As the plan develops, this blog will provide information related to the project.  You can also follow and participate in the planning process by visiting the following sites.

Important Links & Related Sites

www.westfranklinton.com – This site is serving as the primary information collection & dissemination portal for the duration of the project.  The software that is powering the site is provided by MindMixer.  The topics and information that is disseminated through this site, will evolve as the actual planning project evolves.

West Franklinton Facebook Page – West Franklinton has a Facebook page that will also provide a place to keep folks informed on the planning process.  Links to project documents and project photos can be found on this site.

@WFplan (Twitter) - this is the Twitter account for the West Franklinton Plan.  Follow it and you will never be out of the loop!

Project Timeline

October 2013 – The consultant team begins meeting with the Staff Working group (planners from the City of Columbus, recreation & parks, housing, mayor’s office, and others).  Later that month, the team conducts their first meeting with the Community Working Group, a group of leaders from Franklinton comprised of members of the Franklinton Development Association (FDA), Gladden Community House, Mount Carmel, to name a few.

November 2013 – The consultant team begins conducting stakeholder interviews and collecting “existing conditions” data.  Each parcel within the neighborhood is surveyed and vacancies are documented.  The commercial (retail) market analysis begins.

December 2013 – Stakeholder interviews continue as does the data collection and analysis for the existing conditions.  The housing market analysis begins.

January 2014 – The project’s website (www.westfranklinton.com) goes live.  The public information gathering begins in earnest.  Existing conditions data gathering concludes.  The market analyses (housing, commercial, office, and industrial) concludes.  The planning team meets with the Staff Working Group and the Community Working Group.  Both groups are briefed on the results of the existing conditions report and the market analyses.  Later that month, the first public workshop is held.

Public Workshop #1

On January 28, 2014, the first West Franklinton planning Public Workshop was held at the Gladden Community House.  Even though it was the coldest night in decades, almost 100 hearty souls turned out to provide their input and mingle with others that were interested in participating in the planning of Franklinton’s future.  NBC 4 in Columbus even came out to document the event with a nice video piece with an accompanying web article.

One of the exercises that the public was encouraged to partake in was a mapping exercise where four location-specific questions were posed to participants.  The results of that exercise were as follows:

1. Question:  What one place would make the neighborhood better if it was dramatically different from how it is today?  Please indicate on the map.
   Answer:  Click here to see the map
2. Question:  What do you consider to be the “heart” of West Franklinton?  Please indicate on the map.
   Answer:  Click here to see the map
3. Question:  What is the one place that a visitor to Franklinton should see?  Please indicate on the map.
   Answer:  Click here to see the map
4. Question:  If you could create a new neighborhood park in West Franklinton, where would you build it  Please indicate on the map.
   Answer:  Click here to see the map

February 2014 – The “plan development” phase begins.  This is when the rubber meets the road.  New topics are added to the westfranklinton.com site.  The new topics reflect the progression of the planning process.  The team begins working with the City and the Community Working Group to craft a comprehensive vacant housing & housing development strategy.  Late in the month, the team meets with the Community Working Group to initiate the plan development phase.  Discussion topics include improving community outreach for the next public workshop (scheduled for the end of April).

April 2014 – The 2nd community workshop is scheduled for Wednesday, April 30 from 5-7 PM.  The official press release can be found on westfranklinton.com (in the “about” section) OR you can link to it here.

October 2014 – The West Franklinton Plan has been completed.  You can download the plan here.  The plan is very progressive in its approach; emphasizing connectivity and public open space (parks) enhancements as property becomes available.  The flexibility built into the plan allows for the development of these features in a variety of places throughout West Franklinton.

November 2014 – The West Franklinton Plan has been adopted by Columbus City Council.  You can learn more about the Plan by checking out the City of Columbus’ website.

“Creating successful urban retail districts is a goal of planners and community leaders alike. But as Robert J. Gibbs points out in Principles of Urban Retail Planning and Development(2012; Wiley; 272 pp.; $80), planners may be hampered in that task by an overly romantic view of an ideal shopping area. Even in the best planned new urbanist developments, he points out, retail components often fail to live up to expectations.

….(Gibbs) explodes various myths about what makes a successful retail district and lists some of the common mistakes made by planners, business owners, and community leaders — failing to begin a project with a professional market analysis, for instance. He shies away from easy answers. While clearly in favor of the walkable retail districts that planners typically espouse, for instance, he concedes that they don’t always succeed financially.

