A Markov Chain Model of Land Use Change

Recently published:

Minneapolis Aerial
Minneapolis Aerial

The set of models available to predict land use change in urban regions has become increasingly complex in recent years.  Despite their complexity, the predictive power of these models remains relatively weak.  This paper presents an example of an alternative modeling framework based on the concept of a Markov chain.  The model assumes that land use at any given time, which is viewed as a discrete state, can be considered a function of only its previous state. The probability of transition between each pair of states is recorded as an element of a transition probability matrix.  Assuming that this matrix is stationary over time, it can be used to predict future land use distributions from current data.  To illustrate this process, a Markov chain model is estimated for the Minneapolis-St. Paul, MN, USA (Twin Cities) metropolitan region.  Using a unique set of historical land use data covering several years between 1958 and 2005, the model is tested using historical data to predict recent conditions, and is then used to forecast the future distribution of land use decades into the future.  We also use the cell-level data set to estimate the fraction of regional land use devoted to transportation facilities, including major highways, airports, and railways. The paper concludes with some comments on the strengths and weaknesses of Markov chains as a land use modeling framework, and suggests some possible extensions of the model.

Thoughts on Transit and Urban Form

Hypothesis: Regular frequent transit service remains feasible even in single family homes in neighborhoods with a modicum of density.

The Land Use

Consider the 1 mile grid landscape that is common in the post-Revolutionary United States due to the Northwest Ordinance and the ease of development. The is roughly the streetcar era land use design.

While there are a variety of ways this grid can be carved up, one common way is to have

  • 10 cross-streets per mile of grid long direction (520′ )
  • 20 cross-streets per mile of grid in short direction (260′ )

This arrangement produces 200 blocks per square mile. The size of each block is:

  • 520′ x 260′ block (center line – center line)
  • 480′ x 240′ block (edge to edge), allowing space for roads.

If houses have a 40’ frontage with 110′ depth ( allowing 20′ for alley?) = 4,400 sq. ft. (~1/10 acre)

Note there are  640 acres per square mile and 43,560 square feet acre per acre.

This spacing gives 12 houses per block face long direction, or 24 houses per block. In this configuration, no houses face the short direction. Obviously this can be adjusted.

If there were only housing, this would give 4,800 houses per square mile

At 2 persons per household (which is definitely on the low side for single family homes, this gives us 9,600 PPSM in single family homes at typical built density. At 5 persons per household, this leads to 24,000 PPSM.

At 5 persons per household, we could increase lot size to 1/4 acre (neglecting roads) and still can get 2,560 houses per square mile  or 12,800 PPSM.

While some space is devoted to schools, parks, retail, commercial, and industrial activity, among other uses, I hope this is persuasive that 10,000 PPSM is feasible over large areas without being Manhattan-like high density. The City of Minneapolis for instance according to the 2010 Census has a density of 7,417 PPSM. At its peak population, it had over 10,000 PPSM.

The Transit

The target density for successful transit is often given as 10,000 persons per square mile (PPSM), as per Zupan and Pushkarev (also discussed here).

If we assume that every person originates lots of short trips (which can be dealt with by walking or biking) and one long trip per day (say going to work), the 10,000 PPSM would generate 10,000 transit trips per square mile. So we have 10,000 Boardings. This is roughly streetcar era demand in cities.

If we space transit routes on the 1/2 mile routes (as was typical of streetcars) both east-west and north-south, with stops where transit routes crossed and half-way between (i.e. 1/4 mile spacing between stops), the area is served by 21 stops. The four stops at the outer corners are shared with 4 other areas, and the 8 non-corner stops at the perimeter are shared with 2 other areas, while 5 stops are internal to the 1 mile square, gives us 12 equivalent dedicated stops for the area.

With 10,000 PPSM and 12 stops, each stop serves 833 people per day. If transit vehicles carry 50 people each, that is 17 full transit vehicles per day. Of course transit vehicles do not generally fill up at one transit stop, and over a 17 hour day, this would be 1 transit vehicle every hour. If instead we wanted service at 10 minute headways, but full vehicles, we would expect each vehicle to fill up 1/6 of its load at each stop (or about 8 passengers per stop). That would be a much higher load factor than generally observed.

The maximum walking distance to a transit stop would be (by Pythagoras SQRT of 0.25^2 + 0.25^2 =) 0.35 miles.

