be normalized for the MCM portion of the MRM study area and formatted for direct input into the travel demand model software; saving time and potential errors translating data from several sources.

Relationship to the Metropolitan Transportation Plan The starting growth scenario for the Metrolina CommunityViz Model 16, v. 1.0 — community plans — meets federal rules and requirements for developing the Metropolitan Transportation Plans (MTP) required for all metropolitan planning organizations in the region. Specifically, it considers land use and development controls reflected in adopted local government plans and ordinances for preparing the document. Data and tools for the Community Plans Growth Scenario will inform the MTP planning processes, and will be useful for identifying, prioritizing and scheduling specific transportation projects included in the MTP documents.

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The Metrolina CommunityViz Model 16, v. 1.0 also affords the opportunity to study alternative growth scenarios in a MTP planning process, highlighting the relationship between land use (demand), urban form (design), and transportation (supply) for influencing travel behavior and promoting a more sustainable regional transportation system.

Alternative growth scenarios help validate the planning process and build support (both empirical and political) for a preferred growth scenario that influences socioeconomic data in the Metrolina Regional Travel Demand Model 17, v.

1.0 and specific project recommendations in the individual Metropolitan Transportation Plans.

Relationship to the Comprehensive Transportation Plan The starting growth scenario for the Metrolina CommunityViz Model — community plans — also meets rules and requirements in North Carolina for developing the Comprehensive Transportation Plans (CTP) required for all metropolitan planning organizations and rural planning organizations in the region. Specifically, it considers land use and development controls reflected in adopted local government plans and ordinances for preparing the document. Data and tools for the Community Plans Growth Scenario will inform the CTP planning processes, and will be useful for identifying, prioritizing and scheduling specific transportation projects included in the CTP documents.

Alternative Growth Scenarios Two growth scenarios were prepared for building and testing the Metrolina CommunityViz Model 16, v. 1.0: a Community Plans Growth Scenario and the CONNECT Preferred Growth Concept.

Each scenario was different enough to pose real choices for how the MCM study area might develop under one or more planning initiatives.

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A brief summary of the growth scenarios is provided on pages A-9 through A-12.

Each growth scenario used identical projections for population and employment between 2015 and 2045. The number and mix of dwelling units in each scenario were different to account for competing development patterns and intensities or housing preferences represented in the scenarios.

An analysis of transportation impacts (and their trade-offs) for each growth scenario will be contemplated in future updates to the various Metropolitan Transportation Plans and Comprehensive Transportation Plans required throughout the region.

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Metrolina CommunityViz Model 16, v. 1.0

Community Plans Growth Scenario

Growth Forecast (2045)

The Community Plans Growth Scenario shows how the region might develop if locallyadopted plans are followed. People in different parts of the region would experience growth in different ways. Residents in some communities would be able to walk, bike or use transit to get from their homes to work or play. Others would enjoy a more suburban or rural lifestyle; greater distances between home, work and play; and greater reliance on a car.

Households

xxx,xxx

Household Population

xxx,xxx

Group Quarters Population

xxx,xxx

Students

xxx,xxx

Employees

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Some communities would shift their infrastructure investment to support “growth within”, while other communities would tend to invest more in infrastructure to support

“outward growth.” Farmland would be preserved in some counties but not others, and housing choices would stay about the same as today.

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General Development Map (Full Build Out)

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CONNECT Preferred Growth Concept

Growth Forecast (2045)

The Preferred Growth Concept for the CONNECT Region represents the thoughts, ideas and priorities captured in outreach meetings, small group activities, and on-line engagement tools between March and July 2014. The scenario supports major (re)investment in walkable downtowns, mixeduse activity centers, walkable neighborhoods, and major transit corridors region-wide. More compact development patterns would help increase housing choices, travel choices, and open space preservation; create new job centers; and control the cost of providing government facilities and services by concentrating development in smaller service areas.

Households

xxx,xxx

Household Population

xxx,xxx

Group Quarters Population

xxx,xxx

Students

xxx,xxx

Employees

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Land outside designated growth areas would be preserved as rural or working farms. The Preferred Growth Concept for the CONNECT Region was unanimously endorsed by the CONNECT Consortium Program and Policy Forums in July 2014.

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General Development Map (Full Build Out)

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Metrolina CommunityViz Model 16, v. 1.0 Â

Moving Forward The Metrolina CommunityViz Model takes advantage of tools and processes available in the software today to quickly allocate future year socioeconomic data over multiple horizon periods.

Continued updates, both in terms of input data and model scripts, should be made to keep it relevant and responsive to needs in the region.

Subsequent sections in the technical document explain all of the data and components created for the Metrolina CommunityViz Model. It is assumed staff for the three metropolitan planning organizations and/or two rural planning organizations will run and adapt the model in future years using the information presented herein and their increasing command of the software.

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Section B: General Model Characteristics

Metrolina CommunityViz Model 16, v. 1.0

This section of the document summarizes general information about CommunityViz software.

System requirements, key terms and definitions, and the official model location/status discussions apply to both components of the Metrolina CommunityViz Model 16, v. 1.0: the base year data management tool (described in Section C) and the future year allocation tool (described in Section D).

Overview of CommunityViz Software CommunityViz is an extension of ESRI’s ArcGIS desktop software that facilitates the visualization and comparison of alternative development scenarios. It was originally developed by the Orton Family Foundation, a non-profit group that focuses on technology and tools for more informed community decision-making.

There are two software components in CommunityViz. The first is Scenario 360, which is a two-dimensional map and data analysis component of the software. It adds the functionality of a spatial spreadsheet to ArcGIS for Desktop software, similar to how a spreadsheet program like Microsoft Excel handles numerical data. Dynamic calculations embedded in the spatial spreadsheet are controlled by user-written formulas that change value as referenced input values change. The impact of physical development or policy decisions under consideration may be measured side-by-side in two or more growth scenarios contemplated in the software.

The second component of CommunityViz software, Scenario 3D, is a visualization tool that constructs three-dimensional models of buildings, roads, landscapes or entire communities using two-dimensional information generated in the Scenario 360 analysis.

More information on CommunityViz and its capabilities for regional planning is available on their website (www.communityviz.com) or The

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Planner’s Guide to CommunityViz published by the American Planning Association in 2011.

System Requirements CommunityViz is an extension for all levels of ESRI’s ArcGIS for Desktop software (Basic, Standard or Advanced). The current version, CommunityViz v. 5.0, requires ArcGIS for Desktop v. 10.2 or greater. Other software requirements include Windows 7 or 10, Microsoft .Net Framework 3.5 or above, and Windows DirectX 9.0c or higher (required for running Scenario 3D only).

Minimum, preferred and ideal hardware configurations published by the software developer for running CommunityViz are summarized in Table B1.

Key Terms & Definitions CommunityViz uses several terms inside the software to organize data, build equations and present results. Knowing these terms and how they relate to each other is critical for updating (or expanding capabilities) in the Metrolina CommunityViz Model 16, v. 1.0. A brief summary of key terms used in the software is provided below. See the Help Menu in CommunityViz for more information.

Analysis An analysis is the term used in CommunityViz to describe a project file; similar to a Microsoft Word document or Microsoft Excel spreadsheet. It includes the map data, scenarios, calculations and data for the work you are doing.

Data Data includes all of the shapefiles, raster (grid) files or tables referenced in an analysis.

CommunityViz uses a file geodatabase structure to store data that is dynamic (all layers that contain

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 Table B1: Basic System Requirements for Running CommunityViz Software System Requirement RAM Processor Available Hard Disk Space Three-Button Standard Mouse Dedicated Graphics Card, Minimum Texture Memory at least one Scenario 360 formula). Non-dynamic data is stored in the analysis outside of the geodatabase. Data layers that are dynamic may refer to one or more other data layers outside the analysis geodatabase for computing attribute or indicator values.

Map Feature A feature represents the individual point, line or polygon illustrated on a work map. Many features in the same data set depict geographic information. Features and the data associated with them are represented by rows in an attribute table.

Attribute Attributes are fields (columns) in a spatial or numeric table that describe the characteristics associated with features in a data set. Each feature is assigned a value for each field in the table, which may be stored directly in the table cell or referenced from an external lookup table. Static attributes do not change values in the analysis.

Dynamic attributes update automatically using formulas written in CommunityViz that respond to changes made in other areas of the analysis.

Attribute data may be exported from CommunityViz to other software platforms (e.g., Microsoft Excel) for reporting or other analyses.

Assumption Assumptions are used as one input to capture the values, conditions or opinions important to an analysis. They are often referenced in the formula June 14, 2016

Minimum 512 MB 750 MHz 1 GB Yes 32 MB

Preferred 1 GB 1 GHz 5 GB Yes 64 MB

Ideal 1+ GB 2+ GHz 5+ GB Yes 128+ MB

for dynamic attributes, which update automatically every time the assumption values change. Assumption values may be numeric, text or a yes/no format.

Assumptions may also be fixed or variable. A fixed assumption may not be changed in the analysis, and will affect all growth scenarios the same way. A variable assumption may be changed in the analysis using a slider bar, choice button or drop-down list. It can also vary across different development scenarios.

Indicator Indicators are impact or performance measures that apply to an entire scenario. They summarize conditions using a single statistic similar to the “field summarize� function in ArcGIS. Results are displayed in charts or tables for monitoring conditions inside CommunityViz, and often become the criteria for ranking growth alternatives in a scenario planning process. Indicators update automatically using formulas written in the software that respond to changes made in other areas of the analysis.

Indicator values may be exported from CommunityViz to other software platforms (e.g., Microsoft Excel) for reporting or other analyses.

Charts Values for indicators or assumptions in CommunityViz are displayed using charts. They update automatically within the analysis and display their previous values for comparison. Data

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may be presented by item, active scenario or across all scenarios. Charts may be displayed in bar, line, pie, point, doughnut or stacked formats.

Threshold lines may be used in combination with charts to determine if a goal, target or constraint condition has been reached because of changes tested for the scenario.

Categories Categories are used to organize groups of attributes, assumptions, indicators or charts in the analysis. They may be filtered or sorted for a larger analysis to keep track of information.

will be maintained by the Charlotte Department of Transportation, Regional Modeling Section.

Copies of the Metrolina CommunityViz Model 16, v. 1.0 will be made available to all metropolitan planning organizations and rural planning organizations (or their partners) in the MCM study area that want to use the tool for transportation planning studies or processes being completed now or in the future (e.g., metropolitan transportation plans, comprehensive transportation plans, congestion management plans, corridor studies, etc.).

