High-Speed Rail Route and Regional Mobility with a Ras-ter-Based Decision Support System: The Texas Urban Triangle Case ()
1. Introduction
The Texas Urban Triangle (TUT) is comprised of the metropolises of Dallas-Fort Worth, Houston, and San Antonio, and is distinguished among megalopolises because it is not linear but rather triangular. The axis from San Antonio to Dallas is on its way to becoming fully urbanized due to the proximity of the string of cities along Interstate 35. In contrast, on Interstate 45 between Dallas and Houston, and on Interstate 10 between Houston and San Antonio, there are only small villages and towns along these arteries. Further, the urban development between its metropolises is not physically contiguous. The Texas Urban Triangle, with its massive number of inhabitants and area of more than 60,000 square miles, is the economic motor of Texas and hub of the national transportation network operating in a global economy. The Triangle is emerging as a new urban megaregion in its own right, competing with Los Angeles and New York, by virtue of its extensive internal connections and activities.
Accordingly, freight and passenger mobility within and among the Triangle’s metro areas, as well as outward across the continent, are critical to economic and social development, and to the preservation of its natural assets. The initial analysis about the Triangle fringe revealed that over the next 20 years, population in the area will account for over 80 percent of the state’s total [1]. The TUT is projected to account for 8,407,000 of the state’s 10,979,000 new inhabitants, or 77 percent of all of Texas’s growth [1]. The overall findings provide a baseline foundation for policy guidance to decision makers at all levels of government—especially state and federal— and the private sector.
Given that transportation infrastructure shapes and supports growth, $58 billion of the $72 billion identified in Texas transportation infrastructure needed over the next 25 years is in the Texas Urban Triangle [2]. Existing highway-dominated surface transport systems are exceeding design capacity and are increasingly costly to expand and maintain. Accordingly, there is an urgent need for policy and investment decisions that are based on a new and wider set of criteria that account for new conditions and considerations. A new form of decision making based on emerging realities could pave the way for a wider range of options for transportation that are sustainable.
This study addresses sustainable transportation in the Texas Urban Triangle at the regional scale. Its aim is to determine the most suitable corridor for new transport infrastructure by employing a spatial decision support system (SDSS) proposed in this project. The SDSS is being tested through its application to a prototype corridor parallel to Interstate 35 between San Antonio and Austin. The basic research questions asked are spatial in nature, so accordingly the geographic information systems (GIS) are the primary method of data analysis. The overall modeling approach is devoted to answering the following questions: What are the considerations to support sustainable growth? What scale or type of infrastructure is necessary? And how to adequately model the transportation corridors to meet the demands and to sustain the living environment at the same time?
2. Review of the Existing Transportation Decision Support Systems
There are a wide range of decision support systems for transportation investments. Increasing relationship between transportation and land use developed relevant software packages. As a result, a large amount of decision support models are implemented by different organizations. In this section, a few different existing decision support systems are reviewed.
2.1. TransDec2.0
Developed by the Texas Transportation Institute (TTI) under National Cooperative Highway Research Program (NCHRP), TransDec is a multimodal investment model that takes into account many factors not easily measured in traditional benefit-cost assessments of project desirability, such as air quality considerations, gross mobility impacts, community livability factors, and aesthetic considerations [3]. TransDec uses multi-criteria utility analysis methods to assess tradeoffs between transportation modes, planning methods, and priorities set by project evaluators.
2.2. Development of Intercity Passenger Network in Texas (TxDOT Project 0-5930)
This project developed a state-wide network to move people between urban regions by either passenger rail or intercity bus services. For each intercity corridor, a set of criteria was developed to compare the suitability of each corridor against the others. Criteria utilized for this project include the population along each corridor, population density, projected population growth, total employees, number of public or private universities, air passenger travel between corridor airports, vehicular traffic, percent trucks, and average number of corridor flights per day [4]. The outcome of this evaluation will be the recommendation of which corridors are most likely to support an intercity transit system and whether bus or rail is most suitable.