The Car

So what guarantees people will make 1 transit trip per day? If there is no good alternative, this is an easy choice. Today, this depends. The argument for using transit is that in our idealized grid-like city with a grid-like transit system, the transit system is as direct as every other mode, so there is no lost distance due to circuity. The only lost time is the schedule delay (which is a maximum on average of 5 minutes, less if people can time their wait to match the transit vehicle), and the time when the vehicle is stopped (and accelerating and decelerating) boarding and alighting passengers, which we know can be faster if people pre-pay, and the transfer time between vehicles (with a maximum of one transfer in the idealized grid, again with a maximum on average of 5 minutes, less if the routes are timed well). Finally with any transit advantages (e.g. signal timing priority, exclusive lane or stopping in lane, as opposed to weaving into stops) transit can recover some of the time lost vis-a-vis the automobile.


Where transit is better (faster, cheaper) than alternatives, and frequent enough, people will use it in large numbers. This is observed daily in large cities. Thus it must be feasible to obtain such faster, cheaper, frequent enough service levels. In most places in the US, the transit service and ridership is not there. Let’s work through an example.

For a five mile trip, there will be about 20 stops at 1/4 mile stop spacing. If each stop results in 30 seconds lost time (2-3 seconds per boarding plus acceleration/deceleration), that is 10 minutes of time lost there.  This will generally be slower than an automobile, even with  stop signs or red lights every 1/4 mile, as the time spent stop at the stop will be less than for transit, even with pre-payment. (Unless the auto is stuck behind a transit vehicle and cannot pass).

Initial schedule delay is 5 minutes assuming random arrivals.

Walk access time of (let’s say 1/2 of 0.35 miles or 0.18 miles at 3 miles per hour) is about 4 minutes. This is obviously farther than from the front door to a parked car at the home end. Destination walk egress time is probably similar  for most people. For transit to downtown, lower for transit (and higher for the parked car).

Transfer time is also non-trivial, and can be as high as another 5 minutes if it is effectively uncoordinated.

So now even with our idealized transit system we have lost something like 10+5+4+5+4 minutes or 28 minutes compared with the car for a 5 mile trip. At a value of time of $15/hour ($0.25/minute) this is the equivalent of $7. If the transit fare is $2, and the cost of gas (at $5/gallon and 25 miles per gallon) is $1 (not even considering carpooling), net additional out-of-pocket cost for transit is now the equivalent of $8. Of course, vehicle ownership ($10-$20/day) can be avoided, as can parking charges. We are not considering externalities, and other costs of vehicles that are not internalized.

The Express

We can make transit faster with express routes on limited access rights-of-way. If demand is high enough, we can make transit go faster, or have an even higher frequency, and stop less often. One disadvantage of express routes is a longer access/egress time (they can’t be spaced as close together if they are to achieve economies of scale, so they are on the mile instead of 1/2 mile spacing at best (as per London)). If that access and/or egress is by transit itself, that imposes additional scheduling time penalties. We can compensate because now our land use changes to take advantage of the express services. At express stations, densities rise. Apartments replace single-family homes. We can also give transit a higher frequency. Express buses and commuter trains often have low frequencies, while modern or modernized subways may have one train every 2 minutes or better. So if we increase the highest distance to a station for 1 mile spacing between stations and 1 mile between routes (so every station is a transfer), the walk access time is 1/2 of the maximum time of SQRT (0.5^2+0.5^2) = 0.71 or 0.35 miles. At 3 mph this is a walk time of  7.1 minutes on each end.

For a 5 mile trip with transfer Our lost time is 2.5 (30 seconds [per stop * 5 stops]) + 1 (schedule delay) + 7 (access) + 1 (transfer delay) + 7 (egress time) = 18.5 minutes. This is less than the local transit service above, and can be reduced for people who live closer to the station rather than spread out uniformly across the landscape. If we have higher travel speeds than auto (let’s say averaging 45 mph while in motion on exclusive right-of-way instead of 30 on surface streets), for a 5 mile trip the express transit time is 6.67 minutes instead of 10 minutes. But this 3.33 minute savings does not outweigh the lost delays due to access and waiting costs. This does not even begin to consider the additional costs of operating express vs. local services, or revenues from the service.

