Using Large-Scale Urban Models to Predict Neighborhood Scale Impacts: An Application of the Los Angeles-Shanghai Urban Modeling Project

Abstract

A team of researchers led by Richard Arnott, Alex Anas, and Richard Peiser is building a next generation land use_transportation_ecology model for projecting urban growth in the Los Angeles and Shanghai regions. Other team members include Dan McMillen, Joan Walker, Sofia Dermisi, Siqi Zhang, Guoping Huang, and Haixiao Pan. With initial funding from the Real Estate Academic Initiative at Harvard University, the team is working closely with the two regional planning agencies n Southern California Association of Governments (SCAG) in Southern California, and the Shanghai urban Planning and Design Research institute (SUPDRI) in Shanghai. The Los Angeles n Shanghai Urban modeling Project is creating a GISnbased data platform for investigating a series of questions about the impact of future urban growth and change in the two metropolitan regions. The primary objective is to develop better models for forecasting land use and density changes over time. These projections are fundamental for assessing a variety of impacts such as commuting time, economic output, environmental quality, and social indicators for quality_of_life. Our goals are threefold: 1) to develop models to understand urban growth and change _ to develop models to predict urban growth, densities, land use patterns, and who will live and work where; 2) to understand how the complex interactions of congestion, environmental quality, crime and other social indicators impact real estate values and in turn how real estate values impact housing affordability, residential location patterns, employment, and shopping patterns; 3) to compare the impacts of different policies affecting urban development in L.A. and Shanghai and to evaluate the impacts of future growth patterns from the perspective of transportation, urban infrastructure needs, environmental impact, crime, poverty, and education. The project is in its second year and the models are still being developed. In this paper, I will describe the theoretical approach to the model and discuss how the model will be used to project development at the urban design scale. This is new for large scale models, which typically treat land use, transportation, demographic, and other data at much larger zonal scales. Unlike other large_scale planning models such as those developed by Putnam, de la Barra, Waddell, and others, the LA_Shanghai model is based on micro economic foundations with households maximizing utility and firms maximizing profits. The model takes as given the growth process and the transport network, and forecasts wage, land rent, land value, floor space rent, and floor space value surfaces over time for the cities. In future phases of the model, some variables that are exogenous in the initial phase (e.g. population or utility, the severity of land use controls, crime levels) will be made endogenous, and the econometric estimation will be modified accordingly. The present paper focuses on developing a procedure for consistently disaggregating the real estate price and development predictions from the large_scale modelis zonal aggregation down to small neighborhoods and parcels. This will make the results compatible with the level of resolution at which real estate market data exists and is used. The paper explores a number of issues for integrating the large scale_model into small_area urban design_scale neighborhoods and parcels. These include determining where real estate values will rise and fall; how much local congestion and accessibility will change; where gentrification and redevelopment will happen; how this disaggregation will serve as a bridge between SCAG and SUPDRI, and the urban modeling team; and micro_level real estate analysis that real estate developers must do. The approach uses GIS parcel data (4 million parcels in Los Angeles County alone) to enable urban designers, local planners and developers to visualize land use change at the street level. The results are important because they help planners, developers, neighborhood groups, and other stakeholders envision the impacts of various public policies affecting the built environment in their municipality in a format that generates individual buildings and streetscapes. This tool will be valuable to the stakeholders in making more informed urban planning decisions.