Scenarios CommunityViz is capable of analyzing one or more growth scenarios simultaneously. All scenarios contain the same map layers, static attributes, formulas for dynamic attributes, assumptions, indicators and charts. Map features or values for dynamic attributes, assumptions, indicators and charts may vary between the scenarios.

Each growth scenario is displayed in the table of contents window for ArcGIS Desktop. The active scenario is displayed in the work map. Switching between scenarios in the analysis is done through the Scenario 360 window.

External Lookup Table CommunityViz includes a feature that links tables in Scenario 360 to external tables so when changes are made to the external table they are automatically recognized and updated in the analysis. This feature can be used for linking external tables in text (*.txt), comma separated values (*.csv) or Microsoft Excel (*.xls or *.xlsx) formats.

Official Model Location & Status The official Metrolina Community Model 16, v. 1.0 used to generate socioeconomic data for the Metrolina Region Travel Demand Model 17, v. 1.0 Pg. B-3

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Section C: Metrolina CommunityViz Model, Base Year Data Management Tool

Metrolina CommunityViz Model 16, v. 1.0 Â

The Metrolina CommunityViz Model 16, v. 1.0 (MCM) includes two major components: a base year data management tool and a future year allocation tool. The base year data management tool organizes point, polygon and numeric data created by metropolitan planning organizations and rural planning organizations in the MCM study area into a single, comprehensive data set for running the Metrolina Region Travel Demand Model 17, v. 1.0 (MRM). Information summarized in the MCM data set includes population, dwelling units (households), students and employees (all using control total subcategories included in the MRM). The base year for the Metrolina CommunityViz Model 16, v.

1.0 is 2015.

General topics addressed for the MCM base year data management tool include: unit of analysis, starting data, model architecture, data output and calibration activities.

Unit of Analysis: Traffic Analysis Zone The unit of analysis for the base year data management component of the Metrolina CommunityViz Model 16, v. 1.0 is the traffic analysis zone. Population, dwelling unit (household), student and employee data are all aggregated to this unit of analysis for data reporting.

Traffic analysis zones are distinct geographic subareas used in the Metrolina Region Travel Demand Model 17, v. 1.0 to capture assumed growth and development for base year (2015) and future year conditions (2020 to 2045). They vary in shape and size throughout the MCM study area, but always coincide with census geographies (census tracts, census block groups or census blocks) to improve base year demographic inventory processes.

The Metrolina Region Travel Demand Model 17, v.

1.0 uses 2,955 traffic analysis zones to represent conditions in the MCM study area. Twenty-one

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additional traffic analysis zones are used to represent conditions in Anson County (as part of the MCM study area).

Starting Data Sets Base year data for dwelling units (households), population, students and employees in the MCM study area rely on several published data sources.

The Metrolina Regional and County Control Totals Working Committee (including representatives from the FHWA, NCDOT and MPOs and RPOs in the MCM study area) identified a shared project approach, common data sources, preferred reporting categories, acceptable data output formats, and a comprehensive work schedule to prepare base year control totals for the Metrolina Regional Travel Demand Model 17, v. 1.0. Data was summarized by county, traffic analysis zone or point location for all thirteen control total categories used in the MRM, and submitted to the project team for running the base year data management component of the Metrolina CommunityViz Model 16, v. 1.0.

MPOs and RPOs in the MCM study area varied some of the assumptions, work flows, calculations, partner activities, etc. used to create their base year data within the shared framework. A detailed summary of the processes used by MPOs and RPOs in the MCM study area to calculate/summarize/report base year data is provided in the technical appendix (reported by individual MPO or RPO).

Starting data for the MCM study area is described here under four general headings: dwelling units (households), population, students and employees.

Dwelling Units (Households) Source data for dwelling units (households) in the MCM study area starts with 2010 US Census Decennial Data organized by traffic analysis zone.

Five years of growth is added to the 2010 base year data using annual socioeconomic update

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 information provided by metropolitan planning organizations and rural planning organizations represented in the MCM study area (data reported by county and traffic analysis zone).

Group Quarters Population Survey administered for the North Carolina Office of State Budget and Maintenance or similar sources in either North Carolina or South Carolina.

The Charlotte Department of Transportation, Regional Modeling Section collected dwelling unit (household) data from the individual metropolitan planning organizations and rural planning organizations, verified it was complete, and sent everything to the project team for creating the base year data management component of the Metrolina Community Model 16, v. 1.0 (data sets were submitted for each MPO and RPO individually using either ArcGIS shapefile or Microsoft Excel formats).

The Charlotte Department of Transportation, Regional Modeling Section collected group quarters population data from the individual metropolitan planning organizations and rural planning organizations, verified it was complete, and sent everything to the project team for creating the base year data management component of the Metrolina Community Model 16, v. 1.0 (data sets were submitted for each MPO and RPO individually using either ArcGIS shapefile or Microsoft Excel formats).

Dwelling Unit (Household) Population

Students

Source data for population in the MCM study area starts with the base year data for dwelling units (households) described above. Average persons per household statistics applied to dwelling unit data (producing population statistics by county and traffic analysis zone) are based on information published in the US Census Bureau, 2010-2014 American Community Survey, Five Year Estimates (Tables B25033 and S2504) or localized data.

Source data for students in the MCM study area starts with 2015 student enrollment (reported for the twentieth day of the school year) for public elementary, middle and high schools; or similar information published on various school board websites. Meetings and/or telephone calls with colleges and universities, public school officials and private school officials created additional student enrollment information by location and grade level and/or confirmed data previously collected was current.

The Charlotte Department of Transportation, Regional Modeling Section collected population data from the individual metropolitan planning organizations and rural planning organizations, verified it was complete, and sent everything to the project team for creating the base year data management component of the Metrolina Community Model 16, v. 1.0 (data sets were submitted for each MPO and RPO individually using either ArcGIS shapefile or Microsoft Excel formats).

The Charlotte Department of Transportation, Regional Modeling Section collected student data from the individual metropolitan planning organizations and rural planning organizations, verified it was complete, and sent everything to the project team for creating the base year data management component of the Metrolina Community Model 16, v. 1.0 (data sets were submitted for each MPO and RPO individually using either ArcGIS shapefile or Microsoft Excel formats).

Group Quarters Population Source data for group quarters population in the MCM study area starts with information from the

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Employees Source data for employees in the MCM study area starts with InfoUSA data, a proprietary database maintained for the entire United States that currently represents approximately 14.0 million businesses. The database is updated using more than 5,000 public sources (phone directories, new business filings, daily utility connections, annual business reports, SEC and 10k filings, USPOS national change of address data, county courthouse and public record notices, etc.). More than 20.0 million telephone calls are made each year to verify and collect additional information from businesses in their database. Data is continuously updated through web research, news monitoring and user-generated content.

The North Carolina Department of Transportation purchases statewide data from InfoUSA (including annual updates) and provides it to metropolitan planning organizations and rural planning organizations for their use. The Rock Hill-Fort Mill Area Transportation Study organization purchases similar data for York and Lancaster Counties in South Carolina.

Point file data purchased from InfoUSA (verified and pre-verified versions) is reviewed by metropolitan planning organizations and rural planning organizations in the MCM study area to 1) confirm business types, employee counts and business locations in the database and 2) remove duplicate records for the same business in the same location in the database. MPO and RPO officials completed web searches, cross-referenced information with other employment databases, and/or contacted major businesses in the MCM study area via telephone to confirm locations and number of employees for the 2015 base year.

(Note: the size of the database from InfoUSA means MPOs and RPOs needed to prioritize their resources for confirming business location and employee count data for the MCM study area. Major employers — reporting more than 100 or 150

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employees each, depending on the MPO or RPO reporting — were targeted for validation based on available resources.)

Base Year Control Totals The technical coordination committee and policy advisory committee for each MPO and RPO in the MCM study area certified the data sets generated by the Metrolina Regional and County Control Totals Working Committee in July and August 2016 (both base year and future year conditions). Data was summarized for thirteen growth control categories consistent with the needs of the base year data management component of the Metrolina CommunityViz Model 16, v. 1.0 and the Metrolina Region Travel Demand Model 17, v. 1.0:             

residential dwelling units low-traffic industrial employees high-traffic industrial employees low-traffic retail employees high-traffic retail employees low-traffic service employees high-traffic service employees education employees office employees grade K-8 students grade 9-12 students college/university students group quarters population

A table summarizing base year control totals (2015) used for the CommunityViz model is provided in the technical appendix.

Model Architecture The base year data management component of the Metrolina CommunityViz Model 16, v. 1.0 uses a region-wide modeling platform to summarize data by traffic analysis zone. Data is reported for dwelling units (households), population, students and employees using data provided by the

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individual MPOs and RPOs in the MCM study area (organized by control total subcategories included in the MRM).

Information for specific processes in the model architecture is provided below. Table C1 identifies the specific process by data category and

by MPO or RPO for migrating data into the CommunityViz model. The difference in processes used for importing data in CommunityViz is a function of the data format used by MPOs or RPOs for submitting data (Microsoft Excel worksheet, ArcGIS polygon shapefile, or ArcGIS point shapefile).

Table Join Process in ArcGIS In ArcGIS, the table join data tool is used to append the fields and values of one table to another using a common attribute (in this case the Metrolina Region Travel Demand Model 17, v. 1.0 traffic analysis zone identification number). The table join process is used for data transferred to the project team for the Metrolina CommunityViz Model 16, v. 1.0 in either Microsoft Excel worksheet or ArcGIS polygon shapefile formats.

Data in the joined table is sorted using descending order by traffic analysis zone identification number to isolate features for the specific MPO or RPO data set. The “field calculator” tool in ArcGIS is used to transfer data from the MPO or RPO to region-wide traffic analysis zone files in CommunityViz (“MCM_TAZ3490” or “MCM_ANSON_TAZ”) using paired column headings. The table join is removed for each MPO or RPO once all thirteen MRM control total categories have been copied into the regionwide traffic analysis zone files.

The process is repeated for each MPO or RPO that provides data in Microsoft Excel worksheet or ArcGIS polygon shapefile formats (see Table C1).

