Tag Archives: Dallas

A Study on Regional Governments


I’m finally finished with the regional governments project that I’ve been working on for something like six weeks and that has kept me from writing in that time.  In the future I may want to use more accurate measures and publish this, so I’m going to practice by presenting this as scientific research.  So here goes.

Introduction

I wanted to study the possibility of creating regional governments in the United States for three reasons.  First, because I agree with The Charter of the New Urbanism when it states that “The metropolitan region is a fundamental economic unit of the contemporary world. Governmental cooperation, public policy, physical planning, and economic strategies must reflect this new reality.” Also, I feel that the lines that divide government designations in America are arbitrary at best and, in many cases, don’t reflect reality on the ground.

It is interesting to compare government designations in Europe and America.  If you look at a map of Europe, you will notice that none of the boundaries are straight lines.  This is because the boundaries do a much better job of reflecting things like topography and real cultural divides.

The US, on the other hand, was drawn up for ease of division by immigrants who considered it to be essentially uninhabited.  Many counties, particularly in the Midwest, are just boxes laid out along the survey lines created by Jefferson, regardless of the topography on the ground.  There is only one state in the US that doesn’t have a straight line for a boundary, and that is Hawaii.  I don’t believe that this is advantageous.  Take my hometown of Pittsburgh, for example.  Pittsburgh is within the state of Pennsylvania, which it shares with Philadelphia.  This is about all the two cities share.  Their economies, populations, ethnic groups, and cultures are very divergent.  When the two cities are thrown into competition, often for State funds, Pittsburgh, with its lower population and generally higher standard of living, often does not get as much as Philadelphia.  According to Pittsburgh Quarterly, “It is often lamented that the Pennsylvania legislature tilts to the east, favoring Philadelphia over Pittsburgh.”  It would be advantageous to Pittsburgh to not be as closely linked to Philadelphia, which it in reality has little relation to.  At the same time, there are areas in Ohio, West Virginia and Maryland that are closer to Pittsburgh than to any major city in their respective states, and would do well to be involved with the politics of that city.  At a lower level, there are people who live just outside of Alleghany County, where Pittsburgh is, so that they don’t have to pay the higher taxes in that county, yet they still use Alleghany County roads and services without paying their fair share.  I believe that, along with state borders, county borders should be amended to reflect the reality on the ground of how central city services are used.

This brings me to my third point: I don’t think, in many parts of the country, that county governments serve a needful purpose in the way that they did in the past.  When the country was made up of many small, independent towns, counties worked to unite them in common purpose.  Now, in our metropolitan world, counties are often used as tax havens or otherwise don’t serve their original purpose.  Rhode Island, Connecticut and Massachusetts have done away with their county governments, streamlining political processes and ironically creating “small government” in some of the most liberal states in the Union.

But how does one define a region?  For an answer, I turned to Christopher Alexander, as I often do, who, in A Pattern Language, encourages us to, “Wherever possible, work toward the evolution of independent regions in the world; each with a population between 2 and 10 million; each with its own natural and geographic boundaries; each with its own economy; each one autonomous and self-governing; each with a seat in a world government, without the intervening power of larger states or countries.”  With that in mind, I began my research.

Methods

I relied heavily on Wikipedia and Google for this research, which is why it isn’t publishable in its current state.  To begin, I set benchmarks for regions.  I wanted to make three maps to visualize regions of different sizes, so I decided that, so as to be in line with Alexander’s requirements, I would have one map with a minimum population of 2 million per region, another map with a minimum of 5 million per region, and a third with a minimum of 8 million.  Then I got a list of cities in the US with a population of over 100,000.

I went through every county in the country and measured the distance from the county seat to the nearest city of over 100,000, marking them on a map with a different color to designate different cities.  I used Google Maps’ walking distance feature because I felt that it would do a better job of reflecting topography than simple as-the-crow-flies measurement, while at the same time being more accurate than the car distances since cars are expected to travel on highways over large distances, which may be faster but not as direct.  Also, I wanted to measure it as if some sort of catastrophe happened and people were unable to use cars, thus being forced to walk.

After finding out which counties were closest to what cities, I counted up the population of the counties that were marked for a given city based on the most recent data on Wikipedia.  Some of this information was as recent as 2009 estimates, while some was as old as the 2000 census.  Hopefully when the new census comes out I can redo this project with better results.  If the population of the area was below the population benchmark that I had set, then the city was removed from the list and the counties were remeasured and marked for the next closest city.  I then mapped them out on large national maps.

Results

This work generated three maps with corresponding lists of cities and the populations of the regions based on these cities.

