1. Relevance
1.1. Value of Understanding the distribution of Urban Amenities
1.1.1. An accurate consideration of how the distribution of urban amenities affects the shape of a city gives urban planners and policymakers the information to make more effective decisions when attempting to influence city development.
1.1.2. Previous econ thesis work on the implicit value of residential tree canopy in Portland considers how residential trees contribute to the housing market
1.2. Criticism of City Planning as rejecting the influence of human use
1.2.1. Jane Jacobs: The Death and Life of Great American Cities
1.2.1.1. Advocated for mixed-use areas which reflected the vibrancy of local residents
1.2.1.2. "How cities work in real life" versus in orthodox planning models not grounded in reality
1.2.1.3. Direct attempts to address urban issues-as-symptoms have been unsuccessful e.g. public housing projects devoid of any vibrancy
1.2.2. Necessity of considering urban development within the context of the populations which inhabit it, how they use it, and what they value about it
1.2.2.1. Multi-faceted view of City Shape
1.2.2.2. An alternative approach to addressing issues-as-symptoms: approach the amenity access that residents and businesses have, and see if it is adequate to support the kind of vibrancy which Jacobs envisions
1.3. 4-6 Pages
2. Methodology
2.1. The Qualitative Regression
2.1.1. In statistics, a regression compares trends across data points, and mathematically generalizes a relationship between independent and dependent variables
2.1.1.1. Often, there is one independent variable-of-interest, whose relationship with the dependent variable is in question. However, to control for (and simultaneously examine) the influence of other factors on the relationship-of-interest, these factors are included in the regression as endogenous independent variables
2.1.2. I propose to conduct a process which is similarly motivated, but not so easily represented mathematically
2.1.2.1. Zooming In, Zooming Out
2.1.2.1.1. Begin with hypothesized values of the urban forest (see Relevance), and modes by which it may interact with the city shape (see Background)
2.1.2.1.2. Zoom in to example cities of the situated context, and observe the relative prevalence of these relationships in each city
2.1.2.1.3. Use trends in the relationships seen in each cities to Zoom Out by generalizing features of these relationships which are common to all cities observed
2.1.2.2. Relationship of Interest
2.1.2.2.1. Dependent Variable: City Shape
2.1.2.2.2. Independent variable-of-interest: Distribution of the Urban Forest
2.1.2.2.3. Other relevant variables: topography, national trends in industry growth, national political environment, other features of relevance in situated context
2.1.2.3. By observing/measuring the City Shape and Distribution of the Urban Forest in the three cities in my situated context, as well as the modes by which they might interact, I will generalize features of the relationship between them and the other variables which are being controlled for
2.2. Data & Empirical Techniques
2.2.1. Maps & Aerial Photography
2.2.1.1. Shows morphology of city over time
2.2.1.2. Shows distribution of tree canopy
2.2.1.3. When combined with census data, displays spatial metrics such as population density per area.
2.2.1.4. I anticipate this will be the most difficult data to acquire, but also some of the most pivotal data to my analysis
2.2.2. Census Reports
2.2.2.1. Important for the population dynamic
2.2.2.2. most useful if broken down spatially (e.g. by block group)
2.2.3. Politico-Industrial History
2.2.3.1. What types of policies have characterized each era of this city's history?
2.2.3.2. What industries have characterized each era of this city's history?
2.2.3.3. How have these two things interacted? i.e. what sorts of economic development policies have been in place throughout this city's history, and how have they shaped the relationship between policy and industry?
2.3. 10-12 Pages
3. Background
3.1. Framing Question: How does the distribution of urban amenities interact with the forces shaping cities?
3.2. Trees-as-Urban-Amenity
3.2.1. Public Values
3.2.1.1. Shading/Temperature Reduction: reduces the heat island effect and building cooling costs
3.2.1.2. Stormwater Management: Trees and other plants with root systems control rainwater run-off by holding soils together and uptaking water
3.2.1.3. Local Air Quality: trees uptake atmospheric pollutants through leaf stomata, improving air quality
3.2.1.4. Aesthetics: Increases overall appeal of city, contributing to tourism and economic development
3.2.2. Private Values
3.2.2.1. Shade/Cooling: reduces residential cooling costs and provides shaded outdoor areas
3.2.2.2. Aesthetics: Both as a component of landscaping and as a feature positively correlated with more valuable properties
3.2.2.3. Recreation: Associated with parks and open space, features for children's play
3.2.2.4. Fruit Production: residential fruit trees are not uncommon
3.2.3. These values are often intercorrelated: for example, reducing building cooling costs may also reduce local emissions and improve air quality
3.3. City Shape
3.3.1. Morphology: Where businesses locate, where residential areas develop, where parks and open space are, etc.
3.3.1.1. What amenities are present either as a cause or affect of this morphology?
3.3.1.2. How has this changed over time?
3.3.2. Population Dynamic: A term I borrow from the life sciences. In their context, it refers to trends in the composition of populations of animals with respect to their relative age and size. I use it to describe trends in demographic characteristics of residents through space and time.
3.3.2.1. Where do residents of different age/income/education/race live? Where do they work? How have these trends changed over time?
3.3.2.2. How has the presence or absence of certain amenities correlated with trends in the population dynamic? Are they more likely to be a cause or an effect? Or something in between?
3.3.3. Political and Industrial Dynamics: an extension of the above, but applied to policy, business, and the relationship between them.
3.3.3.1. What industries locate in this city? Where in the city do they locate? Whom do they employ? How has this changed over time?