Overlap Sum Function in CommunityViz In CommunityViz, the overlap sum function adds together the values of an attribute for all features in one data set that fall within the boundary of features in another data set. Data is reported as the sum of all underlying features within the boundary of the larger feature. For example, thousands of points in the MCM study area

Table C1: Specific Processes Used for Assigning Base Year Data to Traffic Analysis Zones in CommunitiyViz, Reported by General Control Total Category and Individual MPO or RPO Agency Dwelling Units

Dwelling Unit Population

Group Quarters Population

Students

Employees

Gaston-Cleveland-Lincoln Metropolitan Planning Organization

Table Join

Table Join

Table Join

Table Join

Table Join

Charlotte Regional Transportation Planning Organization (Iredell County)

Table Join

Table Join

Table Join

Table Join

Overlap Sum

Charlotte Regional Transportation Planning Organization (Meck. County)

Table Join

Table Join

Table Join

Overlap Sum

Overlap Sum

Charlotte Regional Transportation Planning Organization (Union County)

Table Join

Table Join

Table Join

Overlap Sum

Overlap Sum

Rock Hill-Fort Mill Area Transportation Study

Table Join

Table Join

Table Join

Overlap Sum

Overlap Sum

Rocky River Rural Planning Organization

Table Join

Table Join

Table Join

Overlap Sum

Overlap Sum

Agency

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Metrolina CommunityViz Model 16, v. 1.0

representing employees are quickly summarized by traffic analysis zone using the boundary of each traffic analysis zone as the criteria for adding together underlying point feature values (in this case by MRM employment control total category).

The overlap sum function is run in a single “OVR_WORK” dynamic attribute variable created for the CommunityViz model, which is modified several times to represent the different control total categories and MPO/RPO areas of interest for importing data using this method (see Table C1). Data in the OVR_WORK column is sorted using descending order to isolate features for the specific MPO or RPO data set. The “field calculator” tool in ArcGIS is used to transfer data from the OVR_WORK column to the corresponding category in the region-wide traffic analysis zone files (“MCM_TAZ3490” or “MCM_ANSON_TAZ”).

The process is repeated for each MPO or RPO that provides data in ArcGIS point shapefile format.

Reporting Geographies

existing conditions. These activities instilled confidence in the analysis tools and helped with reaching greater consensus among metropolitan planning organizations and rural planning organizations in the MCM study area for the results.

A summary of key calibration/validation activities performed for the Metrolina CommunityViz Model 16, v. 1.0 is provided below.

Project Steering Committee A project steering committee for the Metrolina Community Model Initiative was formed to provide direct oversight and counsel for building the model and collecting data identified to run it. Those on the steering committee represented a broad base of interests, viewpoints and concerns in the MCM study area. The following groups were represented on the committee:    

Base year population, dwelling unit (household), student and employee controls totals (reported for thirteen control total sub-categories used in the Metrolina Regional Travel Demand Model 17, v.

1.0) are summarized by MRM sub-district using the “summary statistics” tool in ArcGIS software.

Settings used for the “summary statistics” tool in ArcGIS software, and a summary table with base year control totals reported by MRM sub-district are included in the technical appendix.

Model Calibration A significant amount of time was reserved in building the Metrolina CommunityViz Model 16, v. 1.0 to validate the model architecture and methodology, evaluate different base year data sources, and calibrate results against observed Pg. C-5

       

Federal Highway Administration North Carolina Department of Transportation Charlotte Regional Transportation Planning Organization Gaston-Cleveland-Lincoln Metropolitan Planning Organization Rock Hill-Fort Mill Area Transportation Study Rocky River Rural Planning Organization Centralina Council of Governments Catawba Regional Council of Governments Charlotte Department of Transportation Charlotte-Mecklenburg Planning Department Iredell County Planning Department Union County Planning Department

Nine meetings with the project steering committee were held between April 2015 and June 2016 to build components of the Metrolina CommunityViz Model 16, v. 1.0. They were generally used to integrate MCM model components with 1) the model architecture and data input needs of the Metrolina Regional Travel Demand Model 17, v. 1.0, 2) base year dwelling

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 unit (household), dwelling unit (household) population, group quarters population, student and employment data management tools, and 3) annual socioeconomic data update processes and data protocols.

generated by the Metrolina Regional and County Control Totals Working Committee (certification meetings were held in July and August 2016) for updating their own metropolitan transportation plans and comprehensive transportation plans.

Meeting agendas and summary minutes for the nine project steering committee meetings are provided in the Metrolina Region CommunityViz Initiative Data Summary Document.

Meeting agendas and summary minutes for the control total certification meetings are available from each MPO or RPO in the MCM study area.

Internal Quality Control Metrolina Regional and County Control Totals Working Committee The Metrolina Regional and County Control Totals Working Committee is responsible for summarizing growth data (base year and future year conditions) for the MRM study area. It is hosted by the Charlotte Department of Transportation, Regional Model Section, and includes representatives from all the metropolitan planning organizations and rural planning organizations in the MRM study area as members.

The project team used regular coordination calls, emails, web meetings and on-site coordination meetings to build and calibrate the Metrolina CommunityViz Model 16, v. 1.0 and validate the data used to create it. Key quality control issues addressed by the team included: data quality and availability, model architecture, model input data and values, beta model results and reporting geographies.Â

In 2016, the Working Committee identified a shared project approach, common data sources, preferred reporting categories, acceptable data output formats, and comprehensive work schedule to prepare base year and future year control totals for the Metrolina Regional Travel Demand Model 17, v. 1.0. Data was summarized by county and reporting period (2015, 2020, 2025, 2030, 2035, 2040 and 2045) for all thirteen control total categories used in the MRM. Meeting agendas and summary minutes for four meetings with the Metrolina Regional and County Control Totals Working Committee are available from the Charlotte Department of Transportation, Regional Model Section.

Control Total Certification Meetings The technical coordination committee and policy advisory committee for each MPO and RPO in the MCM study area certified the data sets

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Â

Section D: Metrolina CommunityViz Model, Future Year Allocation Tool

Metrolina CommunityViz Model 16, v. 1.0 Â

The Metrolina CommunityViz Model 16, v. 1.0 includes two major components: a base year data management tool and a future year allocation tool.

The future year allocation tool approximates build out potential, development attractiveness, and future year growth allocation by horizon year (using control total categories from the Metrolina Region Travel Demand Model 17, v. 1.0) for grid cells and traffic analysis zones in the MCM study area. Future year allocation periods in the current CommunityViz model include: 2020, 2025, 2030, 2035, 2040 and 2045.

General topics addressed for the MCM future year allocation tool include: unit of analysis, data needs, model architecture, theory and features behind the tool, data output and calibration activities.

Unit of Analysis: Grid Cell Grid cells are used as a common geography in the Metrolina CommunityViz Model’s future year allocation tool to address size and complexity issues for modeling in a large study area. They are used to aggregate parcel-level data, and support a number of calculations focused on the study-areaas-a-whole.

The size of grid cells used in the MCM varies to reflect different development types, patterns and intensities anticipated for the study area. Smaller size grid cells, generally ten acres each, are used to represent the planning areas for cities and towns throughout the study area (defined by the boundaries used for the Future Land Use Map in locally-adopted comprehensive plans). Larger size grid cells, generally ranging between 40 acres and 2,560 acres, are used for more rural areas (primarily unincorporated areas) and land held in permanent conservation. Increasing the size of grid cells in areas where development types, patterns and intensities are slower to change reduces the total number of features in the data set.

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General rules for assigning grid cell sizes in the region are summarized in Table D1. (Note: a relatively small number of grid cells in the MCM study area do not conform to the simple area rules highlighted in Table D1. These grid cells are located at the boundary of the MCM study area, and are smaller in size because they were clipped to eliminate representation outside the study area.)

The opportunity to use graduated grid cells for the MCM study area improved overall model performance and allowed stakeholders greater flexibility for assigning values and reporting results. Overall, the use of grid cells over parcels in the CommunityViz model reduces the number of records in the database by nearly 88%; converting 914,046 parcels to 113,599 grid cells.

Unit of Analysis: Traffic Analysis Zone The unit of analysis for the future year allocation component of the Metrolina CommunityViz Model 16, v. 1.0 is the grid cell except for two instances: student growth allocation (three categories) and group quarters population allocation (one category). Both of these processes rely on traffic analysis zones to approximate available supply, store land suitability scores (averaged from underlying grid cells), and allocate future year growth.

Traffic analysis zones are distinct geographic subareas used in the Metrolina Region Travel Demand Model 17, v. 1.0 to capture assumed growth and development for base year (2015) and future year conditions (2020 to 2045). They vary in shape and size throughout the MCM study area, but always coincide with census geographies (census tracts, census block groups or census blocks) to improve base year demographic inventory processes.

The Metrolina Region Travel Demand Model 17, v.

1.0 uses 2,955 traffic analysis zones to represent conditions in the MCM study area. Twenty-one additional traffic analysis zones are used to

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Table D1: General Rules for Assigning Grid Cells in CommunitiyViz Grid Cell ⅛-mile

Dimensions 660’ x 660’

Area 10 acres

General Rule Land inside city or town planning boundaries (consistent with the Future Land Use Map boundary presented in locally-adopted comprehensive plans)

¼-mile

1,320’ x 1,320’

40 acres

Land outside city or town planning boundaries but generally within ½-mile of a US Highway or NC/SC Highway

19,573

½-mile

2,640’ x 2,640’

160 acres

7,728

1 mile

5,280’ x 5,280’

640 acres

2 mile

10,560’ x 10,560’

2,560 acres

Land outside city or town planning boundaries and generally greater than ½-mile away from a US Highway or NC/SC Highway Land not likely to develop in the future (e.g., large water bodies, state parks, etc.)

Land not likely to develop in the future (e.g., large water bodies, state parks, etc.)

represent conditions in Anson County (as part of the MCM study area).

Quantity 86,219

74 5

research group or project team working in the MCM study area is allowed access to the data using a log-in and password.

Data Inventory & Analysis Data collection for the future year allocation component of the Metrolina CommunityViz Model 16, v. 1.0 started in 2012 (as part of the CONNECT Our Future scenario planning process) and continued through completion of the model build in 2016. Overall, the quantity and quality of data available in the MCM study area is a major asset for developing the scenario planning model in CommunityViz, and the partnerships formed with the local governments for exchanging data benefitted both the Metrolina CommunityViz Model 16, v. 1.0 and many other plans, studies and initiatives underway (e.g., comprehensive plan updates, a regional freight study, comprehensive transportation plans, development ordinance updates, water and sewer master plans, etc.)

A file transfer protocol (FTP) site was set up for exchanging data in the MCM study area. Data was kept up-to-date by the Centralina Council of Governments and the Catawba Regional Council of Governments. Any government agency,

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Data collected for the Metrolina CommunityViz Model 16, v. 1.0 is described here under three general headings: GIS data, policy and plan documents and resource documents. More detailed information about these topics and the processes used to collect and verify the data is provided in the Metrolina Region CommunityViz Initiative Data Summary Document.

GIS Data Geographic information system (GIS) data was essential to building the Metrolina CommunityViz Model 16, v. 1.0 and evaluating alternative growth scenarios in CommunityViz. The project team worked to create starting data sets during the CONNECT Our Future scenario planning process (2012 to 2014), and partnered with local governments in the MCM study area to update data for the Metrolina CommunityViz Model 16, v.