This first map is based on regions with a minimum population of 2 million, with the following cities anchoring the regions and their given regional populations, from highest to lowest population of the central city:

  1. New York City, NY (10,861,700)
  2. Los Angeles, CA (11.624,092)
  3. Chicago, IL (7,312,584)
  4. Houston, TX (5,807,864)
  5. Phoenix, AZ (6,662,822)
  6. Philadelphia, PA (7,398,857)
  7. San Antonio, TX (3,836,400)
  8. San Diego, CA (3,322,432)
  9. Dallas, TX (3,742,720)
  10. San Jose, CA (3,329,396)
  11. Detroit, MI (2,384,057)
  12. San Francisco, CA (4,318,813)
  13. Jacksonville, FL (3,040,268)
  14. Indianapolis, IN (3,652,091)
  15. Austin, TX (2,079,499)
  16. Columbus, OH (3,736,506)
  17. Fort Worth, TX (3,586,057)
  18. Charlotte, NC (3,878,660)
  19. Memphis, TN (2,502,573)
  20. Boston, MA (6,831,829)
  21. Baltimore, MD (4,243,534)
  22. El Paso, TX (2,874,140)
  23. Seattle, WA (7,070,662) (This includes both Alaska and Hawaii, as will be explained below)
  24. Denver, CO (5,896,137)
  25. Nashville, TN (2,909,035)
  26. Milwaukee, WI (3,184,691)
  27. Washington, DC (3,031,043)
  28. Louisville, KY (2,949,715)
  29. Portland, OR (4,607,152)
  30. Oklahoma City, OK (2,542,568)
  31. Atlanta, GA (6,151,488)
  32. Kansas City, MO (3,814,650)
  33. Fresno, CA (3,032,183)
  34. Sacramento, CA (5,691,903)
  35. Omaha, NE (2,506,874)
  36. Miami, FL (2,785,746)
  37. Cleveland, OH (2,249,989)
  38. Raleigh, NC (2,252,861)
  39. Tulsa, OK (2,843,868)
  40. Minneapolis, MN (4,490,267)
  41. St. Louis, MO (5,069,109)
  42. Tampa, FL (5,049,680)
  43. Santa Ana (Orange County), CA (3,121,251)
  44. New Orleans, LA (2,534,949)
  45. Cincinnati, OH (3,472,024)
  46. Pittsburgh, PA (4,470,907)
  47. Riverside, CA (2,088,322)
  48. Toledo, OH (2,019,458)
  49. St. Paul, MN (2,573,057)
  50. Buffalo, NY (2,782,734)
  51. Greensboro, NC (2,678,241)
  52. Madison, WI (2,070,908)
  53. Orlando, FL (3,625,795)
  54. Birmingham, AL (2,896,134)
  55. Baton Rouge, LA (2,841,516)
  56. Arlington, VA (2,615,764)
  57. Akron, OH (2,307,186)
  58. Montgomery, AL (3,057,149)
  59. Richmond, VA (3,725,124)
  60. Shreveport, LA (2,146,547)
  61. Des Moines, IA (2,092,903)
  62. Augusta, GA (3,286,871)
  63. Grand Rapids, MI (2,311,561)
  64. Little Rock, AR (2,377,037)
  65. Knoxville, TN (3,215,185)
  66. Fort Lauderdale, FL (3,511,282)
  67. Salt Lake City, UT (4,773,812)
  68. San Bernardino, CA (3,454,754)
  69. Fayetteville, NC (2,047,029)
  70. Aurora, IL (3,986,086)
  71. Springfield, MA (3,183,813)
  72. Paterson, NJ (2,285,085)
  73. Syracuse, NY (2,641,398)
  74. Bridgeport, CT (3,876,777)
  75. Warren, MI (2,393,541)
  76. Elizabeth, NJ (4,235,727)
  77. Lansing, MI (2,543,980)
  78. Manchester, NH (3,289,238)
  79. Allentown, PA (2,559,796)

This second map shows regions with a minimum population of 5 million.  They are listed below in the same manner that they were previously.