2.3. MicroBENCOST Model
The MicroBENCOST software was developed by TTI researchers in the mid-1990s [5]. It provides a planninglevel economic analysis tool that can be used to analyze a variety of transportation projects. MicroBENCOST is designed to analyze different types of highway corridors. Benefits are calculated for existing and induced traffic, as well as for diverted traffic. Eight different traffic allocation options exist, depending on the traffic year and the nature of the marginal user costs considered.
2.4. UPlan
This is a GIS-based urban growth model that runs in the Windows version of ArcView. The model was designed by the research team to rely on a minimum amount of data, but it allocates urban growth in several land use types for small (parcel-sized) grid cells [6]. It is a scenario-testing model and rule based; i.e., it is not strictly calibrated on historical data and uses no choice or other statistical models. The result can be applied to various urban impact models to forecast soil erosion, local service costs, and other impacts.
2.5. The “ALLOT” Model
This model is an early prototype of the SDSS developed in 1992 in an attempt to provide governmental jurisdictions and private landowners with more economically efficient and environmentally sound land use and development patterns than usually occur [7]. It employed a GIS land suitability analysis model and multi-attribute value method that helped to determine the location of lands suitable for different land uses.
As can be seen, each model has its own emphasis and aims. But the problem stems from their data-intensive nature and the limited windows for user involvements. In addition, it is also unclear that most of the systems do not specify the relationship between transportation corridors and possible environmental changes. They rather concentrate heavily on the economic side. The proposed SDSS differs from the existing decision systems in that it focuses on selected strategic driving forces of growth of the region as a functional unit—transport infrastructure, available land, economic activity, water, energy, and so on—and then identifies corresponding measures of sustainability for key transportation systems and corridors within the TUT. For example, development patterns driven by transportation infrastructure in turn create impacts on surface and groundwater resources in terms of water quantity and quality. Conversely, consideration about water availability and waste assimilative capacity can be used as a driver of infrastructure planning decisions to achieve greater long-term sustainability.
The SDSS provides a composite foundation for policy analysis and support policy making for a comprehensive sustainable regionalism. The SDSS can be modified by users to support location decisions regarding local and state transportation corridors, in addition to metropolitanand regional-scale corridors. Moreover, it can be used to evaluate other types of infrastructure corridors that can be placed in shared rights of way within or alongside transportation corridors. Unlike the previously reviewed models, the SDSS is multi-scalar in addition to multiattribute, and represents an advance in decision support system model development.
The proposed SDSS compiles decision criteria into a land suitability analysis model [8], employing GIS to map strategic social, economic, and environmental characteristics, and overlay them to assess which locations are most and least suitable for regional transportation networks and urban-scale growth. The vastly changed transportation investment decision panorama in Texas and the United States implies a new type of decisionmaking that considers more than just capital costs and environmental constraints. It needs to consider the economic, demographic, social, ecological, infrastructural, and fiscal parameters influencing decisions.
3. Pre-Modeling
3.1. Identify Factors
“Factors” in the SDSS refers to the individual criteria used in the model to assess the most suitable location for placing transportation corridors on the landscape. Utilizing the Delphi panel discussion technique, a set of experts panel was formed and initially selected 83 factors that could be included in the SDSS criteria. They are organized into seven categories: culture; demographics; engineering; environment; hazard; natural resources; and lands. After thorough deliberation, 38 factors appropriate for a transportation corridor were identified, and this study adopts seven of them to examine the modeling process.
Table 1 presents the list of factor selection. Type of roads, Floodplain, and Surface waters are selected to minimize the probability in constructing additional structures to cross any highways or rivers. Slope, Geology, and Soil types are chosen to represent the construction suitability (i.e. earthworks or foundation enhancements). Finally, Population density is used to minimize any conflicts in relocating people and goods.