Research Commentary

Flexibility is what people seek when striving to increase or expand economic and social choices, equity, and technological innovations. Flexibility provides the robustness needed to adjust to changes such as those arising from a warmer/colder world, and the actions required when managing threats from and results of social strife, economic downturns, environmental catastrophes, infrastructure disruptions, and war. Flexibility is easy to praise at the level of principle, if allowed that a bit of stability and resistance to change does have merit. At the level of practice or operations the concept is most elusive, and explaining what flexibility means, why it is thwarted, and how it might be obtained is a challenging task. This paper begins by contrasting views of systems and their behaviors. Alternative explanations for behaviors thwarting flexibility are identified. Consequences of inflexible, locked-in development paths are illustrated using examples from transportation and similar systems. Suggestions for increasing flexibility are made after examining system behaviors in dynamic contexts. Academic, government, and industry experiences inform and color interpretations.

A Neural Network for Modeling Multicategorical Parcel Use Change

This paper presents an artificial neural network (ANN) for modeling multicategorical land use changes. Compared to conventional statistical models and cellular automata models, ANNs have both the architecture appropriate for addressing complex problems and the power for spatio-temporal prediction. The model consists of two layers with multiple input and output units. Bayesian regularization was used for network training in order to select an optimal model that avoids over-fitting problem. When trained and applied to predict changes in parcel use in a coastal county from 1990 to 2008, the ANN model performed well as measured by high prediction accuracy (82.0-98.5%) and high Kappa coefficient (81.4-97.5%) with only slight variation across five different land use categories. ANN also outperformed the benchmark multinomial logistic regression by average 17.5 percentage points in categorical accuracy and by 9.2 percentage points in overall accuracy. The authors used the ANN model to predict future parcel use change from 2007 to 2030.

Cultural Dasymetric Population Mapping with Historical GIS

There has been a recent flurry of interest in dasymetric population mapping. However, the ancillary coverages that underlie current dasymetric methods are unconnected to cultural context. The resulting regions may indicate density patterns, but not necessarily the boundaries known to inhabitants. Dasymetric population mapping is capable of capturing the cultural commonality and community interaction that define social spaces. Dasymetric mapping may be improved with methodologies that reflect the ways in which social spaces are established. This research applies a historical GIS methodology for identifying early 20th Century agricultural neighborhoods in southern Appalachia. The case study is intended to encourage discovery of additional methods for mapping population on the scale of lived experience.

Sharing Environmental Data through GEOSS

Understanding the complexity of earth-system processes is crucial to convey improved information on the environment to decision-makers and the general public. Addressing this need by sharing environmental data is challenging because it requires a common agreed framework that allows easy and seamless integration of data from different sources. In this regard, the Global Earth Observation System of Systems (GEOSS) portends major benefits through various sharing mechanisms and by giving access to services that could be linked together to process and generate new understandable knowledge and information. Various United Nations projects could greatly benefit from the GEOSS approach.

Relating Transportation Quality Indicators to Economic Conditions in the South-Central U.S.

Investment in transportation infrastructure is widely assumed to spur economic growth, a belief that persists among both the general public and government officials. However, research has provided inconsistent evidence to date, and many researchers believe that good transportation is a necessary but insufficient condition for regional growth. This study examines the issue from a different perspective than the majority of past research, using spatial regression techniques to explore the relationship between transportation quality and regional economic development at an intermediate spatial resolution. Using federal highway statistics on pavement roughness and bridge quality, this research examines the relationship between measurable results of transportation spending, as evidenced by better quality roads and bridges, and various indicators of economic health. This relationship is examined in the South-Central U.S. (Arkansas, Kansas, Oklahoma, and Texas) at the county level and uncovers moderate to weak regression coefficients overall but with notable spatial variations across the study area.