To reduce transportation costs with transit-like services, we can arrange cities linearly, thereby eliminating transfers and reducing access costs. This wastes accessibility for non-transit modes. So optimal urban form depends on the technology you are optimizing for. In a city where driving is perceived to cost $1/trip, and it saves between 18 and 28 minutes per trip, it is no wonder the automobile is the dominant mode for long distance trips even in historically transit advantageous places. Changing that requires changing the perceived (and real) cost of driving for drivers, as there is little that can be done on the transit supply side which will make a significant difference in the absence of that for most markets.

In dense areas, the market takes care of that, with expensive parking. In low density areas, there is enough room for everyone’s car without charging.


I believe systematically re-arranging existing cities for transit (or any mode) is putting the cart before the horse. Transportation should serve activities, and while transportation and land use co-evolve, that co-evolution is slow (over decades) and should be adaptable to alternatives.


One word – Plasticity

One word - Plastics

These are based on my brief closing comments at the WSTLUR conference in Delft.

We heard at the conference from two of the keynote speakers that “The Future is Uncertain”. While I don’t know if this is more true than before, it is certainly true. The question is: “How does one deal with uncertainty?”

One word - Plastics
One word – Plastics

In the Mike Nichols film The Graduate, Dustin Hoffman’s character (Benjamin Braddock) is advised by Mr. McGuire about the future “One word – plastics“. This advice was not too bad for 1968.

Mr. McGuire: I want to say one word to you. Just one word.

Benjamin: Yes, sir.

Mr. McGuire: Are you listening?

Benjamin: Yes, I am.

Mr. McGuirePlastics.

Benjamin: Exactly how do you mean?

Mr. McGuire: There’s a great future in plastics. Think about it. Will you think about it?



I will rephrase that for the transportation and land use context: “One word – Plasticity”.

Plasticity is defined as the ability to change in response to changes in the environment. This may be good or bad (for instance, we might not want plastic deformation in structures). However, since we cannot accurately forecast, and the long-term is unpredictable, we need Transportation-Land Use designs which are adaptable – able to change function over time, and flexible – able to do many things at once.

How do we do this?

I don’t have answers, just challenges.

Now we focus on built environment, embedded infrastructure, and long-lasting constructs, which is essentially the definition of anti-plasticity.

Developing and evaluating new plastic, adaptable, and flexible designs for Transportation – Land Use systems, I believe, is the key research and policy question in our field going forward.

Does BRT have Economic Development Effects?

In a recent post on Streets.MN, I asked if Streetcars had economic development effects, and concluded we have no evidence to date.

In contrast, for Bus Rapid Transit systems, there is lots of peer-reviewed evidence, though not as much as we might like.

First, obviously the nature of the impacts depends on what kind of BRT you are talking about. Broadly, in the Twin Cities we divide systems into freeway-based BRT systems with stations, and arterial-based BRT systems with stops. The differences are that stations are more elaborate than stops, and less frequent. Worldwide, systems are hybrids.

A 2008 review: Bus rapid transit systems: a comparative assessment by David Hensher and Tom Golob found wide variations in the types of BRT across many dimensions (speed, construction costs, ridership, subsidies, etc.) with some systems offering a peak headway of well better than 1 bus per minute, while others were at 10 minutes between buses.

BRT thus has many distinguishing characteristics, ITDP recently developed a ranking system, the BRT standard. The categories for which points are awarded in BRT Basics are:

  • Busway alignment: 7 points
  • Dedicated right-of-way: 7 points
  • Off-board fare collection: 7 points
  • Intersection treatments: 6 points
  • Platform-level boarding: 6 points

The standard scorecard is more complicated, and includes many other factors as well. The best systems are rated Gold, and so on. I don’t agree with all of the points or categories, but this is a good place to start. The US and Canadian systems (Los Angeles, Eugene, Pittsburgh, Las Vegas, Ottawa) tend to fall into the Bronze Category, though Cleveland’s Health Line makes Silver (appropriate given the color of the buses and its former name “The Silver Line).

[I have not scored the University of Minnesota Transitway (which may or may not be considered BRT (I would, wikipedia is mixed on the matter)), or the Red Line, which were not ranked (but would make a good term paper for a transportation class).]

As many people worry, something can be pitched as a high-quality service, and then whittled down by the time of deployment, or afterwards to save costs. Frankly, this can happen with any technology, just look at what has happened to service frequencies on the Phoenix LRT, which are since 2010 12 minutes, but were 10 minutes at opening in 2008). Clearly as BRT is developed and deployed, this needs to be monitored. But this is true for any service with net ongoing operating costs that can be reduced over time.