Gibbs includes plenty of useful information on specifics such as parking. His book will be most useful to private-sector planners and those who work with public-private partnerships. But the material it contains will also be helpful to public planners dealing with zoning issues. — Ryan Smith”

Several of us here at UDG, have at one point in our lives, worked for real estate market analysts (in fact, we have several current clients that are in this line of business).  This is where we learned the value of conducting a market analysis for planning and development purposes.  Our backgrounds in GIS and Urban Planning provide us with a unique perspective on the concept of the market analysis.  We have seen more than our fair share of good and bad examples of market analysis.  If you are a city conducting a land use or comprehensive plan, it is in your best interest to include market analysis as part of the planning process.  In addition, you should thoroughly vet the analyst to make sure they understand what the goals and objectives of the plan are.  Traditional, boilerplate market analysis is not going to suffice.  Cities, and the spaces within a city, are unique.   The market analyst must be willing to approach their task as part of the entire planning team, which means they must be engaged in the process from start to finish.

Traditional market analysis does not address the goals of a land use or comprehensive plan.  There are two basic questions planners need to answer with respect to the market analysis:  1.  Is there a market and 2. how “much” should we plan for? Further, planners (and the public in general) may ask questions regarding “what it takes” to achieve the critical mass required to achieve the desired results.  For example, “how many households do we need to add, at varying income levels, to achieve the critical mass required to support a medium-sized grocery store?”

Geographic Information Systems (GIS) are the perfect tool for conducting this type of analysis and far too few analysts invest the time and money to employ a robust GIS to help them answer these spatial questions.  A GIS makes it much easier to visualize the current conditions as well as visualize future conditions – which is at the heart of the concept of planning.

Urban Decision Group has been fine tuning this very type of analysis into a service we call “Planning Market Analytics“.  Planning Market Analytics is specifically designed for informing  comprehensive or land-use plans.  Like a traditional market analysis, field observations are required but the observations must be targeted and focused on the goals at hand.  Our service focuses on a data-driven GIS model to produce predictive analytics via established methods such as Huff Modeling.

The Planning Market Analytics service is usually expensive because of its intended audience.  The audience for a traditional market analysis generally consists of developers and  financiers.  That group is looking for very specific price points, rents, and lease rates for defined product types like town homes or 2 bedroom apartments.  The planning audience, on the other hand, is focused on the larger picture.  They need to  know if a project has a  chance at being successful (is there a market?), how much space should be allocated, what infrastructure improvements will be necessary, etc.  Two different audiences require two difference approaches.

So if you’re a city, county, region or state that is engaging in city or regional planning, I agree with the letter writer above.  Do you your homework first.  It’s a nominal portion of the project cost that can literally save you millions on the back end.

If you would like more information on Planning Market Analytics and you live in North America, contact Urban Decision Group at 614-383-8447 or email Rick Stein at rstein at urbandecisiongroup.com.

Concentric Circles
DO NOT use simple concentric circles. Concentric circles (sometimes referred to as radials) ignore all the important information about any given area such as physical and psychological barriers, real travel time, and the area’s socioeconomic character. This method may be appropriate as a guide or a starting point, but it should never be used as the final market area for a project.

example of concentric circles

Drive Time Polygons
Drive Times are best expressed as polygons rather than concentric circles because polygons calculate the real travel time required to move from one point to another using actual road infrastructure. Drive Time polygons are a great starting point for a project’s market area delineation. It should be noted, however, that Drive Times ignore walking and users of public transportation, which could be problematic depending on the project. Drive times also do not reflect consumer preferences or psychological barriers.

example of drive time polygons

Census Tracts
Census Tracts, although critical to a proper analysis, are also not the best way to delineate a final market area. Census Tracts are a creation of the U.S. Census Bureau, and their sole purpose of is to make it easy for the U.S. Census Bureau to organize information: Tracts consist of several Census Block Groups which are an aggregation of individual Block Points. Block Points are nothing more than actual city and/or country blocks. Therefore, market areas created by simply aggregating entire Census Tracts are equally likely to include irrelevant areas as well as exclude relevant ones because they do not take any of the factors (barries, population density, etc.) that impact a market area into account. This ultimately results in an inaccurate market area that, much like a simple concentric circle, overstates or understates the true socioeconomic conditions that exist within the actual market area.

