Kevin M. Curtin

A new method for determining the population with walking access to transit

The use of geographic information systems in determining transit service areas has not progressed far beyond simple buffering operations even though there is widespread capability to analyze network walking distances in conjunction with demographic, cadastral, and land-use data sets. This article presents a method for determining the population with walking access to bus stop locations using the spatial and aspatial attributes of parcels and the network distances from parcels to bus stop locations. This parcel-network method avoids the well-known and unrealistic assumptions associated with the existing methods and reduces overestimation of the population with access to transit, resulting in improved spatial precision and superior inputs to transit service decision-making processes. Comparisons of the parcel-network method, the buffer method, and the network-ratio method are made in a study area within the Dallas metropolitan area. The novel integration of cadastral data with network analysis in our method holds promise for research in many areas of geographic information science.

Network Analysis in Geographic Information Science: Review, Assessment, and Projections

Network data structures were one of the earliest representations in geographic information systems (GIS), and network analysis remains one of the most significant and persistent research and application areas in geographic information science (GIScience). Network analysis has a strong theoretical basis in the mathematical disciplines of graph theory and topology, and it is the topological relationships inherent in networks that led to revolutionary advances in GIS data structures. Networks can represent an alternative datum for geo-location in the context of linear referencing and support a set of tools for graphical display known as dynamic segmentation. Many network location problems are among the most difficult to solve in terms of their combinatorial complexity and, therefore, provide both a challenge and an opportunity for GIScience researchers. Because elements of network analysis appear in a wide range of academic disciplines—from physics, to sociology, to neurobiology—there are ample opportunities for interdisciplinary investigations of emerging research topics.

Drugs, Violence, and Development in Colombia: A Department-Level Analysis

Observers say that drug production fuels violence in Colombia, but does coca production explain different levels of violence? This article examines the relationship between coca production and guerrilla violence by reviewing national-level data over time and studying Colombia by department, exploring the interactions among guerrilla violence, exports, development, and displacement. It uses historical analysis, cartographic visualization, and analysis of the trends in four high coca-producing and four violent Colombian departments, along with a department-level fixed effects model. Contrary to the conventional wisdom, the department-level analysis suggests that coca production is not the driving force of contemporary Colombian guerrilla violence. Instead, economic factors and coca eradication emerge as prominent explanatory factors.

Evaluating the spatiotemporal clustering of traffic incidents

Abstract This research presents both theoretical results regarding the nature of spatiotemporal clustering on a network, and applied outcomes from examining such clustering with regard to traffic incidents. The analysis considers fatal traffic incidents in eastern Fairfax County, Virginia and injury incidents in Franklin County, Ohio. The spatiotemporal analytical methods of Knox and subsequent researchers are reviewed. Specific methods for performing spatiotemporal analysis are outlined, with special attention given to the interpretation of the results for traffic incidents. An argument is made for conducting spatial and temporal cluster analyses independently, in addition to spatiotemporal cluster analysis, a comparative analysis of methods for testing for the significance of spatiotemporal clusters is presented, and suggestions for delineating critical parameters for the Knox statistic are provided.

The Transit Route Arc-Node Service Maximization problem

This article presents a new method for determining optimal transit routes. The Transit Route Arc-Node Service Maximization model is a mathematical model that maximizes the service value of a route, rather than minimizing cost. Cost (distance) is considered as a budget constraint on the extent of the route. The mathematical formulation modifies and exploits the structure of linear programming problems designed for the traveling salesman problem. An innovative divide-and-conquer solution procedure is presented that not only makes the transit routing problem tractable, but also provides a range of high-quality alternate routes for consideration, some of which have substantially varying geometries. Variant formulations are provided for several common transit route types. The model is tested through its application to an existing street network in Richardson, TX. Optimal numeric results are obtained for several problem instances, and these results demonstrate that increased route cost is not correlated with increased service provision.

A Subnational Study of Insurgency: FARC Violence in the 1990s

This article examines the traditional political and economic factors that have been purported to explain the prevalence of insurgency. It tests the following hypotheses at the subnational level in Colombia: guerrilla violence is positively associated with exports; higher levels of insurgency are associated with low levels of GDP per capita or negative growth rates; guerrilla violence emerges in the context of weak state presence; and higher levels of state repression are associated with higher levels of insurgent violence. The analysis utilizes a zero-inflated negative binomial to capture dynamics of both intensity and onset of violence. The econometric analysis is supplemented with cartographic visualization and qualitative analysis.

