Varameth Vichiensan

DISCRETE CHOICE MODEL WITH STRUCTURALIZED SPATIAL EFFECTS FOR LOCATION ANALYSIS

The discrete choice modeling paradigm and in particular the logit model are research topics that have been continuously developed and refined for years in the field of transportation applications. Modeling locational choices, however, differ from modeling transportation choices in that geographically referenced data are used and thereby give specifically spatial choices. A discrete choice model with a systematic specification of the spatial influences in the choice process is presented. The utility function of the model is specified with autoregressive expressions for the deterministic and error components, and the model is evaluated with reference to three alternative models: the standard logit model, a logit model with an autoregressive deterministic term, and the mixed logit model with autoregressive error terms. Two applications are presented: one with simulated data and another with real data for the analysis of location choice in Sendai, Japan. The proposed model shows an improved performance over the three reference models.

Nonstationary Spatial Interpolation Method for Urban Model Development

In some situations in urban modeling practice, data cannot be preserved at the highest possible level of resolution. For example, when data from different sources are collated, the areal partitioning systems may not be compatible with each other. In other cases, related but separated models (e.g., urban transportation-land use and environmental models) may have been designed to operate at different spatial scales, posing a challenge to any efforts to link them. In these and similar situations, a method for interpolating data is required to produce compatible zoning systems or data at a desired level of resolution. A nonstationary (location-specific) spatial interpolation method, which has various potential applications in transportation as well as urban modeling, is proposed. The method combines the concept of location-specific parameters of a geographically weighted regression model and the concept of variogram function of kriging used to model spatial autocorrelation. Two case studies are presented to i...

Qualitative and Quantitative Comparisons of Agent-Based and Cell-Based Synthesis Estimation Methods of Base-Year Data for Land-Use Microsimulations

Land-use microsimulation is becoming an indispensable function in a planning support system for sustainable urban development because it provides the detailed information necessary for decision making on emerging issues at the household or firm level. In land-use microsimulations, there are two approaches for estimating base-year micro-data: cell-based population synthesis, which generally uses the iterative proportional fitting method, and agent-based methods. This chapter compares these two methods qualitatively and quantitatively. The qualitative comparison shows that neither one is superior in every aspect. The cell-based method is preferred when the microsimulation deals with data sufficiently simple, while the agent-based method is preferred when accurate and/or numerous micro-data attributes are demanded. Similarly, the quantitative comparison based on a goodness-of-fit evaluation does not show a single superior method for all applications. These findings suggest a way for selecting a better method based on the conditions of the microsimulation model and the purpose of its application.

Modifiable Attribute Cell Problem and Solution Method for Population Synthesis in Land Use Microsimulation

Land use microsimulation requires the preparation of a set of microdata for the base year. Most existing procedures used for the synthesis of population data are based on the iterative proportional fitting method, in which the number of individuals in each cell of the cross-classification table is estimated. Such a procedure is referred to as the cell-based approach in this study. The approach is based on predefined categories of individuals. Originally, however, these individuals have continuous attributes. Therefore, a different type of categorization would yield a different classification table, which would change the end results of the analysis. In this paper, this phenomenon is referred to as the modifiable attribute cell problem (MACP). It is similar to the modifiable area unit problem that arises when spatial data are aggregated into zones. This paper addresses MACP and proposes a method to determine the best combination of the categories. The solution of MACP is considered to be the minimization of the number of cells in a table with respect to the key output variable that has been defined and used as an evaluation criterion. Because of the computational difficulty resulting from the combination explosion, symbiotic evolution, which is a kind of genetic algorithm, is used. Finally, a case study is presented for the Sapporo metropolitan area of Japan.

Urban Flooding and Adaptation to Climate Change in Sukhumvit Area, Bangkok, Thailand

Flooding in urban areas is an inevitable problem for many cities in the world. In Thailand, Bangkok has serious problems related to urban flooding. The situation was highlighted in May 2017, when residences experienced ankle to knee-deep flood water on the streets. Daily activities in parts of the city were nearly paralyzed and heavy traffic jams occurred due to stagnant water on the streets. The study has depended on a combined approach of physically based modeling and GIS. The urban drainage is structured by iRIC software for the basis of two networks, one simulating the two-dimension free-surface flow over the streets and one for the pumping/canal/pipe system. The interaction between street and pumping/canal/pipe system is modeled in a simple way. In 2017, ADAP-T project carried out a pilot study about urban flooding and adaptation modeling for Sukhumvit area, Bangkok Metropolitan. This study is performed as an extension and improvement of pilot study in terms of analyzing drainage system on effect of flood hazard, vulnerability, risk map and adaptation under the issue of climate change in Sukhumvit area, Bangkok, together with suggestion of alleviation scenarios to relieve flood problems.

Transport and Land Use Instruments for A Better Environment

This chapter considers the policy instruments which cities can use to improve the local and global environment. These instruments include land use planning, new infrastructure, management and regulation, information provision and pricing and fiscal instruments.