Tag Archives: Denver

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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Pedestrian-friendly Miami 21 zoning code approved


In case anyone in the planning world hasn’t heard yet, Miami recently approved Miami 21, making it the largest city in the world to approve a form-based code.  Read about it on the Miami Herald, the Congress for the New Urbanism, Planetizen, and Streetsblog.  After four years of debate, editing, and over 100 neighborhood meetings, the commissioners voted 4-1 to pass this plan which will encourage walkability, mixed use, concealed parking, and an appropriate scale of development.  Mayor Manny Diaz said that this plan will finally allow Miami to be classified with New York, Chicago and Paris as great cities of the world.  “I’m going to tell you that history will judge us right,” he said.  The code is based on the SmartCode template, adapted to have a variety of higher-intensity transect zones for the many skyscrapers of Miami.  This vote is the culmination of years of work from Elizabeth Plater-Zyberk of the University of Miami and Duany Plater-Zyberk, as well as city staff and others.  Miami leads a growing trend of large cities adopting form-based code, with Denver close on its heels.  Miami will be a living laboratory to test the effects of form-based code on large cities.  This is the greatest victory yet for form-based codes and arguably one of the greatest for the New Urbanism movement as a whole.

Not-So-New Urbanism


This site is how Latest Word chose to celebrate CNU making it’s visit to Denver.  They took the chance to analyze the various new Urban developments that have gone up since CNU last came to town.  So far they’ve done Stapleton, Belmar and Bradburn Village.  Their perspective is certainly that of true urbanists, and not the suburbanites that sometimes think New Urbanism is just small lots.  It’s good to see an outside view of these developments, and I look forward to future updates.

The Choo-Choo Diaries: A ‘Salon In Motion’ On The California Zephyr


Matt Dellinger of The Infrastructurist brings us this article on his adventures on the California Zephyr, a train full of New Urbanists bound for Denver.  There were more than a few high-profile individuals from the world of New Urbanism on the train: Robert Davis, the developer of Seaside; John Anderson, a Born Again New Urbanist after he completed the Mall of America; and William Lind, the pipe-smoking, conservative supporter of transit and urbanism.  A variety of issues were discussed, many planning related (such as using California’s new laws on green communities and the impact of cheap oil on America), some less so (such as whether or not computers are going to Hell).  A fun read.

Touting new urbanism


Gene Davis brings us this article from the Denver Daily News about the beginning of CNU 17.  According to CNU spokesman Steve Filmanowicz, Denver will better weather this economic crisis because it’s embrace of New Urbanism allows it to better attract young urbanites as demographics continue to shift, and it will be more cost-effective and environmentally friendly for everyone involved.  Denver is the only city to host CNU’s annual conference twice, and it’s multiple examples of New Urbanist developments (Larimer Square, Highlands’ Garden Village, Stapleton, Belmar and Prospect are cited in this article) are complimented by the fact that seven of the area’s 13 malls are being renovated into more walkable forms.  I wouldn’t be at all surprised to see more reports like this as CNU 17 continues.

Vintage Colors Part One: An Introduction


This article by Jaime Brunner describes a characteristic of New Urbanism that is often overlooked: color.  She describes the flourishes of color characteristic of Art Deco and Victorian architecture, and how we have moved towards a great variety of beiges in our color pallet.  She compliments Stapelton and Prospect (again with the Denver compliments) for bringing back color, as well as integrating different architectural styles.  Many New Urbanist communities do have a wider variety of colors than more conventional neighborhoods (Utah’s most prominent New Urbanist community, Daybreak, has a street that has been nicknamed Crayola Street).  They stand out, they have personality, and in a straight affront to the idea that neutrals help resale value, they have been better weathering the recent economic turmoil than their beige counterparts.

Stapleton, LoDo, Belmar redefine “community”


Denver seems to be outdoing itself to prove PBS wrong in their portrayal of the city in Blueprint America.  Norman Gerrick brings us this article describing some of the characteristics of Denver’s New Urbanist developments.  According to his article, California neighborhoods built before 1950 have one third the traffic fatalities of newer neighborhoods, because the new ones are car based and the old ones are not.  He says that the sprawl model, which we expected to make us safer, has failed to do so.  Some areas, such as Denver’s Stapleton, LoDo and Belmar, are giving up on the sprawl model and returning to urbanism in what we now call New Urbanism.  But as many in the development community know, there are significant hurdles to this form of development, from single-use zoning codes to complicated financing.  He, along with practically all New Urbanists, calls for an end to these hurdles.