Crowdsourcing techniques for augmenting traditional accessibility maps with transitory obstacle information

One of the most scrutinized contemporary techniques for geospatial data collection and production is crowdsourcing. This inverts the traditional top-down geospatial data production and distribution methods by emphasizing on the participation of the end user or community. The technique has been shown to be particularly useful in the domain of accessibility mapping, where it can augment traditional mapping methods and systems by providing information about transitory obstacles in the built environment. This research paper presents details of techniques and applications of crowdsourcing and related methods for improving the presence of transitory obstacles in accessibility mapping systems. The obstacles are very difficult to incorporate with any other traditional mapping workflow, since they typically appear in an unplanned manner and disappear just as quickly. Nevertheless, these obstacles present a major impediment to navigating an unfamiliar environment. Fortunately, these obstacles can be reported, defined, and captured through a variety of crowdsourcing techniques, including gazetteer-based geoparsing and active social media harvesting, and then referenced in a crowdsourced mapping system. These techniques are presented, along with context from research in tactile cartography and geo-enabled accessibility systems.

A New Model for a Carpool Matching Service

Carpooling is an effective means of reducing traffic. A carpool team shares a vehicle for their commute, which reduces the number of vehicles on the road during rush hour periods. Carpooling is officially sanctioned by most governments, and is supported by the construction of high-occupancy vehicle lanes. A number of carpooling services have been designed in order to match commuters into carpool teams, but it known that the determination of optimal carpool teams is a combinatorially complex problem, and therefore technological solutions are difficult to achieve. In this paper, a model for carpool matching services is proposed, and both optimal and heuristic approaches are tested to find solutions for that model. The results show that different solution approaches are preferred over different ranges of problem instances. Most importantly, it is demonstrated that a new formulation and associated solution procedures can permit the determination of optimal carpool teams and routes. An instantiation of the model is presented (using the street network of Guangzhou city, China) to demonstrate how carpool teams can be determined.

Maternal-child overweight/obesity and undernutrition in Kenya: a geographic analysis.

OBJECTIVE The purpose of the study was to examine geographic relationships of nutritional status (BMI), including underweight, overweight and obesity, among Kenyan mothers and children. DESIGN Spatial relationships were examined concerning BMI of the mothers and BMI-for-age percentiles of their children. These included spatial statistical measures of the clustering of segments of the population, in addition to inspection of co-location of significant clusters. SETTING Rural and urban areas of Kenya, including the cities of Nairobi and Mombasa, and the Kisumu region. SUBJECTS Mother-child pairs from Demographic and Health Survey data including 1541 observations in 2003 and 1592 observations in 2009. These mother-child pairs were organized into 399 locational clusters. RESULTS There is extremely strong evidence that high BMI values exhibit strong spatial clustering. There were co-locations of overweight mothers and overweight children only in the Nairobi region, while both underweight mothers and children tended to cluster in rural areas. In Mombasa clusters of overweight mothers were associated with normal-weight children, while in the Kisumu region clusters of overweight children were associated with normal-weight mothers. CONCLUSIONS These findings show there is geographic variability as well as some defined patterns concerning the distribution of malnutrition among mothers and children in Kenya, and suggest the need for further geographic analyses concerning the potential factors which influence nutritional status in this population. In addition, the methods used in this research may be easily applied to other Demographic and Health Survey data in order to begin to understand the geographic determinants of health in low-income countries.

Optimal dispersion and central places

This paper presents research into optimal dispersion models as applied to central places. The literature regarding location optimization and central places is reviewed and the motivation for employing dispersion models is identified. Models that employ the objective of maximal dispersion in the context of central places are formulated and solved in the context of both single- and multiple-good systems. Two methods for generating multiple-good systems are presented: a multiple-type dispersion model and a K-value constraint set formulation. Sequential solutions to dispersion models demonstrate how a system of central places could develop over time. The solutions to these models generate the patterns of central places expected under the organizing principles of central place theory. The objective of maximal dispersion is posited as both a motivating factor in central place location decisions, and as the optimal outcome of a mature system of central places.