  1. New York City, NY (15,100,008)
  2. Los Angeles, CA (15,562,860)
  3. Chicago, IL (12,213,121)
  4. Houston, TX (6,568,198)
  5. Phoenix, AZ (8,490,543)
  6. Philadelphia, PA (10,845,050)
  7. San Antonio, TX (5,398,906)
  8. Dallas, TX (5,916,711)
  9. San Jose, CA (9,241,701)
  10. Detroit, MI (8,757,618)
  11. Indianapolis, IN (7,153,419)
  12. Columbus, OH (7,066,082)
  13. Fort Worth, TX (6,422,682)
  14. Charlotte, NC (9,064,119)
  15. Memphis, TN (5,335,220)
  16. Boston, MA (9,275,561)
  17. Seattle, WA (8,755,217)
  18. Denver, CO (10,039,895)
  19. Nashville, TN (5,631,919)
  20. Milwaukee, WI (6,167,922)
  21. Washington, DC (11,269,595)
  22. Portland, OR (5,263,530)
  23. Atlanta, GA (11,943,974)
  24. Kansas City (9,015,985)
  25. Sacramento, CA (6,370,171)
  26. Miami, FL (6,297,028)
  27. Cleveland, OH (6,605,216)
  28. Raleigh, NC (6,911,460)
  29. Minneapolis, MN (8,704,527)
  30. St. Louis, MO (5,438,438)
  31. Tampa, FL (11,235,143)
  32. New Orleans, LA (6,317,469)
  33. Pittsburgh, PA (5,274,967)
  34. Riverside, CA (9,002,191)
  35. Springfield, MA (5,943,610)
  36. Paterson, NJ (6,595,744)

This final map is for regions with a minimum population of 8 million, based on the following cities.

  1. New York City, NY (24,002,264)
  2. Los Angeles, CA (15,562,860)
  3. Chicago, IL (17,521,680)
  4. Houston, TX (14,995,203)
  5. Phoenix, AZ (8,493,518)
  6. Philadelphia, PA (11,376,896)
  7. Dallas, TX (12,594,912)
  8. San Jose, CA (15,669,851)
  9. Detroit, MI (10,047,016)
  10. Indianapolis, IN (14,442,659)
  11. Charlotte, NC (14,787,271)
  12. Memphis, TN (9,796,539)
  13. Boston, MA (12,318,503)
  14. Seattle, WA (13,493,324)
  15. Denver, CO (10,100,944)
  16. Washington, DC (13,875,208)
  17. Atlanta, GA (15,249,097)
  18. Kansas City, MO (10,585,310)
  19. Cleveland, OH (14,161,269)
  20. Minneapolis, MN (9,192,555)
  21. Tampa, FL (17,532,171)
  22. Riverside, CA (9,044,828)

Discussion

There are a number of inferences that can be made from these findings.  The first that I would like to discuss is that, despite using county data, there are still a lot of straight line boundaries.  This is going to be the case as long as counties have boundaries as arbitrary as states.  A more thorough and accurate analysis would include a municipality-by-municipality, rather than county-by-county, analysis, but that would take more time than I am willing to put into this project at this juncture.  The arbitrary straight lines on the map can lead to some unusual results.  For instance, Grand Junction, CO, the county seat of Mesa County, is closer to Salt Lake City and to Denver on the first map, while most of the rest of the counties on the border follow the state line, leaving Mesa County jutting awkwardly into Denver’s region.

Another odd effect is what happens when water transportation is a factor.  Google’s walking directions take regular ferry service into account, so areas such as San Francisco Bay, Puget Sound, Lake Michigan and Massachusetts Bay have many more connections than areas such as Chesapeake Bay.  While in all reality the residents of Northampton County, VA may be more willing to ride a boat to Virginia Beach than to walk to Philadelphia, this isn’t taken into consideration here.  Rivers with infrequent bridges, or at least bridges lacking in pedestrian walkways, also pose a problem.  There are many counties in Arkansas, for instance, that are much closer to Memphis, TN than to Little Rock; however, the lack of bridges and regular ferry service across the Mississippi River made it so that the Google analysis gave many more areas to Little Rock.  Also, Google’s directions from Honolulu to the Mainland included “Kayak across the Pacific Ocean,” and no matter where you wanted the final destination to be, it went through Seattle, thus making Hawaii, as far as this discussion goes, a part of Seattle.

Another issue is the methodology used in selecting which cities would anchor areas.  After having attempted this analysis before with a top-down approach and being unsuccessful, I tried a bottom-up approach, starting with the smallest cities on my list and moving up.  This creates some situations that are somewhat awkward; for instance, Newark, NJ is much more of a population center than either Elizabeth of Paterson, NJ, yet it didn’t make the cut.  Tampa, FL, is another example; it is more likely that Jacksonville and Miami would split the state, rather than Tampa eliminating both of them.  I may in the future consider another top-down approach to see how the results differ.

There is also the fact that this search was limited to cities in the US.  If we were to do a more complete analysis, we would include neighboring countries and, time permitting, the whole world.  There are certainly cities in Alaska, for instance, that are much closer to Vancouver and even Victoria than they are to Seattle.  However, for the purposes of this study, it made sense to limit the scope to the United States.