Showing the Past

Spatial Data Infrastructures have become a methodological and technological benchmark enabling distributed access to historical-cartographic archives. However, it is essential to offer enhanced virtual tools that imitate the current processes and methodologies that are carried out by librarians, historians and academics in the existing map libraries around the world. These virtual processes must be supported by a generic framework for managing, querying, and accessing distributed georeferenced resources and other content types such as scientific data or information. The authors have designed and developed support tools to provide enriched browsing, measurement and geometrical analysis capabilities, and dynamical querying methods, based on SDI foundations. The DIGMAP engine and the IBERCARTO collection enable access to georeferenced historical-cartographical archives. Based on lessons learned from the CartoVIRTUAL and DynCoopNet projects, a generic service architecture scheme is proposed. This way, it is possible to achieve the integration of virtual map rooms and SDI technologies bringing support to researchers within the historical and social domains.

Communities, Cartography and GIS

This paper discusses an introductory cartography and GIS service learning course. The service learning experience, highlighted by a final mapping project and community presentation, resulted in 3,000 student-designed maps being distributed to community residents, a website of downloadable student maps, multiple student speaking engagements, and a sustained community-university collaboration. The course demonstrates the importance of applied geography in local communities and highlights the benefits of community-university partnerships for addressing social change. Such an applied geography experience offers an important twist on the conventional, introductory cartography course where students engage in pre-packaged lectures and labs, and are then asked to complete a final mapping project. Unlike the conventional approach, this service learning class experience allows students to use their creativity to demonstrate knowledge learned in the course and allows students to apply and present their geographic knowledge in a real-world setting to community members.

A GIS Methodology for Assessing the Safety Hazards of Abandoned Mine Lands (AMLs)

Abandoned mine lands (AMLs) associated with past coal-mining scar Pennsylvania’s landscape with environmental and safety hazards. Reclamation projects eliminate and reduce hazards AMLs pose. Due to the large number of AMLs and limited funds, precedence is given to reclaim the most hazardous sites first. These sites are identified through an assessment process that assigns priorities to AMLs. However, priorities are out-dated and do not accurately reflect the current spatial distribution of land use and census data. This article presents a GIS methodology for the prioritization of AMLs using the process of extrapolation and focal statistics. By incorporating current assessment techniques into GIS with current land use and census data, AML priorities were reassigned to accurately reflect the current spatial landscape. Results indicate that current AML priorities assigned by the state do not accurately reflect current land use and census data and underestimate the safety hazards of many sites, including high priority sites.

Applied Geospatial Perspectives on the Rock Art of the Lake of the Woods Region of Ontario, Canada

This study examines the role of rock art in the construction of Woodland Period (300 BC to AD 1700) hunter-gatherer landscapes in the Lake of the Woods region of northwestern Ontario. The authors examine the distribution of documented pictograph sites relative to the locations of rock formations where the geologic conditions would have favored the placement of pictographic rock art but are absent. Point pattern analysis, Monte Carlo simulation, and least cost path analysis were used to analyze the findings. The authors suggest that pictograph sites were placed at points on the landscape along water routes to facilitate information exchange among highly mobile hunter-gatherers.

Target Evaluation and Correlation Method (TECM) as an Assessment Approach to Global Earth Observation System of Systems (GEOSS)

The Global Earth Observation System of Systems (GEOSS) is a ten-year-long Implementation Plan, which commenced in 2005 as a group effort by numerous participating countries and organizations to build a large-scale network to effectively monitor and respond to the increasingly complex web of global environmental and socio-economic issues. This paper proposes the Target Evaluation and Correlation Method (TECM) as an assessment approach to GEOSS with its 241 Targets across the nine “Societal Benefit Areas,” along with a method to identify Target Correlation Levels (TCL). Applying TECM allows concluding whether the chosen targets within the GEOSS fall into the domain of System of Systems (SoS), while using TCLs delineates the extent of inclusion for these targets in the form of a system. Furthermore, this research investigates the possible ways of raising the correlation levels of the targets for the cases in which TCLs are low.