Some findings from the peer-reviewed literature are below (sadly some of the papers are behind paywalls, let me know if you wants). Most, but not all of the evidence is favorable to measurable economic development impacts, clearly every system is unique:

  • Bus rapid transit impacts on land uses and land values in Seoul, Korea by Robert Cervero and Chang Deok Kang. “Multilevel models reveal BRT improvements prompted property owners to convert single-family residences to higher density apartments and condominiums. Land price premiums of up to 10% were estimated for residences within 300 m of BRT stops and more than 25% for retail and other non-residential uses over a smaller impact zone of 150 m.”
  • Redistributive effects of bus rapid transit (BRT) on development patterns and property values in Seoul, Korea by Myung-Jin Jin. This study uses simulation, rather than empirical evidence, so keep that in mind. “First, Seoul’s BRT contributes to increased development density in urban centers, acting as a centripetal force to attract firms from the suburbs into urban cores and supporting arguments for Smart Growth proponents. Second, unlike its redistributive effects on nonresidential activities, the BRT has a limited effect on the redistribution of residential activities, implying that residential locations are less sensitive to accessibility improvements made by the BRT than are nonresidential locations. Third, reflecting the transferred space demands from the suburbs to the urban cores, the CBD reaps the highest property value gains, while all of the outer ring zones suffer from reduced property values.”
  • The impact of Bus Rapid Transit on location choice of creative industries and employment density in Seoul, Korea by Chang Deok Kang. “[T]he BRT system is the favorable component for the location of creative industries and service sectors within 500 meters of BRT-bus stops. In addition, the BRT operation increases the employment density within the same distance to the bus stops by 54%.”
  • The Impact of Bus Rapid Transit on Land Development: A Case Study of Beijing, China by
    Taotao Deng and John D. Nelson. “The statistical analysis suggests that accessibility advantage conferred by BRT is capitalized into higher property price. The average price of apartments adjacent to a BRT station has gained a relatively faster increase than those not served by the BRT system. The capitalization effect mostly occurs after the full operation of BRT, and is more evident over time and particularly observed in areas which previously lack alternative mobility opportunity.”
  • Value of accessibility to Bogota’s bus rapid transit system by Daniel Rodriguez and Felipe Targa. “Results suggest that for every 5 min of additional walking time to a BRT station, the rental price of a property decreases by between 6.8 and 9.3%, after controlling for structural characteristics, neighbourhood attributes and proximity to the BRT corridor. “
  • Capitalization of BRT network expansions effects into prices of non-expansion areas by Daniel Rodriguez and Carlos Mojica. “Properties [in Bogota] offered during the year the extension was inaugurated and in subsequent years have asking prices that are between 13% and 14% higher than prices for properties in the control area, after adjusting for structural, neigh- borhood and regional accessibility characteristics of each property. “
  • Walking accessibility to bus rapid transit: Does it affect property values? The case of Bogota ́, Colombia by Ramon Munoz-Raskin . “The main results showed that, with respect to the value of properties in relation to proximity, the housing market places value premiums on the properties in the immediate walking proximity of feeder lines. The analysis by socio-economic strata showed that middle-income properties were valued more if they fell closer to the system, while there were opposite results for low-income housing. Finally, analysis across time reflects slight average annual increases in property values correlated with the implementation of the system in two specific areas analyzed.”
  • Recent developments in bus rapid transit: a review of the literature by Taotao Deng and John D. Nelson. ” In common with other forms of mass transit, a full‐featured BRT has the potential to offer significant effects on land development; the literature review also indicates that more work is needed to investigate this.” (The general cry of the academic – more research is necessary).

All of this is consistent with general observations and what theory would predict about accessibility improvements. A transportation system that adds to accessibility in a significant way warrants a premium in the prices people are willing to pay to take advantage of it.

Five Rules for Vital Streets | streets.mn

Now at streets.mn Five Rules for Vital Streets: “There are three seeds:

Five Rules for Vital Streets

Streets are vital when there is the feeling that there is something going on, of being where the action is. Successful places have vitality. By definition, dead places don’t. We don’t want too much vitality everywhere (I don’t want it on my street after 9 pm) and probably can’t support it. But surely we could have more active places then we do now with a better location of activities.

