Jeong Hyun Rho

Integrated Urban Systems Modeling: Theory and Applications

I Urban Form, Functions and Structure.- 1 Urban Systems and Systems Analysis.- 1.1 Why Urban Areas?.- 1.2 Measuring Exports from Urban Areas.- 1.3 Review on Urban Systems Models.- 1.3.1 Location Theory and Spatial Economies.- 1.3.2 Models of Urban Rents.- 1.3.3 Models of Regional Economics.- 1.3.4 Transportation Models.- 1.4 Urban Systems and Mathematical Programming.- 2 Determinants of Urban Structure.- 2.1 Suburbanization Trends.- 2.2 Intensive Use of Urban Land.- 2.3 The Role of Congestion in Urban Form and Structure.- 2.4 Concluding Remarks.- II Linear Programming Models and Applications.- 3 Integrated Urban Systems Model I.- 3.1 Introduction.- 3.2 Model Formulation: Postulates.- 3.2.1 Export Requirements of Urban Goods.- 3.2.2 Cost Minimizing Production Function.- 3.2.3 Leontief Fixed Coefficient Production Function.- 3.2 4 Commodity Flow System.- 3.3 Model.- 3.3.1 Exogenous variables.- 3.3.2 Endogenous variables.- 3.4 A Numerical Calculation.- 3.4.1 Input Data.- 3.5 Concluding Remarks.- 4 An Application: Zoning for a Metropolis.- 4.1 Introduction.- 4.2 Model Solution for a Metropolis.- 4.3 Formulating a Zoning Map: An Example.- 4.4 Concluding Remarks.- III Nonlinear Programming Models And Applications.- 5 Integrated Urban Systems Model II.- 5.1 Introduction.- 5.2 Postulates.- 5.2.1 Interzonal Passenger and Commodity Flow.- 5.2.2 User Equilibrium Route and Mode Choice.- 5.3 The Model.- 5.3.1 Exogenous Variables.- 5.3.2 Endogenous Variables.- 5.3.3 Model Development.- 5.3.4 Economic Interpretation of Optimality Conditions.- 5.4 Concluding Remarks.- 6 Solution Algorithms.- 6.1 Introduction.- 6.2 Solution Techniques for Network Equilibrium Model.- 6.3 Alternative Solution Techniques.- 6.3.1 Wilsons Iterative Balancing Method.- 6.3.2 Powells Hybrid Numerical Method.- 6.3.3 Comparisons of the Two Methods.- 6.4 An Alternative Solution Algorithm.- 6.4.1 Solution Algorithm: An Alternative.- 6.5 A Numerical Example.- 6.6 Concluding Remarks.- 7 Model Application to the Chicago Area: Existing Urban Form VS. Model Estimates.- 7.1 Introduction.- 7.2 Application to the Chicago Region: Data.- 7.2.1 Zone and Transportation System.- 7.2.2 Zone System.- 7.2.3 Highway Network.- 7.2.4 Export Zones and Export Handling Cost.- 7.2.5 Land Availability.- 7.3 Transportation Cost Functions.- 7.4 Nonsurvey Input-Output Method.- 7.4.1 Updating Tables.- 7.4.2 Removal of Imports.- 7.4.3 Conversion to Normalized Coefficients.- 7.4.4 Adjustment for Regional Trade Patterns.- 7.4.5 Commodity Aggregation.- 7.4.6 Calculating the Direct Requirement Table.- 7.5 Total Outputs and Exports.- 7.5.1 Total Outputs.- 7.5.2 Total Exports.- 7.6 Land/Capital Input Coefficients and Parameters.- 7.6.1 Land Input Coefficients.- 7.6.2 Capital Input Coefficients.- 7.7 Other Input Parameters.- 7.7.1 Agricultural Land Rent and Capital Rent.- 7.7.2 Trip Generation Factors.- 7.7.3 Auto Occupancy Ratio and Truck Loading Factor.- 7.8 Application to the Chicago Region: Model Estimates and Evaluation.- 7.8.1 Analysis of Convergence.- 7.8.2 Evaluation of the Model Estimates.- 7.9 Concluding Remarks.- 8 Impact Analysis of Network Changes on Urban Form and Structure.- 8.1 Introduction.- 8.2 Fluctuating Lake Levels and Their Transportation Implications.- 8.3 Long-Run Effects of Closing a Major Arterial Street.- 8.4 Concluding Remarks.- IV Future Directions for Integrated Urban Systems Modeling.- 9 Modeling Public-Private Interaction: Bilevel Programming Approach.- 9.1 Introduction.- 9.2 Bilevel Programming Problem.- 9.3 Bilevel Programming Models for Public-Private Interaction.- 9.4 Solution Algorithms: Review and Evaluation.- 9.4.1 Extreme Point Search Method.- 9.4.2 Kuhn-Tucker Approach.- 9.4.3 Descent Method.- 9.5 An Alternative Solution Algorithm.- 9.6 Numerical Analysis.- 9.6.1 Example 1.- 9.6.2 Example 2.- 9.7 Further Research Direction.- 10 Urban Systems Modeling: Retrospects and Prospects.- 10.1 Urban Systems Models Revisited.- 10.2 Urban Systems Modeling: Future Prospects.- 10.2.1 Changes in Urban Lifestyles.- 10.2.2 Subjects for Further Study.- 10.2.3 Emerging New Tools for Urban Systems Modeling.- A Sample Calculation for Example 1.- Author Index.