1.0 (2015 and 2016). Data was collected for three general categories: base map layers, analysis layers

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Metrolina CommunityViz Model 16, v. 1.0

and reference layers. Other data was added to the database as the model build processes evolved.



Metrolina Regional Travel Demand Model 2040 Metropolitan Transportation Plan – MRM14v1.0

More detailed information about GIS data and the rules, processes and calibration activities used to collect and verify it is provided in the Metrolina Region CommunityViz Initiative Data Summary Document. GIS data sets used in the Metrolina CommunityViz Model 16, v. 1.0 are summarized in Table D2 on page D-4.



Metrolina Regional Travel Demand Model Users Guide – MRM14v1.0



CONNECT Our Future Regional Scenario Planning Initiative Summary Document



CONNECT Our Future Place Type & Community Type Summary Document

Policies & Plan Documents Policies and plan documents were collected from local governments in the MCM study area that adopted a new comprehensive plan, small area plan or zoning ordinance since 2012. A list of new policies and documents used to update community type assignments (see page D-7) and confirm development lookup table values (see page D-17) in the MCM study area is provided in the technical appendix.

More detailed information about the rules and processes used to identify policies and documents adopted since 2012, and the methods used to incorporate them into the MCM data update initiative, is provided in the Metrolina Region CommunityViz Initiative Data Summary Document.

Resource Documents Several resource documents were consulted for building the future year allocation component of the Metrolina CommunityViz Model 16, v. 1.0 (MCM). Collectively, they were used to refine the model architecture, validate assumptions, and write equations for CommunityViz. Resource documents consulted for the MCM build include: 

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Metrolina Regional Travel Demand Model Technical Calibration Documentation – MRM14v1.0

Data Manipulation Two new GIS data sets — development status and community types — were created for CONNECT Our Future in 2012 and updated (where appropriate) for the Metrolina CommunityViz Model 16, v. 1.0 in 2016. A description of both data sets and information used for creating the databases is provided on the following pages.

More detailed information about these topics and the processes used to collect and verify the data is provided in the Metrolina Region CommunityViz Initiative Data Summary Document.

Development Status Development status in the MCM study area tells CommunityViz which set of equations to use for estimating the development yield (build-out potential) of a grid cell. And when combined with the land suitability scores and community type assignments, it establishes the order and supply available for a grid cell to receive future growth in the model.

Development Status Assignments Development status was assigned to parcels in the MCM study area using December 2014 aerial photography, property appraiser data, and topicspecific GIS data sets (e.g., existing land use, farmland, or vacant land inventories, etc.).

Emphasis on one or more of the data sets varied

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Table D2: Summary of GIS Data Used in Building the Future Year Allocation Component of the Metrolina CommunityViz Model 16, v. 1.0 File Name Base Map Data City-County Labels Interstate Shields US /NC/SC Highway Shields MCM Study Area Boundary MRM Study Area Boundary Interstates County Boundaries Analysis Data Graduated Grid Cells Permanent Conservation Areas National Wetlands Inventory Stream Buffer Protection Areas Major Water Bodies Existing Rights-of-Way (2015) Composite Development Constraints Layer Interchanges Major Intersections Major Roads Metropolitan Center Town Center / CBD Activity Nodes Major Activity Centers Commuter Rail Station Area of Influence Light Rail/Street Car Station Area of Influence Bus Rapid Transit Station Area of Influence Watershed Protection Areas Flood Hazard Areas Water Service Areas Sewer Service Areas Reference Data Zoning Maps / Future Land Use Maps Points of Interest Parcels Building Footprints Height/Bulk/Density Thresholds by Community Type Aerial Photography Growth Control Totals (2015 – 2045) Traffic Analysis Zones (MRM TAZ 3490) Traffic Analysis Zones (Anson County)

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Shapefile Format

Source

CommunityViz Module

Point Point Point Polygon Polygon Polyline Polygon

COGs COGs COGs CDOT CDOT COGs COGs

Reporting Reporting Reporting Reporting Reporting Reporting Reporting

Polygon Polygon Polygon Polygon Polygon Polygon Polygon Point Point Polyline Polygon Point Point Polygon Polygon Polygon Polygon Polygon Polygon Polygon

Consultant Non-Profits USGS COGs USGS Consultant Consultant MPO/RPO MPO/RPO MPO/RPO COGs COGs COGs MPO/RPO MPO/RPO MPO/RPO NCDEQ NCDEQ COGs COGs

All Modules Carrying Capacity Carrying Capacity Carrying Capacity Carrying Capacity Carrying Capacity Carrying Capacity Land Suitability Land Suitability Land Suitability Land Suitability Land Suitability Land Suitability Land Suitability Land Suitability Land Suitability Land Suitability Land Suitability Land Suitability Land Suitability

Polygon Point Polygon Polygon N/A Raster N/A Polygon Polygon

COGs COGs COGs COGs COGs USDA MPO/RPO CDOT CDOT

Build-Out Potential Build-Out Potential Build-Out Potential Build-Out Potential Build-Out Potential Build-Out Potential Growth Allocation Reporting Reporting

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Metrolina CommunityViz Model 16, v. 1.0

by the development status category being coded, which is highlighted in the category descriptions below. Values for development status are recorded in a new column created for the parcel files named DEV_STAT (short for “development status category”). Internal scripts in the model transfer values from parcels to grid cells using an overlap most function.

Category Descriptions Development status categories used for the MCM study area include: permanent open space, developed, undeveloped, under-developed and water. A brief description of each category follows: Permanent Open Space — Active or passive land dedicated to permanent or semi-permanent open space, including: state parks, conservation areas, parks and recreation fields, and land set aside for open space in residential neighborhoods, commercial centers, business parks, etc. GIS data (conservation easements, points of interest, etc.) and/or land ownership information in a property appraiser database were used to assign permanent open space status.

Future year growth cannot be allocated to grid cells identified as permanent open space in the MCM study area. State parks, recreation areas, etc. expected to see future growth were assigned under-developed status.

Developed — Lots or parcels largely built-out with permanent buildings or structures.

Developed status was also assigned to surface parking lots that serve adjoining buildings, or to sliver lots adjacent to developed parcels (appearing to be part of the same development or home site) where size, shape or access limitations would generally keep them from developing in the future.

December 2014 aerial photography, GIS data (existing land use inventory, building footprints,

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points of interest, etc.) and/or land ownership information in a property appraiser database were used to assign developed status.

Future year growth cannot be allocated to grid cells identified as developed in the MCM study area.

Undeveloped — Lots or parcels without permanent buildings or structures. Undeveloped status was also assigned to more rural parcels with temporary structures (e.g., pole barn, large storage shed, etc.) that could easily be removed to accommodate new development. December 2014 aerial photography, GIS data (vacant lands inventory, building footprints, etc.) and/or land ownership information in a property appraiser database were used to assign undeveloped status.

Future year growth can be allocated to grid cells identified as undeveloped in the MCM study area.

Under-Developed — Lots or parcels with permanent buildings or structures that occupy only a small portion of the property; leaving significant area available for future development.

The initial test was limited to space efficiency, or a mismatch between existing land use and current zoning (e.g., residential home in a commercial district). The condition of buildings or structures on the property was not a consideration for underdeveloped status except for obvious cases of neglect.

The category also includes land presently being used for recreation, agriculture or forestry activities, including: state parks, recreation facilities, cultivated farmland, timber harvest, livestock or woodlands.

December 2014 aerial photography, GIS data (underutilized lands inventory, redevelopment priority areas, etc.) and/or land value and building value information in a property appraiser database were used to assign under-developed status.

Additional parcels were (re)assigned under-

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Â

Photo Examples of Development Status Categories Used for the Metrolina CommunityViz Model 16, v. 1.0

Permanent Open Space

Developed

Undeveloped

Under-Developed

Water

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Metrolina CommunityViz Model 16, v. 1.0

developed status in consultation with local government officials during a series of county-level comment sessions held in the MCM study area.

Future year growth can be allocated to grid cells identified as under-developed in the MCM study area.

Water — Lots or parcels where all, or nearly all, of the land is covered by a water feature. December 2014 aerial photography and/or GIS data (water features, stream corridors, etc.) were used to assign water status.

Future year growth cannot be allocated to grid cells identified as water in the MCM study area.

Development Status Assignment Maps Maps depicting development status assignments for the MCM study area (presented for both the Community Plans Growth Scenario and CONNECT Preferred Growth Concept) are included in the technical appendix. Large-scale, printable versions of the maps are available from the Charlotte Department of Transportation, Regional Modeling Section.

Community types in the MCM study area tell CommunityViz which set of equations to use for estimating the development yield (build-out potential) of a grid cell. And when combined with the land suitability analysis scores and development status assignments, it establishes the order and supply available for a grid cell to receive future growth in the model.

Community Type Assignments Community types were assigned to parcels in the MCM study area using previous work from CONNECT Our Future (referencing the Community Plans Growth Scenario) and/or more current development status and community type data made available during the Metrolina CommunityViz Model 16, v. 1.0 build process.

Values assigned outside areas where a new comprehensive plan, small area plan or zoning ordinance was adopted since 2012 match exactly the information presented for CONNECT Our Future (referencing the Community Plans Growth Scenario) unless updated development status data identified a required change (e.g., parcels reassigned a ‘developed’ status where also reassigned a community type that best matched what was built on the site, is appropriate).

Community Types CONNECT Our Future introduced the concept of community types to the MCM study area, which generalized various development categories used by local governments to describe, measure and evaluate the built environment. Community types for CONNECT Our Future were modified for the Metrolina CommunityViz Model 16, v. 1.0 to complement specific needs in the Metrolina Region Travel Demand Model 17, v. 1.0 (namely expanding the number of employment growth control total categories from four to eight). The concept of community types and a full description of the categories created for the MCM study area are described in the Metrolina Region CommunityViz Initiative Data Summary Document.

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Values assigned to areas where a new comprehensive plan, small area plan or zoning ordinance was adopted since 2012 (see list of communities in the technical appendix) used a four step process for updating community type assignments: 1) parcels identified with a development status of ‘permanent open space’ where assigned a community type of ‘permanent open space’, 2) parcels identified with a development status of ‘developed’ used December 2014 aerial photography or topic-specific GIS data to assign community type, 3) parcels identified with a development status of ‘undeveloped’ or ‘under-developed’ used newly adopted plans and policies to assign community type, and 4) parcels identified with a development status of ‘water’

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Preserved Open Space

were assigned a community type of ‘permanent open space’.