We drive to places we can walk around, rather than walk around our own neighborhood, unless we happen to live in a place with vitality.

Istanbul 2004 - 19

Why do we want to walk around? Because there are multiple things to do: find food, browse books, hear music, entice the intellect, watch people, stimulate the senses. This concentration of activities only happens because of the crowds around, and the crowds only gather because of the concentration. More begets more.

These are ‘economies of agglomeration’ as the economists might say or perhaps ‘network effects’. But they allow for the spontaneous walk-in business rather than the planned trip.

Many businesses are unlikely to attract spontaneous walk-ins, for instance vacuum cleaner repairs, [I don’t normally walk around with a vacuum cleaner on the hope I will find a repair shop] and thus lose little by not being located in the center of action and save much on rent. There are limits to the value of agglomeration.

Some restaurants are so good, they require a reservation, and thus there is little spill-in traffic. But other businesses, by saving on rent, are foregoing additional business. Moreover, those businesses are denying potential spillover traffic to their would-be neighbors. It is a calculation that proprietors must do for themselves, but there is a coordination function that a good entrepreneur can serve, matching businesses that attract walk-ins with compatible stores, and maybe subsidizing (lowering the rent for) those that generate more spill-over traffic than they attract.

There are three seeds:

  • A concentration of people (customers, though they need not be spending money, that helps)
  • A concentration of stuff (suppliers, who need not be selling)
  • An environment that encourages people to spend time doing stuff (marketplace)

People concentrate for a variety of reasons – to exploit the material resources of the earth, to have safety in numbers, to find a pool of potential mates, or simply because it is at the intersections of routes between two other places. These intersections (nodes in transportation lingo), create opportunities.

In the streetcar era, people might change lines at a node, and those pedestrians would contribute to the street life necessary to support new businesses. In the highway era the scale changed, and nodes are the interchanges of freeways. Businesses, and especially shopping malls, take advantage of these points of high accessibility. But the shopping mall is now clearly the destination, not a side-product of a transfer point in the same way street-car corners were. Some further assertions about human nature:

  • People like pleasant climates – dry, not too hot, not too cold, clean air, not too loud.
  • People want to feel safe – they don’t want a car careening out of control disturbing their sidewalk café meal, they don’t want to think they will get run over crossing the street.
  • People are lazy – they don’t want to walk too far to get where they are going. If they are driving, they want easy convenient parking near their destination. They like to cross the street mid-block and don’t want to have to walk to intersections.
  • People are cheap – they don’t want to pay for that easy convenient parking, they prefer lower to higher prices for the same good.

The last two be summarized by the idea that “People take the path of least resistance”.

Observing cities around the world with an informed, but casual analysis leads me to assert some rules about the environment that lead to vitality or vibrancy.

  1. Buildings on the sidewalk – vibrant areas have buildings that abut sidewalks with not large gaps between the building and the walk. The density of activity is necessarily reduced by space between building and path (and thus other buildings).
  2. Sidewalks on the street – to have vitality, sidewalks must abut the street, or *be* the street in pedestrian only areas. Pedestrian only areas can work, and anyone who says otherwise has other interests at heart. This does not mean that they will work, but given the right environment, people would prefer to shop without having to look out for motorized vehicles.
  3. Streets move slowly – fast streets make pedestrians feel unsafe, and thus reduces the benefits of being on the sidewalk. Ideally streets are moving at pedestrian speed in the pedestrian area. Of course streets leading to the pedestrian area move faster, or people could not get there. One-way streets may not be inherently problematic, but one-way streets are generally that way to move more vehicle traffic faster through the area, which is the opposite goal of moving pedestrians between buildings within the area. On the other hand, one-way streets are easier to cross.
  4. Vehicle space on the street is minimal – wide streets increase the distance pedestrians must walk to reach other activities. Narrow streets give access to more stuff in less time. Hence the reason many enclosed shopping malls work better than many shopping streets is the density of stuff is fairly tight.
  5. Opportunities to explore just around the corner – hidden (pleasant) surprises are one of the things that make cities interesting to be in, if I go around this corner what will I discover. The same opportunities do not exist in an enclosed shopping mall, where everything is pre-mapped and tightly controlled, and I know each “block” ends at a parking ramp. Hidden unpleasant surprises however are one of the things that can kill a city, I don’t want to experience dread when I walk down an alley attached to my favorite shopping street.