example of census tracts

Hand Drawn Market Areas
By far, hand drawn market areas are the best way to delineate a project’s market area. Hand trade areas rely on multiple sources of information to establish boundaries. These might include interviews with local stakeholders, thematic demographic maps that visually display socioeconomic character down to the Block Group level, or oversetting thematic data with drive time polygons. This is important because a useful market area isn’t bound by arbitrary political boundaries; it should be based on all of the information available.

example of a hand drawn market area

Once you’ve delineated the final market area, then you must spatially gather the data associated with the people, housing units and businesses in order to build a profile of exactly “what” the trade area contains. It is during this step that planners, developers and analysts sometimes make the mistake of choosing the wrong tools to do the job. The only proper tool for apportioning data to a market area is a Geographic Information System (GIS). Without a properly outfitted GIS, spatial data is going to be miscounted and miscalculated. Here’s why: This map shows a close-up of a market area boundary (red) and a Census Tract (black) that is bisected by the market area. The area to the right of the red boundary is INSIDE the market area. The area to the left of the red boundary is OUTSIDE of the market area.

Census Tracts bisected by a market area boundary

Let’s assume you have data from the U.S. Census Bureau for this particular Tract. How would you go about the process of determining the number of households within the market area? A lot of guesswork could be involved. For example, visually it seems that 70% of the Tract is within the market area and 30% is outside. It stands to reason, therefore, that 70% of the households must be within the market area and 30% must be outside. It sounds simple, but let’s look at the actual numbers. Using real Census data, we know the total number of households within this Tract is 2,300 Therefore, we are estimating that there are 1,610 (2,300 x 70%) households within this single Tract that reside within the market area. However, if we use a GIS to do this calculation, we find out the actual number of households within the market area is 1,343. That means we over counted this single Tract by 267 households. The typical market area cuts through 20 or more Census Tracts (depending on the type of project and the density of the population). That means there are at least 20 opportunities for estimation and calculation errors from manually assembling this market area data. The difference between the estimation and the actual number has real consequences: at this level, bad information could either potentially provide support for a project that should not be supported OR dissuade a project that is actually viable. In sum, there is a lot of money at stake when apportioning data to a market area. If you don’t use a GIS to apportion the data for you, then miscalculations will assuredly occur, effectively wasting many people’s time and money.

So why does a GIS do a better job of apportioning data to a market area? A GIS is capable of accurately apportioning population, household, housing unit and business data because it uses the location of Census Block Points to determine exactly how many people, households, housing units, or businesses, are within a market area’s boundaries. Let’s look at the zoomed-in map again.

Census Block Points in relation to the market area

The dots you see on the map are proportional symbols that represent the actual physical location of Census Block Points. Block Points contain four types of information for each city/country block that it represents – total population, total households, total housing units, and the total number of businesses. Virtually all Census data (and by extension, third-party demographic data) is associated with one of these “Universes” (that’s U.S. Census lingo). Let’s use the same example market area and Census Tract that we just looked at. A GIS will examine all of the Block Points that reside within the market area and will calculate the actual percent of population, households, housing units and businesses that reside within the market area. Those percentages can then be used to apportion all the data associated with that tract. In other words, we can now accurately determine the precise levels of all data elements within the market area. A GIS can also calculate things like median income for an entire trade area without you ever having to type in a bunch of numbers into a spreadsheet and apply a bunch of assumptions.

A properly outfitted GIS is without a doubt, the most effective tool available for market area delineation and more importantly, for data apportionment to the market area. There is a lot riding on your project(s). Shouldn’t you be using the right tools for the job?

Rick Stein is Principal & Owner of Urban Decision Group (UDG).  He is a trained urban planner, GIS expert, and software developer.

So Franklin and Delaware Counties are bright spots in a state where most counties lose population overall, but what other information can we infer from these growth rates? A friend asked if these growth trends might indicate that individuals in Central Ohio are starting to prefer urban environments over the suburban, with Franklin County representing urbanity and Delaware County the suburbs. It’s a good question, but the short answer is… not really.

Beyond the fact that one year is not enough information to establish any sort of statistically relevant trend, that more people are moving into Franklin County matters a little less than where in Franklin County they are moving (as some have already discussed). After all, there’s a big difference between greenfield development outside of Columbus City limits and moving into the city center. It’s also important to separate natural population changes from migration. Natural population growth includes births and deaths, and the remainder are individuals moving in and out of an area.  This type of voluntary population change would obviously be the more interesting demographic for exploring a preference for urban or suburban environments.