Values for community type are recorded in a new column created for the parcel files named CT_CAT_2015 (short for “community type category in 2015”). Internal scripts in the model transfer values from parcels to grid cells using an overlap most function.

Community Type Category Descriptions Twenty-six community type categories capture different development types, patterns and intensities observed in the MCM study area. A brief summary of each community type category is provided below. See the Metrolina Region CommunityViz Initiative Data Summary Document for more detailed information, including: land use considerations, general development characteristics, and images representing typical development for each community type category.

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Preserved Open Space — land dedicated to permanent conservation by legal means. These areas may be preserved because of their outstanding natural beauty, or because they serve environmental stewardship or wildlife management purposes. The areas are typically undisturbed or undeveloped and have been protected from development by federal, state or local agencies; or by public, private or non-profit organizations. In the MCM study area, these areas include state parks, permanent conservation areas, cemeteries and (at a smaller scale) dedicated open space within residential neighborhoods.

Recreational Open Space — land dedicated for active and passive recreational uses. These areas are intended to be publically-accessible. In the MCM study area, these areas include municipal and community parks, open air sports complexes and athletic fields.

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Metrolina CommunityViz Model 16, v. 1.0

Rural Living — land characterized by large lots, abundant open space and a high degree of separation between buildings. Large acreage, rural family homes and “hobby farms” are scattered throughout the countryside and often integrated into the landscape. The lot size and distance between dwelling units decrease with greater development densities.

Conservation‐based subdivisions in the MCM study area cluster development and leave large areas for permanent open space and uninterrupted views. Small nodes of commercial activity — gas stations, convenience stores or restaurants — are concentrated at rural crossroads, serving some daily needs of the surrounding rural population.

Working Farm — land actively being used for agriculture or forestry activities, including cultivated farmland, timber harvest, livestock and woodlands. These areas may also support the primary residence of the property owner and any out-buildings associated with activities on the working farm.

Large-Lot Residential — land generally formed as subdivisions, which consist almost entirely of single‐family detached homes. Buildings are oriented interior to the site and are typically buffered from surrounding development by transitional uses, topography or vegetative areas.

Many neighborhoods ‘borrow’ open space from adjacent rural or natural settings. Blocks are typically large, and streets rural or suburban in character. In some cases, the neighborhood is served by only one long cul‐de‐sac.

Single-Family Neighborhood — land generally formed as subdivisions or communities, with a relatively uniform housing type and density throughout. They may support a variety of single‐ family detached residential types, from mobile homes to large‐lot, low‐density single‐family homes to denser formats of smaller single‐family detached homes. Homes are oriented interior to the neighborhood and typically buffered from

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Rural Living

Working Farm

Large-Lot Residential

Single-Family Neighborhood

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surrounding development by transitional uses or landscaped areas. Single‐family neighborhoods are often found in close proximity to suburban commercial and suburban office centers, which help provide the consumers or employees needed to support these businesses.

Town Home Community — land generally developed to provide pockets of greater residential density, often in locations that create a transition between commercial or mixed‐use areas and smalllot or large‐lot single family neighborhoods. The more dense development intensities help provide “rooftops” to support nearby suburban commercial, suburban office or suburban mixeduse centers.

Multifamily Neighborhood — land generally formed as complexes or communities, with a relatively uniform housing type and density throughout. They support the highest residential density in the suburban landscape, and may support condominiums or apartments.

Multifamily neighborhoods are found in close proximity to suburban commercial, suburban office and suburban mixed-use centers, which helps provide the consumers and employees needed to support these centers. Buildings are oriented interior to the site and typically buffered from surrounding development by transitional uses or landscaped areas. Large parking lots and low street connectivity are common in suburban multifamily neighborhoods.

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streets. Cul‐de‐sacs are restricted to areas where topography, environmental constraints or existing development makes other street connections prohibitive.

Light Industrial Center — land supporting opportunities to concentrate employment in the MCM study area on normal workdays. Each center generally supports manufacturing and production uses; including warehousing, light manufacturing, medical research and assembly operations. These areas are found in close proximity to major transportation corridors (i.e., highway or rail) and are generally buffered from surrounding development by transitional uses or landscaped areas that shield the view of structures, loading docks or outdoor storage from adjacent properties.

Clusters of uses that support or serve one another are often encouraged to locate in the same light industrial center.

Heavy Industrial Center — land supporting large‐ scale manufacturing and production uses; including assembly and processing, regional warehousing and distribution, bulk storage and utilities. These areas are found in close proximity to major transportation corridors (i.e., highway or rail) and are generally buffered from surrounding development by transitional uses or landscape areas that increase in size as development intensity increases.

Urban Neighborhood — land supporting a mix of moderate‐ to high-density housing options. These neighborhoods are relatively compact, and may contain one or more of the following housing types: single family detached (small lots), townhomes, condominiums or apartments.

Heavy industrial centers may require larger sites because activities are not confined entirely to buildings. Conveyer belts, holding tanks, smoke stacks or outdoor storage all may be present.

Clusters of uses that support or serve heavy industrial centers generally locate in close proximity.

Buildings are generally oriented toward the street.

The design and scale of development in an urban neighborhood encourages active living with a complete and comprehensive network of walkable

Suburban Commercial Center — land supporting the daily needs of surrounding suburban residential neighborhoods. They typically locate near high‐volume roads and key intersections, and

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Metrolina CommunityViz Model 16, v. 1.0

Regional Employment Center

are designed to be accessible primarily by automobile. Buildings are set back from the road behind large surface parking lots with little connectivity between adjacent businesses.

Common types of suburban centers in the MCM study area include: multi‐tenant strip centers, big box stores, small outparcels with a drive‐through and large shopping malls.

Suburban Office Center — land supporting opportunities to concentrate employment in the MCM study area. They include both large‐scale isolated buildings with numerous employees as well as areas containing multiple office uses that support and serve one another. They are typically buffered from surrounding development by transitional uses or landscaped areas and are often located in close proximity to major highways or thoroughfares.

Regional Employment Center — places that draw people from throughout the MCM study area (and beyond) for employment activities.

Development is typically large-scale, including a hierarchy of streets, large sites for a building or group of buildings, supporting amenities and dedicated open space. Centers tend to locate near major transportation corridors and often at the intersection of two major highways or an interstate exit. Uses in a regional employment center vary greatly; however, most complement each other in some manner for increased learning, production or other economies of scale.

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Walkable Activity Center

Walkable Neighborhood — land developed to offer residents the opportunity to live, shop, work and play in one community. These neighborhoods include a mixture of housing types and residential densities, integrated with goods and services in a walkable community that residents visit on a daily basis. The design and scale of the development encourages active living through a comprehensive and interconnected network of walkable streets.

Walkable neighborhoods support multiple modes of transportation.

Walkable Activity Center — land developed to serve broader economic, entertainment and community activities (compared to walkable neighborhoods). Uses and buildings are located on small blocks with streets designed to encourage pedestrian activities. Buildings in the core of a walkable activity center may stand three or more stories. Residential units or office space may be found above storefronts.

Parking is satisfied by using on‐street parking, structured parking and shared rear‐lot parking strategies. A large‐scale walkable activity center may be surrounded by one or more walkable neighborhoods that encourage active living, with a comprehensive and interconnected network of walkable streets.

Town Center — land that satisfies daily economic, entertainment and community needs

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Metropolitan Center

Health Care Campus

for surrounding neighborhoods. Uses and buildings are located on small blocks with streets designed to encourage pedestrian activity.

Buildings in a town center typically stand two or more stories in height with non-residential uses on the ground floor and residential units above storefronts.

entertainment, civic and cultural activities, with a mix of housing types and common open space for active living. As a magnet to surrounding towns and neighborhoods, the metropolitan center becomes an iconic symbol in the region, starting with very tall buildings and a compact street network.

Neighborhoods surrounding the commercial core are relatively compact and support moderate‐ to high‐density housing options, including: single‐ family homes (small lots), townhomes, condominiums and apartments.

The walkable environment and mix of residential and non-residential uses in a metropolitan center support multiple modes of transportation. The only metropolitan center in the MCM study area is Uptown Charlotte.

Transit Activity Center — land representing the concentration of mixed-use, dense development around a transit center, whether serving bus rapid transit, light rail, street car or commuter rail. Uses and buildings are located on small blocks with streets designed to encourage bicycle and pedestrian activity. High-density development is located primarily within ¼‐mile of the transit station, with progressively lower densities spreading out into neighborhoods surrounding the center.

Health Care Campus — a concentration of various medical and medical-related uses, such as primary care, outpatient surgery, birthing centers and other specialty services. They are relatively large in scale, and may include a hospital, teaching facilities, research and rehabilitation centers and private medical office buildings.

Different transit technologies will spur slightly different development patterns and intensities around transit centers, but their similarities are more important than their differences for the community type.

Metropolitan Center — a major focal point in the MCM study area. It is a hub of employment,

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Buildings are typically oriented in a campus setting, with large buildings connected via walkways, structured parking or internal network of streets for circulation.

Educational Campus, K-12 — a public, private or charter school that serves students in kindergarten through twelfth grade (including elementary, middle and high schools). Day care centers and nurseries are not considered part of an educational campus for the Metrolina CommunityViz Model 16, v. 1.0.

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Metrolina CommunityViz Model 16, v. 1.0

University/College Campus, Dormitories — the area of a university or college campus that includes residence halls (group quarters) occupied by students of the institution. Buildings are often oriented around a highly‐walkable network of internal streets and pedestrian pathways, which support several modes of transportation.

University/College Campus, Academic Buildings — the area of a university or college campus that includes all of the academic buildings and other ancillary employment uses needed to support an institution for higher education. Buildings are often oriented around a highly-walkable network of internal streets and pedestrian pathways, which support several modes of transportation.

Structured parking or large surface lots, dedicated areas for public gathering and distinctive architecture also represent a typical university campus.

Building uses and intensities on campus vary widely based on the school’s mission and available space, topography, etc.

Airport, Charlotte Douglas International — land that supports commercial and general aviation air traffic into and out of Charlotte Douglas International Airport; including multiple runways, terminals, taxiways, jet fuel and storage facilities, and paved aircraft parking areas. Complimentary uses (e.g., rental car facilities, hotels, restaurants, long‐term parking lots, etc.) also surround the airport. Restrictions on use, building or structure placement, and maximum height are enforced in designated runway airspace protection areas.

Airport, All Others in MCM Study Area — land that supports commercial or general aviation air traffic into and out of the MCM study area. Each airport may include one or more runways, terminals, taxiways, jet fuel and storage facilities, or paved aircraft parking areas. Complimentary uses (e.g., rental car facilities, hotels, restaurants, long‐term parking lots) may surround an airport.