This set of rules is by no means complete, but rules like these created street life in streetcar era places, and they create vitality in the better shopping malls.

What other rules do you have?

What are the most and least vital shopping areas in Minnesota?

Updated from a Transportationist post: July 12, 2007.

Land Developability


Guangqing Chi has a new website devoted to Land Developability:

“Land developability is a measure of land availability for future conversion and development in a geographic entity, such as a state, a county, a city, a census tract, or other geographically aggregated units. The land developability index is generated using spatial overlay methods based on data layers of surface water, wetland, federal/state-owned land, Indian reservation, built-up land, and steep slope, which are all seen as undevelopable. The land developability index can be used for regression modeling when land use and development is a consideration of an analysis, for detecting potentials for land conversion and development, and for predicting the direction of future land use and development.”

This looks like a very useful piece of research data infrastructure.

Utilizing the Space Beneath Bridges – Some More Examples | streets.mn

Cross-posted from streets.mn: Utilizing the Space Beneath Bridges – Some More Examples

I want to thank Reuben for posting Utilizing the Space Beneath Bridges

Since I cannot put images in comments, I will post these as further examples, from Borough Market, London, Brixton, and the Darling Harbour, Sydney, respectively. The first three pictures are under railway bridges, the last a freeway bridge.

Borough Market - London
Borough Market – London
Borough Market, London
Borough Market, London
Brixton, London - Shops in the Viaduct
Brixton, London – Shops in the Viaduct
Carousel in Sydney, Australia
Carousel in Sydney, Australia

Affordable housing is existing housing | streets.mn

Cross-posted from streets.mn: Affordable housing is existing housing

Affordable housing is existing housing

We see gobs of money spent on new “affordable housing”.

Ok, “gobs” is not a very precise term. Marlys Harris reports in streets.mn affiliate MinnPostthat nonprofits are pushing for 4500 units of affordable housing on the Central Corridor. You can do the math on how much that would cost.

Let’s define “affordable housing”. Obviously different programs have different definitions.Wikipedia says: “In the United States and Canada, a commonly accepted guideline for housing affordability is a housing cost that does not exceed 30% of a household’s gross income.”

This of course is arbitrary. Clearly it is more difficult to spend 35% of gross income than 30%, or 30% than 25%. Canada once had a 20% rule, India has a 40% rule.

Incomes vary, so typically affordable housing programs are concerned with affordability relative to median household income.

So why is it government’s business to build, or encourage to be built, new, affordable housing?

Public housing, the “projects,” were often built in the US from the New Deal through the Great Society eras, and were one set of attempts in the US to address the problem by building new houses to replace inadequate old houses. (Public Housing has an earlier history in Europe, e.g.). But soon these projects came to be seen as the problem not the solution. Newer housing programs diffuse these housing projects a bit more (I suppose they could not have been diffused less) throughout metropolitan areas (scattered-site housing), though there is a focus on affordable housing around transit stations, limiting the diffusion.  Marlys Harris reports Myron Orfield research “since 1986, 83 percent of affordable housing units in the metro have been located in a way that contributes to segregation.” The HUD program HOPE VI aims to fix existing housing projects, though it may replace 2 units with 1, thereby reducing the supply of housing.

The downside of scattered site housing is the reduction in economies of agglomeration. If there are services that are easier to provide at one location serving more people, scattering the housing increases the costs of reaching those services. The aim is to reduce the diseconomies of agglomeration (the crowding, the low employment rates, etc.)

There are also housing voucher programs. In the US, “Section 8” (or Housing Choice Voucher Program) is a major version of this. It currently subsidizes the rents of 1.5 million households. (The program also has a supply-side component, which subsidizes the production of housing).

In the Twin Cities there are a variety of programs. The one that annoys me most is theTransit Oriented Development (TOD) grants. which says:

The Livable Communities Act (LCA) Transit Oriented Development (TOD) program is a new funding resource intended to help catalyze Transit Oriented Development in and around light rail transit, commuter rail, and high-frequency bus transit stations by focusing on proposals that are:

  • In a Transit Improvement Area (TIA) designated by the Minnesota Department of Employment and Economic Development (DEED) or TIA-eligible station areas located along light rail, commuter rail or bus rapid transitways operational by 2020.
  • Within one-quarter mile of any spot along high frequency local bus lines.
  • Within a one-half mile radius of bus stops or station on high-frequency express routes where significant passenger infrastructure is in place.