But getting back to my friend’s question, there are some basic ways we can look at this data to get a rough idea of where things stand. Again the really interesting question isn’t whether people are moving into Franklin County, it’s where they’re going. We can get an idea of exactly where people are going in the county by disaggregating the Census data from the entire county to census block groups. Since there’s no question on the US Census about a preference for urban or suburban communities, the next step is picking some kind of proxy. I decided to use population density. Population density is usually expressed by the number of people per square mile or square kilometer. Basically, it is the ratio of people to space: a small area with a large number of individuals has a higher population density than a large area with few individuals. Higher population densities, therefore, correlate with more urban environments and lower population densities with suburban or rural areas. My thought was that if people in central Ohio were starting to prefer urban communities, then the population density of Columbus proper should increase over time. Sounds like a perfect excuse to make a few maps.

Before I get to the maps, I have to emphasize that this is a quick survey exercise. I’m an academic at heart and I’d feel horrible if I didn’t point out that I didn’t triple check my numbers, I didn’t account for natural vs. migratory population changes, and I didn’t account for the growth rate (percentage increase) of each census block, or any number or time consuming things that would better validate these results. This is a sketch of population patterns in Franklin County, Ohio, and it’s a game anyone can play. If you have some kind of access to a mapping program, I encourage you to download this free data from American FactFinder and explore on your own. It’s a fun nerdy time.

First we have Franklin County’s population density in the year 2000.  I calculated population density by dividing the population of each census block group by its area.  If I were making this map again I would probably leave the numbers in the population density scale, but at the time I thought the numbers were too confusing because the census block groups can be such small areas.  I’d also retain labels for the highways and major roads to make the map easier to understand.  Regardless, I think this map largely reflects what you’d expect if you’re familiar with Columbus or Franklin County.  The areas with the highest population density are generally within I-270 (the circular outerbelt highway) and are further concentrated immediately south and north of downtown (downtown is smack in the middle of the map within the rectangle of highways).

Next is Franklin County’s population density in 2012 using the census estimates.  You can’t see it on the map, but I decided to keep the numeric range behind the density scale (lowest, low, middle, high, highest) the exact same as in the 2000 map because I wanted to see exactly how the population densities did or did not change.  My theory was that, given the same scale, an influx of people into the city (a preference for urban living) would result in more dark blue areas around the core.

It might be a bit difficult to see at first, but instead of a steady gain in population density in the heart of the city, it seems that the population densities spread out a bit throughout the county, meaning there was actually some density loss in Columbus, particularly in the German Village/South Side area.  (It would be interesting to go through foreclosure data to see if this area was particularly affected by the housing crash – perhaps that can be a future map series.)  North of downtown in the Short North/University area held pretty steady and density gains are apparent in the communities that surround Columbus proper.

After making these maps to demonstrate why an increase in Franklin County’s population doesn’t necessarily mean an increased desire for urban living, I started to wonder if I was over complicating the issue.  Maybe it would be better to simply see how areas lost or gained population over the twelve years.  I decided to make another map that just looked at whether each census block group lost population, gained population, or held steady from 2000 – 2012.  Again, I did not differentiate between natural and migratory population change.

The green areas in this map represent a net population gain since the year 2000 while the grey displays a net population loss. This map largely confirms the 2012 population density map in that the areas that lost density experienced a net loss of population over the same time period.  It also suggests in simple binary terms that areas outside of Columbus seem to have experienced population growth in equal or greater terms as the city proper.  To double check I made one more map highlighting Columbus’s city limits.

The opaque areas of the map are Columbus proper.  This makes it a bit easier to see that although the city itself has experienced a healthy amount of growth over its entire geographic area, there were losses in eastern portion of the city and much of the growth is in the periphery.

At the end of the day, these maps confirmed my suspicions: Sorry, friend.  Franklin County’s growth rate doesn’t really mean that more people are choosing an urban life style.  However, the last map brought a bit of unexpected optimism.  Columbus may not be the densest urban environment, it may have even lost some population density since 2000, but it has experienced positive growth downtown and downtown’s surrounding neighborhoods.  I can’t help but feel that this is a good sign; if you’ve seen the development boom in central Columbus lately, you might agree.  From the mixed-use development underway at High and Hubbard in the Short North, to the construction of apartments around Columbus Commons, to the the grand opening of the downtown Hills Market, it certainly feels like there’s a renewed momentum for the central area of the city.    Perhaps in another ten or so years we’ll look at the census data and see, thanks to present day efforts, that individuals are in fact expressing a preference for urban living in Central Ohio.