3.3.3.2. What city policies have been instrumental in defining the "place-ness" of this city? Urban Growth Boundaries? Business Incentives?
3.3.3.3. The presence of economic development in city policy creates a strong relationship between industrial and political trends, and is why I state them together.
3.4. 5-7 Pages
4. Situated Context
4.1. Focus Question: What role has the urban forest played in determining the shape of US cities?
4.2. Portland
4.2.1. Mid-Sized City (500,000)
4.2.2. Considered a testing ground for certain urban policy measures, notably the UGB
4.2.2.1. Not a lot of sprawl
4.2.2.2. Also public transit investment, bike lanes: policies to incentivize non-car transit
4.2.3. Grew up as a logging city throughout the 19th and 20th centuries, but began experiencing growth in other areas in the mid-late 20th century. Began establishing relationships with other cities around the pacific, and created a distinctive culture which separated it from its logging roots
4.2.4. Has a department of urban forestry
4.2.5. Location for past research on the value of urban tree canopy
4.3. Chicago
4.3.1. Big city (2.7 Million)
4.3.2. Major Urban Sprawl
4.3.2.1. Central city populations have been in decline since 1950s
4.3.3. Boomed in the 19th century, first through agricultural trade on the Mississippi River, but then much more through the growth of railroads
4.3.4. Has a department of Urban Forestry
4.3.4.1. Official City Motto: Urbs in Horto (City in a Garden)
4.3.5. Not quite a "would it work in phoenix" example, but still a "would it work in a massive world-city" example
4.4. Ann Arbor
4.4.1. Small City (100,000)
4.4.2. Tree City USA
4.4.2.1. Arbor Day Foundation program which certifies cities that demonstrate tree stewardship
4.4.2.2. Requires a citywide tree board, tree ordinances, and a community forestry program
4.4.3. Uses economic policies to regulate urban trees. Fees charged for business street frontage for tree maintenance, as well as for any removal of canopy
4.5. 3-5 Pages
5. External Validity
5.1. Isolation Principle of the Regression
5.1.1. In theory, the reason for controlling for other independent variables, and for reducing exogenous variation overall, is to isolate the effect of the influence of the urban forest on city shape from the circumstance in which it occurs.
5.1.1.1. This suggests that the whole is equal to the sum of its parts—that is, that the integrity of the generalized relationship will remain once it is extracted from its individual contexts
5.1.1.2. The above statement is likely to be neither entirely true nor entirely false. The degree to which it is true, however, will be important in any prospective applications of the generalized results. I hope to gain a perspective on this through analysis of the most significant factors which change each of my sample cities' relationships with the urban forest.
5.1.2. Applying the results of this regression to any other city would theoretically happen independent of any complicating factors the environment of that city brings with it. These complicating factors would then need to be factored in to complete the picture for any individual city.
5.2. Conflict between internal and external validity
5.2.1. In selecting my three cities, I chose examples which had certain characteristics in common, and other characteristics which varied between them
5.2.2. The more comparable cities are in every way except for the features of my relationship-of-interest, the less error I will encounter in generalizing the relationship due to exogenous variation
5.2.3. However, limiting the variation of cities which I sample also reduces the set of cities to which my generalized results are applicable.
5.2.4. I must therefore strike a balance between controlling for variance in my results (increasing internal validity) and extending their range of applicability (increasing external validity). Because of my limited resources with which to conduct this analysis, I lean toward favoring the internal validity. However, this makes it necessary to acknowledge the limitations of my method.
5.3. Limitations
5.3.1. n = 3
5.3.1.1. As of now, I plan to conduct my analysis on the three cities in my situated context. In theory, this will allow me to "triangulate" features of my relationship-of-interest that I can then begin to generalize.
5.3.1.2. However, it should be noted that this is still a small sample. An n of 3 would never fly if this were a statistical regression. It is, however, necessary for me to reduce the sample size for a qualitative regression, as I must individually compare the data points: I can't just "crunch the numbers" with R or STATA.
5.3.2. Latitude
5.3.2.1. All sampled cities are at similar latitudes and are therefore similarly temperate, although the weather patterns which Portland experiences have definite distinctions from those experienced by Chicago and Ann Arbor.
5.3.2.2. This makes it more difficult to apply my results in arid, tropical, or polar regions, as well as possible implications for applicability to the global south and equatorial regions.
5.3.3. US-Centric
5.3.3.1. All sampled cities are in the United States. This limits the sample to one general politico-industrial environment.
5.3.3.2. Theoretically, this should make the results more applicable to cites which are located within politico-industrial environments more like that of the US.
5.4. 3-5 Pages
6. Results
6.1. A discussion of the role of the urban forest in shaping each individual city
6.1.1. Most important features of each city related to the urban forest
6.1.1.1. e.g. "in Chicago, the following events have displayed the effect of immigrant landing zones on tree canopy..."
6.1.1.2. e.g. "in Portland, the presence of street trees has influenced the site selection process for public housing process in this way..."
6.1.2. I expect to see variable valuation of the urban forest from city to city
6.1.3. However, I expect to be able to explain much of this variance with other factors in the city
6.2. A generalization of the role of the urban forest in shaping cities in general, with respect to their morphology, population dynamic, and politico-industrial dynamic
6.2.1. Given that I can explain the variation between cities, I will attempt to isolate the overall trend of the effects of the urban forest in city development
6.2.2. This is the "zooming out" perspective: how might my results for these three cities apply to cities throughout the rest of the US, throughout cities at similar latitudes around the world, or in cities with very little in common with my situated context?