Modeling investment priorities for national road improvements: A case study of Korea

The paper addresses specific problems associated with formulating investment priorities for national road improvements in Korea. More specifically, the objectives of the paper are (1) to present a model for formulating investment priorities for road improvements that may be useful to developing countries, (2) to test the model with simplified data for deriving investment priorities for Koreas road improvements, and (3) to learn lessons that can be applicable to other developing countries with particular respect to recommending investment priorities for road improvements. The study results are useful for planners, in developing countries, and also for evaluation analysts in funding institutions who are confronted with evaluating investment priorities for deteriorating road conditions.

Impact Analysis of Network Changes on Urban Form and Structure

The model presented in Chapter 5 describes an urban system in which a transportation network model is linked with an integrated land use and input-output model.1 The major objective of the exercise reported in this chapter is to trace the impacts of some exogenously imposed changes in the transportation network on production levels, location, and their associated impacts on journey-to-work patterns and residential location. Thus, the integrated model provides a link between the transportation system and land use patterns through the workings of the production system.

Urban Systems Modeling: Retrospects and Prospects

Some urban systems models introduced in Chapter 1 have been quite widely applied throughout the world. Potential use of such models has been well described by Batty (1979) [14] and a few of them have been operationalized (Oppenheim 1980; Foot 1981) [121] [55]. Urban systems, however, are complex. Thus, urban systems models cannot produce useful recommendations to decision makers unless the models are founded on an understanding of the structures and behavior of the organizations involved in decision making that affect the functions and forms of urban areas.

An Application: Zoning for a Metropolis

Since the adoption of a zoning ordinance by the City of New York in 1916, zoning ordinances to control local land uses have been widely accepted by most U.S. municipalities. Zoning is probably one of the most powerful public controls in a free-enterprise economic system. In fact, zoning is only one of several types of land use controls based on police power.1

Integrated Urban Systems Model II

Most cities have been built incrementally. As urban population levels and socio-economic activities have changed, urban land uses have also been altered. While it is quite reasonable to assume that urban forms and structure are the results of urban dwellers’ economic behavior, particularly of their cost minimizing behavior, there are still many factors in urban forms and structure that cannot be solely explained by the cost minimization criterion.1

Model Application to the Chicago Area: Existing Urban Form vs. Model Estimates

In this chapter,1 the integrated urban activity model introduced in Chapter 5 is applied to the Chicago region. The region includes the Chicago-Kenosha-Gary Standard Consolidated Statistical Area (SCSA), except for the Kenosha Standard Metropolitan Statistical Area (SMSA).

Urban Systems and Systems Analysis

Historically, urban areas have been established due to different causes, such as economic, military, religious, or governmental activities. Whatever activity may have been the predominant reason for its origin, an urban area today needs to export goods and services to other areas in order to sustain its economic growth. Today’s metropolitan areas, however, export products from both manufacturing and service industries to the rest of the world.

Determinants of Urban Structure

Historically, the decentralization of residences and employment around the centers of metropolitan areas is one of the major characteristics of cities in the U.S. and many other countries.1 This suburbanization trend has proceeded especially far and fast since World War II in U.S. metropolitan areas. According to Mills and Hamilton (1984)[107], about sixty percent of the population in metropolitan areas in the U.S. lived in the central city in the 1950s. By 1980, the figure was reversed; about sixty percent of the U.S. metropolitan population lived in suburban areas. Although employment is less suburbanized than population, it also has become much more subur-banized during the postwar period. About seventy percent of jobs in the metropolitan areas were in central cities in 1950. By 1980, the number of employees was almost equal in U.S. central cities and suburban areas.

Modeling Public-Private Interaction: Bilevel Programming Approach

As mentioned in Chapter 1, the usual view in a mixed economy is that some goods and services are produced privately and some, such as transportation, are produced publicly. Most spatial development planning models miss the essential normative issue in a mixed economic system — the interaction between the public and private sectors. 1