11.522: UIS Research Seminar (Fall 2014) - Discussion notes

Monday, October 6, 2014, 7-9 PM

Buenos Aires Metropolitan Region Urban Growth Model

Discussion Leader: Gabriel Lanfranchi

Introduction:

In order to plan the provision of basic services like water and sanitation, to estimate the need of housing or to define the construction of new roads the capability of predicting urban growth is an important skill that every city should develop. If we try to do this exercise in metropolitan cities the task gets much more complex since the variables that can influence the results are multiple: land use, access to public transportation, existence of roads, access to basic services, land cost, and population growth rate are some of the typical factors considered to evaluate different scenarios.
The purpose of this discussion is to identify different types of urban growth models that could be develop for the Buenos Aires Metropolitan Region. This includes these sub-topics:

    1. gain a deeper understanding of the literature surrounding urban growth models
    2. understand the growth trends of Buenos Aires Metro Region and the “Urban DNA” method, developed by the discussion leader for his Master in Urban economics
    3. Try to explore other possible outcomes of the model related to density, poverty and access to basic services.

Background: Urban growth trends & water and sanitation expansion policy

Buenos Aires Metropolitan Region has around 15 million inhabitants and it has been increasing it’s population about 1.5 million inhabitants every ten years during the last 40 to 50 years. This growth in population wasn’t followed by an equal growth of the water and sanitation network. For that reason at the beginning of the 21st century the region was experiencing a serious deficit in the access to these services. In 2006 the national government decided to cancel the concession of the service to the private company in charge of it.  A new public company, called AySA, was established with the scope to achieve Universal service by 2020. Since then big efforts have been made and the company is going to experience a 100% growth in the upcoming years. Since the company was always playing 'catch up' by providing services within the urban growth frontier, very rudimentary population growth models were used. This new scenario will require better anticipation of urban growth in order to improve the planning of their investments in the region. 

Objective

My main objective for this course is to build a model capable to predict different scenarios of urban growth for the company at a census tract scale. To achieve this goal I will make use of a helpful tool I developed for my Urban Economics thesis called the “Urban DNA”. This method was built to assist researchers and policy makers to understand where demographic and urban land growth is taking place. It provides a systematized approach to read, analyze and represent metropolitan areas considering three basic indicators: Density (D), Needs – poverty -  (N), and Access to infrastructure services (A). A 3D indicator is constructed to overlap these variables creating a new way to understand cities, reaching to classify them according to urban typologies. This experiment was run for the 31 biggest cities in Argentina to promote integral planning in metropolitan areas.

Available Exposure Data and outcomes

I will collect data from 2001 and 2010 national census, satellite photos information from 2000 and 2010, land use data available, and basic geo referenced infrastructure information like roads, highways and railways. As an outcome I expect to be able to offer possible urban growth scenarios for 2030, indicating population, density and new urban area required.

Models review

To initiate this research I’ll start by studying two different approaches:

  1. The SLEUTH urban growth model (cellular automaton model), developed by Keith C. Clarke (now a Professor at UCSB).

“SLEUTH is an acronym for the imput layers that model uses in gridded map form: slope, Land use, Exclusion, Urban Extent, Transportation and Hillshade. The basic growth procedure in SLEUTH is a cellular automaton, in which urban expansion is modeled in a special two-dimensional grid. Diffusion, breed, spread, slope and road coefficients control the behavior that can take place: spontaneous, diffusive, organic and road-influenced. Self-modification of the rules changes the control parameters when modeled growth rates are exceeded, so that the model’s behavior includes feedback”. (Clarke et al., 1997)

  1. What if? software developed by Richard E. Klosterman, Ph.D., President and CEO of the company and retired urban planning Professor.

A free version of this software, together with shapefile-formatted GIS basemaps, can be used to project the following variables for enumeration districts such as census tracts and block groups, and for user-defined areas such as political jurisdictions, schools districts, and traffic analysis zones (TAZs):

  1. Residential population
  2. Group quarter population
  3. Number of households
  4. Number of housing units
  5. Employment by sector and by place of work
  6. The projected land use, population, and employment for each sub-area and each projection year can be viewed in easy-to-understand maps and reports.

Key Readings:

  1. Silva, E., Clarke, K.C., 2002. "Calibration of the SLEUTH urban growth model for Lisbon and Porto, Portugal," Comput. Environ. Urban 26, 525–552. http://ncgia.ucsb.edu/projects/gig/v2/About/references/Lisbon_Portugal/silva_2002.pdf
  2. Richard E. Klosterman. (2001) "A New Tool for a New Planning: The What if?TM Planning Support System," in Planning Support Systems: Integrating Geographic Information Systems, Models and Visualization Tools. (Edited with Richard K. Brail), 2001. (Pages. 85 – 100)
    http://www.spatial.redlands.edu/sds/downloads/A%20New%20Tool%20for%20a%20New%20Planning.pdf

Optional Readings: 

  1. Angel S, Parent J,  Civco, Daniel L. and Blei A.M. (2010)  Making Room for a Planet of Cities, Policy Focus Report • Lincoln Institute of Land Policy. (Called lincoln_Planet_of_Cities.pdf in class locker and on Stellar.)
  2. Goytia,C.,  Lanfranchi,G. (2009) “Informal Neighborhoods in Buenos Aires Metropolitan Region: Understanding the Effects of land Regulation on the Welfare of the Poor,” Chapter 7 in Lall, S. Freire,M., Yuen B., Rajack R., and Heullin J.J, (eds.) Urban Land Markets, Improving Land Management for Successful Urbanization. Springer. (Called lanfranchi_175825_1_En_7_Chapter.pdf in class locker and on Stellar.)
  3. Alexandra D. Syphard, Keith C. Clarke, Janet Franklin (2005). "Using a cellular automaton model to forecast the effects of urban growth on habitat pattern in southern California," Ecological Complexity, 2, pp 185-203.
    http://www.geog.ucsb.edu/~kclarke/Papers/SyphardClarkeFranklin_EcComplexity.pdf

Discussion questions:

1) What sort of outcome should be provided to the water company in order to facilitate their planning operations?
2) Which of these models are the best choice to achieve the goals?
3) Are there other models that should be tested? 


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