The last problem with the model is the fact that I set minimum benchmarks.  This worked very well for the first map, which only has two regions exceeding Alexander’s limit of 10 million people, and those not by much.  However, when we get to a minimum of 8 million, nearly all of the regions exceed the limit.  It may be better to next time set a maximum number and split regions in two as they exceed that limit.

These weaknesses being established, there are a few recommendations that I would like to make after doing this research.  First of all, all counties should have one county seat.  There are a number of existing counties that have two seats, and even a few counties that have no seat.  Counties with more than one seat should settle on one and move on, while counties with no seat should either establish one or be dissolved.  Second, if counties are to exist, then all cities should lie within one.  I feel that there is a little bit of leeway in here for state capitals, such as Carson City, NV, which are just following the example of our nation’s capital, but most of the 39 independent cities in Virginia, for example, shouldn’t be independent.  Many of these cities are even the seats of the counties that they are not a part of!  Unless a city has the same boundaries as its county, like Miami and Boston, they should not function independently.  Counties should also be contiguous.  There are a few counties in Louisiana and Kentucky where changing river course or other events have cut certain parts of a county off from the rest of it.  These areas should become part of another, adjacent county.

Also, I will again refer to Christopher Alexander’s A Pattern Language: “Decentralize city governments in a way that gives local control to communities of 5,000 to 10,000 persons. As nearly as possible, use natural geographic and historical boundaries to mark these communities. Give each community the power to initiate, decide, and execute the affairs that concern it closely: land use, housing, maintenance, streets, parks, police, schooling, welfare, neighborhood services.”  While there is a lot in there, Alexander does seem to set 5,000 persons as a baseline for a functional community.  With that being understood, I propose that any counties under 5,000 in population be dissolved.  If this were done, the country would have 292 fewer administrative units to deal with.  The interesting thing is that most of these counties that would go away are not in the sparsely-populated regions of the Rocky Mountains, as I had supposed; they are in the Plains States, where counties were created arbitrarily after Jefferson’s survey and without any sort of requirements for a population to support them.  These counties have no reason to be there, and their citizens would be better off being a part of a real, larger community.

With these suggestions being made, there are still many things that we can learn from these maps.  I personally prefer the first map and think that it could be a good basis for establishing regional governments and possibly eliminating county governments, particularly in the East and in California, where the population is the most dense.  To properly follow the borders of these regions, state borders would also have to be amended.  In this process, States which don’t have significant population centers would be eliminated, including Alaska, Delaware, Hawaii, Idaho, Kansas, Maine, Mississippi, Montana, North Dakota, New Mexico, Nevada, Rhode Island, South Carolina, South Dakota, Vermont, West Virginia and Wyoming.

The second map, with the much fewer and larger regions, might not be as good for establishing regional governments, but may be more useful for realigning state boundaries to better reflect reality.  If this were the plan, then county governments would probably still be needed, but only if they conform to the requirements stated above.  The last map, with the fewest and very largest areas, might not function either as regions or states, but may be one example of how the country might be equitably divided if it were to break up into small countries.  It is interesting to compare this map to others of how the US could potentially break up, as seen here.

Finally, it should be remembered that mere numbers are not what links people to a city or a region.  Few people would ever say that San Jose is the heart of the Bay Area, despite it being considerably bigger than San Francisco.  The only way you would really be able to truly find a dividing line between New York and Boston would be to go door to door through Connecticut and ask people if they are Yankees or Redsox fans.  The only true way to establish a regional identity is through years of tradition and cultural association with an area.  In the words of Lewis Mumford from his epic The City in History, “Contrary to the convictions of census statisticians, it is art, culture, and political purpose, not numbers, that define a city.”

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Clean, affordable light rail also delivers economic lift


Greg Gormick brings us this story on the future of light rail in Toronto.  He says that the debate over Toronto’s Transit City light rail transit plan has been between critics who don’t know the benefits of light rail and supporters who have been unable to articulate those benefits.  He explains the differences between streetcars and light rail.  The later evolved from the former in European cities after WWII, when transit started losing ridership to cars.  Light rail became a mid-capacity system between high-capacity subways and low-capacity buses.  Light rail became larger, smoother, quieter, farther spaced, and faster, and had priority signaling and their own right-of-way.  At the same time, European cities embraced transit-oriented development, controlling sprawl and creating vibrant new neighborhoods.  They also embraced a concept known as lateral segregation, which gives transit users, drivers, cyclists and pedestrians their own part of the road adapted to their specific needs.