Restrictions on use, building or structure

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placement, and maximum height are enforced in designated runway airspace protection areas.

Special District — uses that do not meet general definitions or intent of other community type categories used for the MCM study area.

Examples include a regional race track, amusement park, etc. that are unique in the region and often defined by their own planning and design standards.

Community Type Assignment Maps Maps depicting community type assignments for the MCM study area (presented for both the Community Plans Growth Scenario and CONNECT Preferred Growth Concept) are included in the technical appendix. Large-scale, printable versions of the maps are available from the Charlotte Department of Transportation, Regional Modeling Section.

Growth Control Totals County-level control totals for the thirty-year planning horizon (2015 to 2045) were provided by metropolitan planning organizations and rural planning organizations participating as members of the Metrolina Regional and County Control Totals Working Committee. The technical coordination committee and policy advisory committee for each MPO and RPO certified the data sets generated by the Working Committee in July and August 2016 for updating their independent metropolitan transportation plans and comprehensive transportation plans.

Data was summarized for fourteen growth control categories consistent with the needs of the Metrolina CommunityViz Model 16, v. 1.0 (future allocation tool component) and the Metrolina Region Travel Demand Model 17, v. 1.0:   

single-family residential dwelling units multifamily residential dwelling units low-traffic industrial employees Draft Document

Technical Document

Airport, Charlotte Douglas International

          

high-traffic industrial employees low-traffic retail employees high-traffic retail employees low-traffic service employees high-traffic service employees education employees office employees grade K-8 students grade 9-12 students college/university students group quarters population

A table summarizing control totals used for the CommunityViz model (reported in five year increments) is provided in the technical appendix.

More information on the growth control totals created for the Metrolina CommunityViz Model 16, v. 1.0 is available in the various metropolitan transportation plans and comprehensive transportation plans prepared for the MCM study area; including starting data sets, key assumptions,

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background calculations, and a summary of the review process.

Household Category Ratios The Metrolina CommunityViz Model 16, v. 1.0 calculates residential build out potential (supply) for single family and multifamily dwelling unit categories. Future year growth forecasts from the metropolitan planning organizations and rural planning organizations in the MCM study area provide only total households for the thirty-year planning horizon (reported in five year increments).

Household category assumptions used in CommunityViz approximate the ratio of singlefamily dwelling units (single family detached or town home) to multifamily dwelling units (condominium or apartment) to assume for the growth allocation process. Ratios developed for the conversion use county-level data published in the US Census Bureau, 2010-2014 American

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Metrolina CommunityViz Model 16, v. 1.0

Community Survey, Five Year Estimates (Table B25024).

Household category ratios (county-level assumptions) for the Metrolina CommunityViz Model 16, v. 1.0 are summarized in the technical appendix.

Household Size Assumptions The Metrolina CommunityViz Model 16, v. 1.0 calculates residential build out potential (supply) and residential growth allocation (demand) for single family and multifamily dwelling unit categories. The Metrolina Region Travel Demand Model 17, v. 1.0 also needs population for developing a complete socioeconomic data set.

Household size assumptions are used in CommunityViz to convert dwelling units to population during the data output reporting process. Ratios developed for the conversion use county-level data published in the US Census Bureau, 2010-2014 American Community Survey, Five Year Estimates (Tables B25033 and S2504).

Household size assumptions (county-level assumptions) for the Metrolina CommunityViz Model 16, v. 1.0 are summarized in the technical appendix.

Employee Space Ratios Employee space ratios are used in CommunityViz to convert build out potential for non-residential development (square feet) to available supply (employees) for the growth allocation process.

Ratios used for the conversion followed information published in the Institute of Transportation Engineers Trip Generation Manual, Ninth Edition.

Employee space ratios assumed for the Metrolina CommunityViz Model 16, v. 1.0 are summarized in the technical appendix.

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Model Architecture The future year allocation component of the Metrolina CommunityViz Model 16, v. 1.0 uses a region-wide modeling platform to run and evaluate competing growth scenarios. Certain variables and values used in the calculations were linked to CommunityViz via lookup tables, which accounted for the different rules or policies local governments use to regulate development potential.

Growth by control total category was allocated to grid cells (for dwelling units and employees) and traffic analysis zones (for students and group quarters population) in the model for each of the alternative growth scenarios. Grid level data was summarized in CommunityViz by traffic analysis zone and exported to a database format (*.dbf) for creating socioeconomic data in the Metrolina Region Travel Demand Model 17, v. 1.0.

A map of the model architecture for the future year allocation tool is provided in the technical appendix. More information for specific components of the model architecture is provided on the following pages.

Model Components The future year allocation component of the Metrolina Community Model 16, v. 1.0 includes six major components: carrying capacity analysis, external lookup tables, build-out potential analysis, land suitability analysis, growth allocation and TAZ-level reporting.

Carrying Capacity Analysis Some land in the MCM study area will never develop because of physical conditions on the site, land ownership, or the existence of state and local policies that prohibit development. These areas ― referred to as “highly-constrained for development” in the Metrolina CommunityViz Model 16, v. 1.0 ― are removed from the model

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Model-at-a-Glance: Study Area (sq. mi.)

5,026

Model Components

2

Parcels

914,046

Grid Cells

113,599

Assumptions

grid cells in the MCM study area to account for land typically set aside for on-site improvements (e.g., internal streets, utility easements, storm water management, open space, etc.) to support new development. Site efficiency factors are lowered for grid cells located in critical or protected watersheds to limit the maximum buildable area (or maximum lot coverage) consistent with state and local rules or policies.

The portion(s) of a grid cell remaining after the removal of “highly-constrained areas for development” and the application of factors for on-site infrastructure (if vacant) and watershed protection areas (if applicable) are used to approximate buildable area for the region (BUILD_AREA).

XX Features in the MCM study area used to represent highly-constrained areas for development include:

Dynamic Attributes

XX

Indicators

XX

Lookup Tables

4

    

Existing Rights-of-Way Water Bodies Stream Protection Buffers Wetlands Permanent Conservation Areas

A composite map and contributing factors map for the carrying capacity analysis is included in the technical appendix.

area to more accurately approximate buildable area in the MCM study area.

External Lookup Tables

Internal scripts in the model remove “highlyconstrained areas for development” from the build-out calculations using an overlap function.

The presence of development constraints on a grid cell is reported as an area statistic (DEV_CON).

The area(s) of a grid cell remaining for development (DEV_AREA) is calculated as the difference between total land area (SHAPE_AREA) and DEV_CON statistics.

Some variables and values used in the calculations for CommunityViz are linked to the analysis via external lookup tables, which update automatically every time a change is made outside the software.

The tables are used to capture general development characteristics associated with the different community types, and enumerate household, employment, student and group quarters population control totals for the growth allocation process.

A site efficiency factor (specific to each community type category) is applied to vacant

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Metrolina CommunityViz Model 16, v. 1.0

Site Efficiency & Watershed Protection Maximum Lot Coverage Factors Lookup Table Site efficiency factors in the lookup table (SITE_EFF_TABLE.xls) are used to account for the amount of land typically set aside for on-site improvements (e.g., internal streets, utility easements, storm water management, open space, etc.) to support new development. They are reported in the lookup table as the percentage of land remaining for development after deducting for on-site infrastructure (e.g., a site efficiency factor of 80% means 20% of the land is assumed for on-site infrastructure). Site efficiency factors vary by community type category. They are constant for all jurisdictions in the MCM study area.

Maximum lot coverage factors for critical and protected watershed categories in the lookup table (SITE_EFF_TABLE.xls) are used to store maximum lot coverage requirements (representing maximum impervious surface) by community type category. They are constant for all jurisdictions in the MCM study area. Statistics assumed in the lookup table are consistent with rules and ordinances enforced by state agencies or local governments in North Carolina and South Carolina.

Site efficiency factors and maximum lot coverage factors for watershed protection areas are both used in the buildable area calculation (BUILD_AREA), which is part of the carrying capacity module in CommunityViz (see page D15).

The Site Efficiency & Watershed Protection Maximum Lot Coverage Factors Lookup Table is included in the technical appendix.

General Development Lookup Table The general development lookup table (DEV_LOOKUP_TABLE.xls) is linked to the Metrolina CommunityViz Model 16, v. 1.0 using

Pg. D-17

community type categories and jurisdiction code values. Statistics in the table vary by local government represented in the MCM study area; reflecting small differences in characteristics or expectations for each community type category specific to the jurisdiction’s local comprehensive plan and/or land development controls.

All 91 communities in the MCM study area are represented in the lookup table organized by county. Each jurisdiction uses the same data columns, naming convention and formatting features to streamline the modeling process. The only variations in the table are associated with the density and floor area ratio (FAR) values assumed for the variables. Build-out potential factors calculated in the lookup table streamline calculations inside CommunityViz by multiplying factors outside the model environment.

Information in the lookup table is summarized under 30 column headings, including: General Characteristics       

County Name Growth Tier Community Type Category Jurisdiction Code Jurisdiction Name % Residential Development % Non-Residential Development

Residential Development Characteristics    

Average Density Outside Watershed Areas Average Density Inside Watershed Areas (six categorical conditions) % Single Family Development % Multifamily Development

Non-Residential Development Characteristics   

Average Floor Area Ratio % Low-Traffic Industrial Development % High-Traffic Industrial Development

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     

% Low-Traffic Retail Development % High-Traffic Retail Development % Low-Traffic Service Development % High-Traffic Service Development % Education Development % Office Development

Build-Out Potential Factors          

Single Family Development Multifamily Development Low-Traffic Industrial Development High-Traffic Industrial Development Low-Traffic Retail Development High-Traffic Retail Development Low-Traffic Service Development High-Traffic Service Development Education Development Office Development

The General Development Lookup Table (representing all 91 communities in the MCM study area) is included in the technical appendix.

Growth Control Totals Lookup Table: Dwelling Units & Employees The growth control totals lookup table (CONTROL_TOTALS.xls) for dwelling units and employees is used to store county-level control totals for six interim horizon periods between 2015 and 2045. Dwelling unit data is reported for single family and multifamily residential categories. Data for employees is reported for low-traffic industrial, high-traffic industrial, lowtraffic retail, high-traffic retail, low-traffic service, high-traffic service, education and office categories.

The Growth Control Totals Lookup Table: Dwelling Units & Employees is included in the technical appendix.

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Growth Control Totals Lookup Table: Students & Group Quarters Population The growth control totals lookup table (CONTROL_TOTALS_2.xls) for students and group quarters population is used to store countylevel control totals for six interim horizon periods between 2020 and 2045. Student data is reported for kindergarten through eighth grade, nine grade through twelfth grade, and college/university.