The Livable Communities TOD program is an extension of the established Tax Base Revitalization Account (TBRA) and Livable Communities Demonstration Account (LCDA) programs, and allows applicants to combine in one application requests for resources from four different funding categories:

    • Tax Base Revitalization Account (TBRA) Contamination Cleanup Site Investigation TOD grants – these grants are intended for applicants that have or will purchase a redevelopment site with suspected or perceived contamination and are seeking public funding to assist with the cost of determine the scope and severity of the contamination and to develop a cleanup plan. The investigation grants are intended to encourage an early start to the environmental remediation process.
    • TBRA Contamination Cleanup TOD grants – these grants are intended for applicants that have recently completed their cleanup site investigation and are seeking public funding to assist with the cost of implementing a cleanup plan and beginning redevelopment.
    • Livable Communities Demonstration Account (LCDA) Pre-Development TOD grants – these grants are intended for applicants who are defining their project through such activities as design workshops, preparing redevelopment, corridor or station area plans, developing zoning and land use implementation tools such as overlay zones or zoning districts, or determining strategies for land banking and land acquisition.
    • LCDA Development TOD grants – these grants are intended for applicants that are ready to:
      • acquire sites and/or conduct site preparation activities; and/or,
      • begin development or redevelopment and are ready to build the infrastructure necessary to support it.


I am okay with contamination cleanup site grants. Someone has to clean them up, and clearly we have failed previously in making the polluters accountable.
It is the Livable Communities grants that puzzle me. The transit system was supposed to create value, the developers should be paying a premium to be near it (a premium which we can capture to help pay for the infrastructure), we shouldn’t be paying them.

We have lots of existing housing that is slowly deteriorating due to lack of capital infusion. Yet we spend money to create new developments. Wouldn’t it be better to give money or vouchers (if you don’t trust them with cash) to the people you want to help (low or low-middle income people), and let them purchase (and repair) housing on the open market? Or give money to people salvaging existing structures that would otherwise go unused, if salvage costs are less than new construction. There are at least 700 vacant and condemned properties in the City of Minneapolis alone (2011 data). This does not include vacant rental properties. The Census found 15,000 vacant units in the City of Minneapolis. Making housing “affordable” should start there.

If there were a demand for housing near transit, which there should be if it is in fact as useful as the planner claim, it will be quickly met if local jurisdictions don’t create too many needless regulations. That demand should be fulfilled by serving the best and highest use, to maximize the value captured by the community from its infrastructure.

New affordable housing is the same model we have with public infrastructure, it is much sexier to build a new road or rail line than maintain or rehabilitate an old one.

Clearly it is sad when someone cannot afford to live in adequate housing. But there is lots of housing around which is vacant or not fully occupied, and there are lots of people with inadequate housing. Unemployment in the residential construction trades is still relatively high. Neighborhood groups are trying to save some of these vacant and condemned houses.

This seems like a market clearing problem, not one requiring new supply.

Markov Chain Model of Land Use Change in the Twin Cities (working paper)

Michael Iacono, David Levinson, Ahmed El-Geneidy, and Rania Wasfi (2012) Markov Chain Model of Land Use Change in the Twin Cities. (Working Paper)

The set of models available to predict land use change in urban regions has become increasingly complex in recent years. Despite their complexity, the predictive power of these models remains relatively weak. This paper presents an example of an alternative modeling framework based on the concept of a Markov chain. The model assumes that land use at any given time, which is viewed as a discrete state, can be considered a function of only its previous state. The probability of transition between each pair of states is recorded as an element of a transition probability matrix. Assuming that this matrix is stationary over time, it can be used to predict future land use distributions from current data. To illustrate this process, a Markov chain model is estimated for the Minneapolis-St. Paul, MN, USA (Twin Cities) metropolitan region. Using a unique set of historical land use data covering several years between 1958 and 2005, the model is tested using historical data to predict recent conditions, and is then used to forecast the future distribution of land use decades into the future. We also use the cell-level data set to estimate the fraction of regional land use devoted to transportation facilities, including major highways, airports, and railways. The paper concludes with some comments on the strengths and weaknesses of Markov chains as a land use modeling framework, and suggests some possible extensions of the model.