The effects have been economically and socially stimulating, and a number of cities that tore out streetcar systems have either replaced them with light rail or are in the process of doing so.  Edmonton was the first North American city to adopt light rail in 1978.  Since then, in places such as San Diego, Dallas and Portland, light rail has gotten people out of their cars, acted as an economic catalyst, and revived failing neighborhoods.  He argues that those who oppose the plan, who say that a new light rail line will have exactly the opposite effect, are fighting against historic precedent.  Light rail is also much cheaper than subways, an alternative supported by some, and can generally be built faster.  Building a new light rail system would make Toronto more competitive, more environmentally friendly, and more economically robust.

Taking Oak Cliff’s “Better Block” to Atlanta and the Congress for the New Urbanism


Robert Wilonsky of Unfair Park brings this awesome story on an urbanism technique that should be replicated in every small town and suburb in America.  Instead of coming up with a fancy proposal full of glossy architectural renderings and lofty language about the future, The Better Block Project simply took a block near the intersection of West 7th Street and North Tyler Street in the Oak Cliff neighborhood of Dallas and just made it right, overnight.  They installed a bike lane protected from the street by parking, narrowed the street by just setting up plants as bollards, and turned the reclaimed street section into cafe seating.  They added a little bit of paint to the buildings and voila, awesome little block.  What’s really amazing about this was that it was fast and relatively cheap–no new infrastructure, just some paint and some plants, but it still ended up being really cool.  This project has been squeezed into the CNU 18 schedule at the last minute due to its sheer awesomeness.  Check out the video.

Texas Sprawl Goes Out With a Bang, Development Sprouts on Irving Transit Line


Greg Lindsay brings us this article on development in Irving, Texas.  Many in Irving were unhappy when they lost the new Cowboys stadium to neighboring Arlington, but they have turned lemons into lemonade with a great plan for development on the former site of the recently demolished Texas Stadium.  The city is leasing the land to the Texas Department of Transportation, making more money than they ever did with the Cowboys, and have plans to create a dense, transit-oriented development along the future DART corridor.  The area will become the most walkable in the Metroplex outside of downtown Dallas.  The city has already begun building convention and entertainment centers and looks forward to $4 billion in private investment.  The plans include five-story apartment blocks with ground-floor retail.

Irving is known for office parks and gated communities, so the new development is not only very different, it is aimed at different groups than have previously been courted by Irving.  Some see the new dense, mixed-use and apartment-based development plans are seen by some as an admission that office parks and single-family McMansions are no longer enough.  Market demand is pointing in this direction, and Irving has been smart enough to take the lead, and they will profit from it.  Here are some renderings from the Irving Chamber of Commerce of what it might look like.

Green, Orange, and Blue Line DART Rail expansion to generate $4+ billion in economic activity in next 5 years


This story from Pegasus News Wire brings us more good news on the economic vitality of rail projects.  DallasDART light rail is expanding three lines, and those expansions, combined with existing projects on their Green Line, are expected to bring in $5.6 billion, and will create over 32,000 jobs.  DART President/Executive Director Gary Thomas said the study “is the latest evidence transit can help sustain and strengthen communities, particularly during tough economic times.”  Another interesting point is the high number of minority- and women-owned businesses associated with DART.  The light rail projects have continued despite economic downturn, sustaining important jobs, and has raised the value of development near transit stations.  DART is an extremely successful example of well-developed transit, and many other systems in this country could learn from their example.

Officials reshaping downtown Carrollton around light-rail hopes


Dianne Solis brings us this story about the efforts of Carrollton, TX to prepare for TOD.  A variety of new buisnesses have already opened in the city’s downtown, and they are beginning to build the high-density residential units that are needed to truly bring life and vitality to the community in a 24-hour basis.  The city is making an effort to make sure that good developments end up on the fast track to approval and completion.  They have done a great job of rehabilitating old buildings for new uses, including turning grain silos into a climbing gym.  This is all fueled by the prospect that trasit lines from DART will be crisscrossing the town in the near future.

5th Street Crossing project in downtown Garland fuels lofty goals


Ray Leszcynski brings us this story from Garland, an inner-ring suburb of Dallas.  Garland has been ripe for redevelopment for quite some time, and its old bones are finally getting some exercise.  The DART station has fueled various developments which are coalescing into a revitalized urban core.  Because of the variety of uses, the project isn’t expected to be as harshly affected as other nearby single-use projects have been by the recent economic downturn.  Really, it’s the same idea as a mutual fund, where you bundle together a variety of different stocks so that, even if one of them tanks, you’ve hopefully still got a bunch that are going strong.  In mixed-use developments, if residential tanks, you can covert it to office or some other use a lot easier than you can single-use districts.  This strength will hopefully allow Garland to continue to redevelop in a good, urban fashion.