Group quarters population data is kept in a single category.

The Growth Control Totals Lookup Table: Students & Group Quarters Population is included in the technical appendix.

Allocation Categories Lookup Table The allocation categories lookup table (ALLO_CATEGORIES.xls) is a data set referenced in the “land uses” window of the Allocator 5 Wizard in CommunityViz. It assigns a numerical identifier to each growth allocation category (residential, employee, student and group quarters) that streamlines internal scripts and calculations in the software.

The Allocation Categories Lookup Table is included in the technical appendix.

Build-Out Potential Analysis Build-out potential in CommunityViz quantifies the type, location and intensity of development for a theoretical condition where all land available in the MCM study area is developed. Specific information for calculating build-out potential for grid cells (used for dwelling unit and employee allocation categories) or traffic analysis zones (used for student or group quarters population allocation categories) is summarized below.

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Metrolina CommunityViz Model 16, v. 1.0

Dwelling Units & Employees

Student Categories

Build-out potential calculations for dwelling units and employees simulate a theoretical condition where all grid cells in the MCM study area assigned ‘undeveloped’ or ‘under-developed’ status are (re)developed consistent with assigned community types and development lookup table values. Internal scripts in the software start with buildable area (BUILD_AREA) and apply rules for land use mix, density or intensity from the General Development Lookup Table to approximate a maximum number of new dwelling units or maximum number of new employees for the grid cells. A factor is applied in the employee calculations to convert maximum allowable nonresidential square feet to total employees for the growth allocation process (see employee space ratio discussion on pg. D-15).

New school locations in the MCM study area are limited to those identified by public school districts or private education providers, which represent very limited data for a thirty-year planning horizon. Capacity assumptions for existing school facilities in future years are also limited because conditions are extremely variable for a thirty-year planning horizon: changing school attendance boundaries, changing federal or state minimum classroom size requirements, school board funding decisions, etc.

Build-out potential statistics are summarized using ten development categories (single-family residential, multifamily residential, low-traffic industrial, high-traffic industrial, low-traffic retail, high-traffic retail, low-traffic service, high-traffic service, education and office) and sis horizon periods: 2016 to 2020, 2021 to 2025, 2026 to 2030, 2031 to 2035, 2036 to 2040 and 2041 to 2045. Available supply for successive horizon periods is calculated by subtracting current period allocation statistics from the same horizon period supply statistics (e.g., 2025 available supply – 2025 allocation = 2030 available supply).

Build-out statistics are summarized by control total category, county location and horizon period for the growth allocation process consistent with control total categories and periods in the Growth Control Totals Lookup Table for Dwelling Units & Employees. Results are saved in a file named “MRCVM_GRID_FILE”. This information is used to represent ‘available supply’ for the growth allocation scripts in CommunityViz.

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The Metrolina CommunityViz Model 16, v. 1.0 uses simple rules for simulating theoretical build out conditions for schools in the study area. All traffic analysis zones in the MCM study area with students identified for the base year condition (2015) are assumed to grow in the future to meet new demand either through school classroom expansion (portable classrooms or building additions) or new school construction in the same traffic analysis zone. A factor of 30% is applied to base year student data in the TAZs to calculate ‘available supply’ for future year students.

Build-out potential statistics are summarized using three student categories (kindergarten through eighth grade, ninth grade through twelfth grade, and college/university) and six horizon periods: 2016 to 2020, 2021 to 2025, 2026 to 2030, 2031 to 2035, 2036 to 2040 and 2041 to 2045.

Available supply for successive horizon periods is calculated by subtracting current period allocation statistics from the same horizon period supply statistics (e.g., 2025 available supply – 2025 allocation = 2030 available supply).

Build-out statistics are summarized by control total category, county location and horizon period for the growth allocation process consistent with control total categories and periods in the Growth Control Totals Lookup Table for Students & Group Quarters Population. Results are saved in a file named “MRCVM_STU_TAZS”. This

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information is used to represent ‘available supply’ for the growth allocation scripts in CommunityViz. Group Quarters Population Category New group quarters locations in the MCM study area are limited to those identified by service providers, which represent very limited data for a thirty-year planning horizon. Capacity assumptions for existing group quarters facilities in future years are also limited because conditions are extremely variable for a thirty-year planning horizon: market-driven decisions to expand existing facilities, changing federal or state size and space utilization requirements, government budget decision, etc.

The Metrolina CommunityViz Model 16, v. 1.0 uses simple rules for simulating theoretical build out conditions for group quarters in the study area. All traffic analysis zones in the MCM study area with group quarters population identified for the base year condition (2015) are assumed to grow in the future to meet new demand either through facility expansion or new facility construction in the same traffic analysis zone. A factor of 30% is applied to base year group quarters population data in the TAZs to calculate ‘available supply’ for future year group quarters population.

Control Totals Lookup Table for Students & Group Quarters Population. Results are saved in a file named “MRCVM_GQP_TAZS”. This information is used to represent ‘available supply’ for the growth allocation scripts in CommunityViz.

Land Suitability Analysis Land suitability analysis (LSA) in a GIS environment measures the appropriateness of an area for a specific condition or use. For the MCM study area, it is used to identify locations attractive for growth based on known physical features or policies unique to the area. Physical features in and immediately surrounding the MCM study area are layered over grid cells in CommunityViz, and calculations performed to determine either percent overlap or proximity of features to individual grid cells. A normalized scale (between 0 and 100) is used to rank the grid cells from least to most suitable for future development. Factors in the LSA could have a positive or negative correlation to desirability scores.

Build-out potential statistics for group quarters population are summarized for six horizon periods: 2016 to 2020, 2021 to 2025, 2026 to 2030, 2031 to 2035, 2036 to 2040 and 2041 to 2045. Available supply for successive horizon periods is calculated by subtracting current period allocation statistics from the same horizon period supply statistics (e.g., 2025 available supply – 2025 allocation = 2030 available supply).

The land suitability analysis calculations for the Metrolina CommunityViz Model 16, v. 1.0 are repeated four times to anticipate changing conditions during the thirty-year planning horizon. Specifically, the model acknowledges new or emerging growth activity centers will attract future growth over time and/or expanding service areas and infrastructure will increase the desirability to grow in certain patterns and intensities over time. Horizon years assumed for the land suitability analysis include 2015, 2025, 2035 and 2045. Factors considered for running the land suitability analysis (data assumed varies over the four horizon years for similar categories) are summarized in Table D3. Results are saved in a file named “LSA_GRID_CALCS”.

Build-out statistics are summarized by control total category, county location and horizon period for the growth allocation process consistent with control total categories and periods in the Growth

Factors were also weighted (using a scale of 0 – not important to 10 – most important) to put more or less significance on one factor compared to others in the calculations. Focus group

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Metrolina CommunityViz Model 16, v. 1.0

Table D3: Factors Considered for Running Land Suitability Analysis in the Metrolina CommunityViz Model 16, v. 1.0 by Horizon Year LSA Factor

Measurement

Correlation

2015

2025

2035

2045

Interchange Locations

Proximity

Positive

•

•

•

•

Major Intersections

Proximity

Positive

•

•

•

•

Major Roads

Proximity

Positive

•

•

•

•

Overlap

Positive

•

•

•

•

Town Centers

Proximity

Positive

•

•

•

•

Major Activity Centers

Proximity

Positive

•

•

•

•

Bus Rapid Transit Station Area of Influence (½-mile radius)

Overlap

Positive

•

•

•

•

Commuter Rail Station Area of Influence (½-mile radius)

Overlap

Positive

•

•

•

Light Rail or Streetcar Station Area of Influence (½-mile radius)

Overlap

Positive

•

•

•

•

Flood Hazard Area

Overlap

Negative

•

•

•

•

Watershed Protection Area

Overlap

Negative

•

•

•

•

Water Service Area

Overlap

Positive

•

•

•

•

Sewer Service Area

Overlap

Positive

•

•

•

•

Metropolitan Center

meetings with business and development interests for CONNECT Our Future helped set the weighted values (see meetings summary in the technical appendix). A summary table of variables and weights for the four LSA analyses in CommunityViz is included in the technical appendix.

A composite map and contributing factor maps for all four land suitability analyses (reported by horizon year) are also included in the technical appendix. Internal scripts transfer LSA scores from one grid cell file (LSA_GRID_CALCS) to another (MRCVM_GRID_FILE) for the growth allocation process (using an overlap most function).

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Growth Allocation Growth forecasted for the MCM study area is allocated to grid cells (for dwelling unit and employee allocation categories) and traffic analysis zones (for student and group quarters population allocation categories) using the Allocator 5 Wizard in CommunityViz. The tool helps determine where growth would likely occur using a supplyand-demand approach and a series of probabilitybased algorithms internal to the software.

The allocation wizard also uses a “randomness” factor of 1 (available settings range from 0 = strict order, follow LSA scores only to 10 = totally random, ignore LSA scores completely). This setting assumes a conservative amount of growth will locate in the MCM study area irrespective of land suitability analysis scores. Qualitative observations throughout the study area support

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this phenomena, whereby small amounts of growth compared to the region as-a-whole occur in more rural areas that lack many of the variables identified by the local development community as important for supporting high growth areas (see business and developer focus group meeting summary in the technical appendix and list of land suitability analysis factors in Table D3).

Information from previous steps in the modeling process — build-out potential analysis, land suitability analysis for multiple horizon years, and growth control totals — is fed directly into the wizard for completing the allocation processes.

Control totals for the thirty-year planning horizon (reported in five year increments, 2015 to 2045) rely on socioeconomic data prepared by others (see discussion on page D-13). Control totals are constrained by county boundary (growth cannot be assigned to other counties) for the growth allocation processes.

Specific information for assigning future year growth to grid cells and traffic analysis zones in the MCM study area is summarized below.

Dwelling Units & Employees Data is summarized for ten development categories (single-family residential, multifamily residential, low-traffic industrial, high-traffic industrial, low-traffic retail, high-traffic retail, lowtraffic service, high-traffic service, education and office) and six horizon periods: 2016 to 2020, 2021 to 2025, 2026 to 2030, 2031 to 2035, 2036 to 2040 and 2041 to 2045. Results are saved in CommunityViz as individual columns in a file named “MRCVM_GRID_FILE”, using the naming convention GA_[allocation category]_[horizon year]. For example, new lowtraffic industrial employees between 2021 and 2025 would be saved in a column named “GA_LI_25”.

Summary tables and composite maps for the allocation of new dwelling units and new

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employees by grid cell and horizon period (presented for both the Community Plans Growth Scenario and CONNECT Preferred Growth Concept) are included in the technical appendix.

