Category Archives: New Urbanism

The end of this blog and the beginning of a new one


I haven’t written in this blog in a very long time.  I’ve been very busy, moving across the country, starting grad school, and various other things.  I’ve also been getting a little tired of focusing just on New Urbanism.  I think part of what’s wearing me out is that I’m tired of dealing with different people’s definitions of New Urbanism.  To some (myself), it’s compact, mixed-use, pedestrian-centered development.  But to many planners, New Urbanism is Calthorpe and Duany building greenfield development with kitsch, traditional decoration.  I’m not wild about greenfield development, and I’m especially not fond of Calthorpe, who more often builds uses adjacent to each other rather than truly mixed or even vertically mixed.  Duany has done great theoretical work and some wonderful projects on the ground, but many have been greenfields that aren’t connected to transit and central cities.  Norquist, on the other hand, is an urban, central city New Urbanist, and I find myself very much in line with his rhetoric.  And as far as architecture goes, I feel that it’s secondary to true urbanism.  Although I probably want a porch on the house I finally live in, I don’t feel that everyone else should have one.

I want to comment on things not related to New Urbanism, both things still related to planning and things related to architecture and other topics.  I also want a place to just spout off every once in a while.  With that in mind, I have started a new blog, Munson’s City.  I hope that those who have been reading my blog for a while will visit my new one and continue to take interest in my opinions on architecture, urbanism, and everything else.

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.”

The City in History


I recently finished reading Lewis Mumford‘s 600-page masterpiece, “The City in History.”  I think I folded more corners and underlined more paragraphs than I ever have before.  But to help myself understand the form of cities in the time periods described by Mumford, I drew them out.  I refrained from things like the neighborhood unit and the garden city, for which there are entire books, but drew the basic features of cities in different periods and places.  So, with no further ado, here is my illustrated guide to Mumford’s “The City in History.”

Mesopotamian City

Egyptian City

Greek City

Greek Colony

Roman City

Medieval City

Baroque City

Commercial City

Industrial City

Early Suburb

Conurbation

American Makeover Episode 1 – SPRAWLANTA


I probably should have plugged this a long time ago considering that I actually gave these guys money (and anyone who knows me knows I’m not loose with cash), but better late than never.  The creators of last year’s award-winning short film Built To Last have taken their efforts to the next level, creating American Makeover, a series of videos on sprawl in different parts of the city and efforts that are being made to overcome it.  Their first episode, SPRAWLANTA, looks at Atlanta, Georgia and how it has developed, taking special care to highlight Glenwood Park, a growing New Urbanist development there.

To continue their work, these guys need your help.  They are quite a bit shy of the funding goal that they need to achieve to continue this project.  I gave them a small contribution and got my name put at the end of SPRAWLANTA, so feel free to donate either out of interest in the project or self-interest, just help these guys to continue making great videos.  Here is SPRAWLANTA, for your viewing pleasure.

City Council approves cars on K Street


Ben Adler brings us this story on Sacramento‘s recent decision to reopen the K Street Pedestrian Mall to cars.  K Street, as with many similar projects across America, died when it was closed off to vehicle traffic, losing shoppers and gaining criminals.  This is actually a great decision and will hopefully reinvigorate the area.  Even though I don’t use a car myself, I and many other New Urbanists realize that cars still play a very important role in cities.  Most people still travel by car, and if you don’t allow cars at all then you don’t allow a large segment of your population.  Cars are good for retail because it allows more people to see street signs and to take part in commerce.  It also puts more eyes on the street, reducing crime.  Parked cars along streets add to pedestrian safety, creating somewhat of a wall between pedestrians and fast-moving cars.  The problem comes when people plan for cars only, allowing them to go at lethal speeds, providing too much parking, and diminishing the pedestrian scale of a place, making it boring and dangerous for people walking or biking.  Good communities need to plan both for cars and for people, and to give precedence to people, because as long as they are able, the cars will still come.

New USDOT Report Identifies Win-Win Transportation Emission Reduction Strategies


Considering my recent uptick in searches related to Todd Litman, win-win emission reduction strategies and federal implementation of New Urbanism, some of you may have already heard about this.  Nonetheless, here is Todd Litman’s latest Planetizen article on the US Department of Transportation‘s Earth Day release of their report, Transportation’s Role in Reducing US Greenhouse Gas Emissions.  This shows a shift in policy away from simply advocating the creation and buying of more energy-efficient vehicles, since this has little long-term effect on emissions and none on other problems such as congestion, accidents, and sedentary living.  This report evaluated the net costs of implementing different transportation strategies, and found the following to be most effective:

Not only do these save money in reducing carbon emissions, but they also reduce congestion, parking costs, consumer costs, accidents, energy costs, and sprawl, while improving public health and mobility for non-drivers.  Litman says that the savings estimates may be conservative, because the study relied on out-dated data about how much can be saved by vehicle reductions and the benefits of pay-as-you-drive insurance.  Even with these conservative estimates though, it is exciting to see the federal government recognizing the importance of transportation and planning policy in reaching other goals.

How Urban Planning Can Improve Public Health


This story by Jonathan Lerner tells us about smart growth as a public health tool.  Scientific studies are quantifying how our built environment affects our health.  Depression, for example has been traced to a lack of open space, suburban isolation, and a lack of transportation options.  Cars pollute the air and trap people alone for long periods of time, as well as causing accidental injuries and deaths.  They have also contributed to our sedentary lifestyle, which can lead to obesity, diabetes and other conditions.  Car-dependent development patterns destroy farmland, contributing to a lack of local food, aiding industrial farming, and forcing those who live in the suburbs to have multiple cars.  Planning was originally implemented as a public health endeavor, to get people away from polluting factories, but the two have become divorced in our time.  They need to come back together.

One example of this reunion is the joint effort of CNU and the CDC to put on CNU’s most recent conference, “New Urbanism: Rx for Healthy Places.”  A number of past efforts by CNU leaders, such as the Ahwahnee Principles, have also related to public health, while the CDC’s new Healthy Community Design initiative shows a new interest in planning issues.  Recent studies have also shown that mixed-use, walkable communities have higher levels of physical activity and lower levels of obesity, as do areas with good transit and access to parks.  Exposure to nature also may have a positive effect on ADHD.  Hopefully these new numbers can help turn theory into policy.  Other important studies show that compact communities have lower overall emissions and that people who live near major roads and highways are more prone to emissions.

More studies are needed to investigate the effect of communities and buildings on mental health and social capital.  Walkability needs more study, since a five-minute walk for a young athlete is different than a five-minute walk for an elderly person.  Parks need more research to determine whether it is better to have one large park, many small parks, or a mixture of the two.  Urban and suburban farming could address local food issues as well as take better care of vacant land.  Planning is also beginning to address issues of aging in place, or planning for all age groups, who may have different mobility and land use needs.  These improvements to public health, however, need to be accepted by a broader range of professionals and decision makers, as well as be accepted by a public that is often averse to change.  Planning needs to be recognized in a more holistic manner, addressing health, social, political and environmental issues, as well as many others.  Some municipalities are implementing health impact statements, similar to the environmental impact statements that have been required for major development since the 70’s.  But to really change the way cities and health interact, we need to make drastic changes to our transportation infrastructure and our land use patterns.