AMIS: Development of a GIS/Multicriteria Corridor Planning Methodology
A foundational assumption was that a well designed decision support methodology for participants in such a process should (i) assist them determine criteria of significance, (ii) assess the importance of each criterion and (iii) allow them to quantify tradeoffs between each pair of criteria. It was not intended to form a rigid a priori framework to be imposed on participants. A formal system with such properties is termed a Decision Support System or DSS [1]. A DSS where the decision criteria have spatial dimensions is termed a Spatial Decision Support System, or SDSS [2]. A SDSS was developed based on the concept of the least cost path. However, the notion of cost, or its spatial equivalent of impedance, was treated as a complex, multidimensional and not necessarily monetarily-based variable. This impedance variable was composed of the sum of a number of individual impedance elements. Each of these elements consisted of an attribute with a location. The GIS was used to sum the value of all impedance elements for every cell in the corridor study area. The result was a continuous geographic surface that summarized scores pertaining to routing preferences and obstacles. This surface could be queried to provide combinatorial scoring useful for exploratory corridor testing.
A rigorous spatial analytic framework, in the form of a raster-based GIS, Arc/View, was conjoined with a robust rational choice decision methodology, the Analytic Hierarchy Process or AHP [3] to create AMIS. AMIS combines system priorities, such as economic development and connectivity improvement, with varied but specific on-the-ground features, such as wetlands, schools, median incomes or areas where endangered species are located. Both the system priorities and features can be user-specified. Input is in both written and electronic data format, while the output is displayed on standard GIS software.
One important goal of formalizing the selection criteria was to increase stakeholder satisfaction. Decision theoretic literature contends that policy decisions are often based on invisible or surrogate criteria – that is, participants may not be offered a framework that permits articulation of their true goals, or in other cases, support or resistance for a project is couched in tactical terms. For example, specific locational choices may be protested although opposition is in reality formed in principle to the development’s goals rather than its specific form. In many cases this has led SHA’s to regard public input as problematic and negative. Predicated on the belief that broad stakeholder involvement is a critical and a highly desirable component of any transportation modeling system, articulating and clarifiying individual values and views is, therefore, of fundamental importance. Yet, in the absence of a formal, analytical framework for capturing and incorporating these values, competing and often fractious views render goal-setting intractable, or result in compromises which are viewed as unsatisfactory even by those who contributed to them. One of the major reasons for this outcome is that the weighting system is often not rendered explicitly, and participants are left wondering whose views have more weight, and why [4]. It is therefore helpful to structure the problem in such a way that participants feel they are making a genuine contribution to goal-setting, and that their individual voices all count [5]. Further, iterative adjustment of model parameters based on expert opinion usually produces more satisfactory outcomes. Previous experience with the application of multicriteria techniques to large-scale, complex and contentious public policy and environmental management problems supports this view [8].
AMIS was therefore built using iterative process that incorporated input from a variety of federal and local government SHA representatives, including Engineers, Planners and Environmental specialists. This process took place over a period of approximately six months, with sets of meetings being held to move through the design stages. Facilitation methodologies were employed at each of these meetings to maximize stakeholder input [9].
The multicriteria priority model was structured around these three data layers comprised of surface data elements (originally 69 of these), affinity groupings of the 69 data elements (5 total) and FHWA Purpose & Need categories (8 total). First the participants were asked to specify an exclusive membership for each of the 69 elements in a category called an affinity grouping. This required definition of five appropriate classes (see Table 1). Two classes of elements were identified. The first consisted of elements considered critical (a), and the second class of less important elements (b). Then the individual elements were each assigned a raw impedance score, a, from 1 to 10 points, or exactly 100 points. This discontinuous scale was chosen arbitrarily, with 1 point representing low impedance (high willingness to develop) and 10 points a high impedance (low willingness to develop). 100 point a values were reserved for “undevelopable” factors. Arithmetic mean impedance scores were then calculated for each element (see Table 2). The research team facilitated this process: however, the participants assumed full responsibility for defining and naming the affinity groupings, assigning elemental membership and classifying and weighting each element.
Originally it was planned to use a classical AHP hierarchical framework. However, methodological limitations forced a reevaluation. First, 69 data elements were considered to be too many to be effectively handled using classic AHP even with multiple hierarchical levels. Second, the requisite assumption that the preference differentials between elements at the same level of the hierarchy approximated one order of magnitude was not tenable [3,6,7]. In addition, at the second meeting, one participant suggested that 8 Federal Highway Administration Purpose and Need (FHWA P/N) criteria for road construction be taken into account explicitly [10] (Table 3). This suggestion was greeted with such strong consensus that the research team felt it should be addressed, although incorporating the FHWA P/N’s into the methodology required a substantial revision to the proposed procedure. A hybrid AHP process was developed in which affinity groupings were combined with the P/N’s and inserted into the second level of the hierarchy. Connecting the P/N’s to individual elements was then accomplished by using the P/N’s to weight the affinity groupings. This was achieved by performing a full set of pairwise comparisons between the five affinity groupings for each of the 8 Federal Highway Authority Purpose and Need (FHWA P/N) criteria specified above. The logistics of this procedure were somewhat lengthier than had originally been planned, nevertheless, the participants were expeditious with their judgments and the meetings concluded in a timely manner. Priority setting for each of the affinity groupings were then averaged to scale the raw elemental impedance scores. This produced a unique impedance score for each element that represents a combination of its individual raw impedance and the priority of its affinity grouping. This affinity group priority was determined both by pairwise comparison among other affinity groups within single FHWA P/N and also by the relative priority of the P/N’s deemed applicable to this connector.