Kamyoung Kim

Enhancing Classic Coverage Location Models

An important area of regional science has long been location analysis and modeling. Its significance continues, now more formally known as location science, and has evolved because of the need to address complex facility siting problems and issues. This article focuses on classic coverage location problems, and how advances along theoretical and methodological fronts have enabled such problems to be viewed in new ways. Specifically, notions of implicit and explicit coverage, along with geographic information systems (GIS), provide the capacity to reconceptualize as well as better model intended planning goals and objectives. This article reviews covering problems and presents a comparative framework for both linkage and assessment. This research is significant because evolving models enable issues of frame independence, and the modifiable area unit problem, to be addressed, making planning and analysis more reliable and valuable.

Delimitation of Functional Regions Using a p-Regions Problem Approach

Various spatial data analyses have been used for the identification of functional regions. Functional regions are identified by grouping many areal units into fewer clusters to classify the areal units in terms of similar properties, as well as to constrain the spatial contiguity of the areal units in each cluster. This article proposes a spatial optimization model, called the p-functional regions problem, to solve a regionalization problem by considering geographic flows. The magnitude of geographic flows, such as journey-to-work, is widely considered a good indicator of functional relationships between areas so that regionalization models incorporating various criteria, such as the maximum intraregion flows or the total inflows from other units, may be used to identify the p regions. We also propose an analytical target reduction approach to enhance the model tractability in generating optimal solutions to large problems and to demonstrate the effectiveness of the optimization model using journey-to-work data from Seoul (South Korea) and South Carolina (the United States).

Pedagogical Potential of a Web-Based GIS Application for Migration Data: A Preliminary Investigation in the Context of South Korea

This article examines the pedagogical potential of a Web-based GIS application, Population Migration Web Service (PMWS), in which students can examine population geography in an interactive and exploratory manner. This article introduces PMWS, a tailored, unique Internet GIS application that provides functions for visualizing spatial interaction data. The easy-to-use interface of PMWS enables users to interactively and intuitively explore migration data in the form of flow maps and to use local data. The results of the usability survey indicated that pre-service teachers (n = 33) believe that PMWS represents an alternative GIS tool that overcomes the obstacles of desktop GIS in secondary education.

Developing a Flow Mapping Module in a GIS Environment

Abstract The serious drawback of traditional flow mapping commonly representing geographical movement with straight lines of varying widths is a visual cluttering problem. To resolve these issues, several alternatives reducing the problem or enhancing pattern detection have been suggested. Despite being successful in some aspects, they have their shortcomings such as partial representation or misrepresentation of geographical movement and difficulty in interpreting visualized results. In addition, flow mapping functionality has yet to be fully implemented in modern geographic information systems (GIS) applications. Given these problems, this paper proposes the new designed symbols for improving the traditional flow mapping and develops a flow mapping module implementing them within a commercial GIS software package. Application results demonstrated that the developed module can represent gross, net, two-way and location-specific flows from a single dataset efficiently and can make better flow maps with the alternative symbols. The alternative symbols successfully reduced the visual overlap of symbols and improved the estimation of values.

Spatial optimization for regionalization problems with spatial interaction: a heuristic approach

Spatial optimization techniques are commonly used for regionalization problems, often represented as p-regions problems. Although various spatial optimization approaches have been proposed for finding exact solutions to p-regions problems, these approaches are not practical when applied to large-size problems. Alternatively, various heuristics provide effective ways to find near-optimal solutions for p-regions problem. However, most heuristic approaches are specifically designed for particular geographic settings. This paper proposes a new heuristic approach named Automated Zoning Procedure-Center Interchange (AZP-CI) to solve the p-functional regions problem (PFRP), which constructs regions by combining small areas that share common characteristics with predefined functional centers and have tight connections among themselves through spatial interaction. The AZP-CI consists of two subprocesses. First, the dissolving/splitting process enhances diversification and thereby produces an extensive exploration of the solution space. Second, the standard AZP locally improves the objective value. The AZP-CI was tested using randomly simulated datasets and two empirical datasets with different sizes. These evaluations indicate that AZP-CI outperforms two established heuristic algorithms: the AZP and simulated annealing, in terms of both solution quality and consistency of producing reliable solutions regardless of initial conditions. It is also noted that AZP-CI, as a general heuristic method, can be easily extended to other regionalization problems. Furthermore, the AZP-CI could be a more scalable algorithm to solve computational intensive spatial optimization problems when it is combined with cyberinfrastructure.

The modifiable areal unit problem in hedonic house-price models

When geographically aggregated data are included in hedonic models, the resulting coefficients are biased by the spatial scale and spatial configuration of variable measurement. We explore the effects of this modifiable areal unit problem (MAUP) within the context of hedonic price models with an individual-level dependent variable. Specifically, we developed standard and spatial hedonic regression models in order to examine the effects of the MAUP on model fit and coefficient estimates. Our empirical analysis documents several significant scale and zoning effects in the hedonic modeling framework. First, neighborhood characteristics are clearly important in efforts to improve model fit—and they are more significant contributors in the standard model than in the spatial hedonic model. For aggregation scale, the model fit change of the standard model is relatively large, whereas the change is more modest for spatial models. The patterns of change in model fit for standard and spatial hedonic models clearly diverge from one another, implying the existence of a scale level showing a maximum functional range of the submarket on which scale dependencies are expected to have an impact. Regarding the zoning effect, the model fits for both standard and spatial hedonic models vary according to the submarket systems.

Critical Review of Gentrification in Urban Spatial Structure and Exploration of the Future Research Direction

In terms of dynamics of urban space, gentrification is very important research theme in company with suburbanization. The purpose of this paper is to critically review the discussion of gentrification, and then to suggest the direction for the future research. In order to do it, the concepts of gentrification, researches on gentrification in production-side and supply-side explanations, and debates between the two sides were critically reviewed. In addition, topics which have been the focus of attention such as globalization and gentrification worldwide, displacement and social mix, various spatiality of gentrification, and new-build gentrification were reviewed, and based on them, future research direction is suggested in terms of understanding dynamics of urban space, comprehensive consideration of various factors, consideration of various kinds of scales, and application to domestic urban phenomena.

A Robust Heuristic Approach for Regionalization Problems

Spatial optimization is commonly used for political (or electoral) districting problems. Although an exact approach can be used, heuristic methods have often been used due to the complexity of political districting problems and their multi-criteria nature. However, heuristic approaches may not produce consistent results and may vary in solution quality. This paper focuses on the development of a robust heuristic method for political districting problems, specifically incorporating existing physical barriers in combination with population, contiguity, and compactness of the resulting districts. An application for legislative election districts in Seoul, South Korea shows that the proposed method produces prominent and robust results compared to generic meta-heuristic approaches.