Students Data is summarized for three student categories (kindergarten through eighth grade, ninth grade through twelfth grade, and college/university) and six horizon periods: 2016 to 2020, 2021 to 2025, 2026 to 2030, 2031 to 2035, 2036 to 2040 and 2041 to 2045. Results are saved in CommunityViz as individual columns in a file named “MRCVM_STU_TAZS”, using the naming convention GA_[allocation category]_[horizon year]. For example, new high school students (ninth grade through twelfth grade) between 2021 and 2025 would be saved in a column named “GA_HS_25”.

Summary tables and composite maps for the allocation of new students by traffic analysis zone and horizon period (presented for both the Community Plans Growth Scenario and CONNECT Preferred Growth Concept) are included in the technical appendix.

Group Quarters Population Data for group quarters population are summarized for six horizon periods: 2016 to 2020, 2021 to 2025, 2026 to 2030, 2031 to 2035, 2036 to 2040 and 2041 to 2045. Results are saved in CommunityViz as individual columns in a file named “MRCVM_GQP_TAZS”, using the naming convention GA_[allocation category]_[horizon year]. For example, new group quarters population between 2021 and 2025 would be saved in a column named “GA_GQ_25”.

Summary tables and composite maps for the allocation of new group quarters population by traffic analysis zone and horizon period (presented for both the Community Plans Growth Scenario

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Metrolina CommunityViz Model 16, v. 1.0

and CONNECT Preferred Growth Concept) are included in the technical appendix.

Total number of fields should be 60 (ten control total categories x six horizon periods = 60 columns)

Reporting Geographies

Statistic Type — Summation

Future year growth is allocated to grid cells or traffic analysis zones in the Metrolina CommunityViz Model 16, v. 1.0 using pre-defined control total categories and horizon years. The Metrolina Regional Travel Demand Model 17, v.

1.0 requires all socioeconomic data be organized by traffic analysis zone for its processes.

Therefore, grid cell data in CommunityViz (tagged with overlying traffic analysis zone identification number) is summarized into traffic analysis zones using the “summary statistics” tool in ArcGIS software.

Case Field — TAZ_NO

Specific settings for running the “summary statistics” tool are as follows:

A significant amount of time was reserved in CONNECT Our Future to calibrate the CommunityViz models and validate the data used to create them. These activities were critical to developing the new model architecture, data protocols, and key assumptions for building the Metrolina CommunityViz Model 16, v. 1.0; instilling confidence in the analysis tools and reaching greater consensus among metropolitan planning organizations and rural planning organizations in the MCM study area for the results.

Input Table — MRCVM_GRID_FILE Output Table — TAZ_Summary_[Date].dbf Statistics Fields — Growth Allocation for Single Family Dwelling Units (GA_SF_[HY]), Growth Allocation for Multifamily Dwelling Units (GA_MF_[HY]), Growth Allocation for LowTraffic Industrial (GA_LI_[HY]), Growth Allocation for High-Traffic Industrial (GA_HI_[HY]), Growth Allocation for LowTraffic Retail (GA_RT_[HY]), Growth Allocation for High-Traffic Retail (GA_HY_{HY]), Growth Allocation for Low-Traffic Service (GA_LS_[HY]), Growth Allocation for HighTraffic Service (GA_HS_[HY]), Growth Allocation for Office (GA_OF_[HY]) and Growth Allocation for Education (GA_ED_[HY]) Notes: [HY] = Growth Allocation Horizon Year Data columns should be included for each control total category and each horizon year in the input table (2020, 2025, 2030, 2035, 2040 and 2045).

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Build-out potential and growth allocation output data from the Metrolina CommunityViz Model 16, v. 1.0 is also summarized by jurisdiction and MRM sub-district using the same “summary statistics” tool in ArcGIS software. Summary tables (presented for both the Community Plans Growth Scenario and CONNECT Preferred Growth Concept) are included in the technical appendix.

Model Calibration

A summary of key calibration/validation activities performed for CONNECT Our Future (and carried forward in building the Metrolina CommunityViz Model) is provided below.

Project Steering Committee A project steering committee for the Metrolina Community Model Initiative was formed to provide direct oversight and counsel for building the model and collecting data identified to run it. Those on the steering committee represented a broad base of interests, viewpoints and concerns in the MCM study area. The following groups were represented on the committee:

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Federal Highway Administration North Carolina Department of Transportation Charlotte Regional Transportation Planning Organization Gaston-Cleveland-Lincoln Metropolitan Planning Organization Rock Hill-Fort Mill Area Transportation Study Rocky River Rural Planning Organization Centralina Council of Governments Catawba Regional Council of Governments Charlotte Department of Transportation Charlotte-Mecklenburg Planning Department Iredell County Planning Department Union County Planning Department

Nine meetings with the project steering committee were held between April 2015 and June 2016 to build components of the Metrolina CommunityViz Model 16, v. 1.0. They were generally used to integrate MCM model components with 1) the model architecture and data input needs of the Metrolina Regional Travel Demand Model 17, v. 1.0, 2) base year dwelling unit (household), dwelling unit (household) population, group quarters population, student and employment data management tools, and 3) annual socioeconomic data update processes and data protocols.

Meeting agendas and summary minutes for the nine project steering committee meetings are provided in the Metrolina Region CommunityViz Initiative Data Summary Document.

Technical Advisory Committee A subset of the project steering committee and invited guests made up a technical advisory committee for the Metrolina CommunityViz Model 16, v. 1.0. Their charge was to discuss very specific data needs, key assumptions and model logic important for building parts of the future year allocation tool in CommunitViz. Topics discussed in technical advisory committee meetings include: employee space ratios, regional

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control total categories, land suitability analysis data and horizon periods, a crosswalk (classification matrix) for matching MRM control total categories with MCM community type categories, household size assumptions, and household type percentage split assumptions (single family vs. multifamily by county).

Meeting agendas and summary minutes for four technical advisory committee meetings are provided in the Metrolina Region CommunityViz Initiative Data Summary Document.

County-Level Coordination Meetings County-level coordination meetings were held throughout the MCM study area in January and February 2016 to present initial data and collect comments for moving forward. Events were held in Gastonia, Shelby, Lincolnton, Statesville, Albemarle, Wadesboro, Charlotte and Monroe in North Carolina, and in Rock Hill in South Carolina. Participants included planning directors, other planning staff, MPO and RPO representatives, utility service providers and MPO technical committee members.

Initial data maps were presented at each meeting and comments recorded for revising data sets. A comment period remained open for two weeks following each event. Maps and data were transferred via a file transfer protocol (FTP) site.

Meeting agendas and summary minutes for the county-level coordination meetings are provided in the Metrolina Region CommunityViz Initiative Data Summary Document.

GIS Source Data Geographic information system (GIS) data was essential for completing CONNECT Our Future and building the Metrolina CommunityViz Model 16, v. 1.0. Staff for the Centralina Council of Governments and Catawba Regional Council of Governments worked with local governments to

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Metrolina CommunityViz Model 16, v. 1.0 Â

create starting data sets for CONNECT Our Future in 2012, and partnered with local governments in the region to keep files up-to-date throughout the process to build the Metrolina CommunityViz Model 16, v. 1.0 in 2015 and 2016.

the land suitability analysis, build-out potential and growth allocation processes), beta model results and reporting geographies.

See the Metrolina Region CommunityViz Initiative Data Summary Document for more information about GIS data and the rules, processes and calibration activities used to collect and verify it for the Metrolina CommunityViz Model 16, v. 1.0.

Site Validation Studies Site validation studies were completed for CONNECT Our Future to confirm the values used in the general development lookup table for community types and jurisdictions represented in the MCM study area. Using existing development, the project team completed site analyses for the community type categories (three sample sites each) present in the individual jurisdictions. Data was collected for buildable area, density and floor area ratio.

Information from the validation studies was shared with local governments during county-level coordination meetings for CONNECT Our Future, and used to adjust lookup table values for conditions unique to each community type and jurisdiction. Development lookup table values (site efficiency, density and floor-area-ratio) from CONNECT Our Future remain unchanged for the Metrolina CommunityViz Model 16, v. 1.0.

Internal Quality Control The project team used regular coordination calls, emails, web meetings and on-site coordination meetings to build and calibrate the Metrolina CommunityViz Model 16, v. 1.0 and validate the data used to create it. Key quality control issues addressed by the team included: data quality and availability, model architecture, model input data and values, rates and calculations (especially for

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Section E: Technical Appendix

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Technical Appendix Base Year County-Level Household, Population, Student & Employment Estimates (2015)

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Technical Appendix Future Year County-Level Household, Population, Student & Employment Estimates (2020 - 2045)

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Technical Appendix Summary of the Process Used by MPOs & RPOs in the MCM Study Area to Calculate, Summarize & Report Base Year Data (2015)

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Technical Appendix List of Jurisdictions in the MCM Study Area with New Land Use Plans or Policies Since 2012

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Technical Appendix Development Status Maps: Community Plans Growth Scenario CONNECT Preferred Growth Scenario

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Technical Appendix Community Type Maps: Community Plans Growth Scenario CONNECT Preferred Growth Scenario

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Technical Appendix Household Category Ratios Assumed for the MCM Study Area (single family vs. multifamily)

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Technical Appendix Household Size Assumptions for the MCM Study Area

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Technical Appendix Employee Space Ratios Assumed for the MCM Study Area

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Technical Appendix Metrolina CommunityViz Model Architecture: Future Year Allocation Tool

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Technical Appendix Metrolina CommunityViz Model 16, v 1.0 Equation Dictionary

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Technical Appendix Carrying Capacity Composite Map & Contributing Factors Map

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Technical Appendix Site Efficiency & Watershed Protection Maximum Lot Coverage Factors Lookup Table

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Technical Appendix

General Development Lookup Table: Community Plans Growth Scenario

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Technical Appendix

General Development Lookup Table: CONNECT Preferred Growth Scenario

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Technical Appendix Growth Control Lookup Table: Dwelling Units & Employees

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Technical Appendix Growth Control Lookup Table: Students & Group Quarters Population

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Technical Appendix Allocation Categories Lookup Table

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Technical Appendix Focus Group Meeting Summary: Business & Development Interests

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Technical Appendix Land Suitability Analysis Assumptions Summary Table

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Technical Appendix Land Suitability Analysis Composite Maps & Contributing Factors Maps

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Growth Allocation Maps & Tables: Community Plans Growth Scenario, 2020 – 2045 Horizon Year Reporting Periods

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Growth Allocation Maps & Tables: CONNECT Preferred Growth Scenario, 2020 – 2045 Horizon Year Reporting Periods

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Technical Appendix ArcGIS Summary Statistics Tool Settings

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