Piotr Jankowski - US grants

The goal of the project is to expand and improve the existing curriculum and teaching capabilities in computer-assisted cartography, geographic information systems (GIS) and remote sensing in the Department of Geography, University of Idaho. The new laboratory equipment includes PC workstations, data input and output devices (digitizers and plotters) and a local area network to provide transfer capability of files from IBM compatible workstations to Macintosh workstations as well as with the campus-wide electronic network. This will provide a versatile laboratory for undergraduate instruction in computer assisted geographic information technologies. A series of lab sessions based on the proposed equipment has been designed that will address a missing component of the curriculum, learning and mastering tools and skills to address theoretical problems and applied techniques needed in the present computer-aided job market. The laboratory improvement is part of a larger development program for the College of Mines and Earth Resources.

9411008 JANKOWSKI Locational conflicts arise when different people or groups give different weights to various factors when deciding where to locate facilities or resources. The development of spatial decision-support systems (SDSSs) for use within geographic information systems (GISs) has offered new approaches for solving spatial problems and making locational decisions. Knowledge of the benefits and limitations of such systems is limited by a paucity of conceptual and empirical critiques of their use, however. This collaborative research project will provide insights into the use of a SDSS for groups in order to understand how and why such a group system affects decision-making processes and outcomes. Special attention will be given to analysis of that ways that several thematic map types and multi-criteria decision models influence the dynamics of, and are influenced by, small-group interactions for site-location decisions. In laboratory experiments of small groups with five participants within each group, graduate students from environmentally related programs will select sites for habitat restoration and development in the wake of toxic-waste cleanup projects. Participants will function in a group-based software environment created from a combination of commercial and public-domain software. Interaction-coding techniques will be used to compile data from transcripts of the interaction process in order to ascertain how SDSS approaches affect group decision making. This project will contribute valuable new insights into the dynamics of collaborative decision making and the use of information technology by adding substantive knowledge about multi-phase group decision-making processes. It will apply and refine an interaction-coding scheme to develop a knowledge base that other technology-based studies of collaborative spatial decision making can use, and it will develop a more complete understanding of the integration needs for information tech nology that involves GISs, multi-criteria decision models, and SDSSs for groups. Because of the pervasive character of locational issues requiring collective decision making, the potential applications for advances along these lines is enormous.

The increasing involvement of stakeholder groups in solving spatial decision problems has created a need for information technology capable of supporting collaborative spatial decision making. The goal of this project is to develop a better understanding of how groups of stakeholders may use geospatial technology to enhance collaborative approach to problem solving and decision making. Such knowledge is necessary in order to develop geospatial technology support tools capable of accommodating diverse participants involved in solving location-based decision problems. This project will use a field experiment approach to study the dynamics of collaborative work and decision making supported by geospatial information technology. The experiment will involve true stakeholders invited to engage in a realistic decision problem of water management planning in the Boise River basin in southwestern Idaho. Two groups each with 10 participants will be used: the control group will be exposed only to traditional support tools such as traditional maps, whereas the experimental group will be exposed to collaborative decision support tools such as geographic information system (GIS) -based maps and three-dimensional visualizations. The human-computer-human interaction process during the experiment will be captured using professional video cameras. A tested social-behavioral science technique called "interaction coding" will be employed to compile data logs from the experiment and exploratory sequential data analysis techniques will be used to analyze the data. Parametric and non-parametric statistical procedures will be used to test a number of research hypotheses.

Dealing with location-based decision problems in an open manner is becoming more important as stakeholder participation increases in land use, natural resource, and environmental decision making. The primary rationale for enhanced stakeholder participation in environmental decision making is based on the democratic maxim that those affected by a decision should participate directly in the decision making process. The project results are expected to expand knowledge about the impacts of geospatial information technology on collaborative decision processes engaging diverse groups of stakeholders. Moreover, the project will help develop and share a better understanding of the integration needs for information technology involving geographic information systems, decision models, and group collaboration support tools.

Abstract

EIA-0325916
Nyerges, Timothy
Title: ITR: An Internet Platform to Support Public Participation in Transportation Decision Making


This project develops and evaluates Internet-hosted capabilities, particularly based on Internet geographic information systems (GIS) technology, to support participatory modeling in transportation decision making.
The project makes a contribution to knowledge and understanding about Internet GIS technology designs that can improve the publics' access to voice, competence of knowledge, and shared understanding within transportation planning decision situations. We make that contribution by implementing a prototype Internet platform through which a variety of GIS-based analytic-deliberative agendas and participatory choice models can be designed and implemented. As a broad impact with benefits to society, the Internet GIS platform will provide a technology prototype that supports enhanced participation in three, pervasive, transportation planning decision contexts common to metropolitan areas across the US. The results of the study are likely to be general enough to transfer to other planning contexts such as land use and environment, because the participation framework underlying the needs analysis is based in large part on public empowerment in decisions. Enhancing participation in decision making is a step toward improving local governance - a widespread challenge across western democracies.

Suburbia located in the urban-rural transition zone have an undeniable appeal to many urban dwellers. At the same time, they are characterized by low-density, leapfrog, and fragmented residential patchwork of developed and undeveloped tracts. Such land-use arrangements have led to an increasing ethnical and economic separation, deterioration of the environment, loss of agricultural land and wilderness, and the erosion of society's architectural heritage. This doctoral dissertation research project addresses a question of whether other arrangements of land that ameliorate the negative effects of current growth in the suburban fringe are sustainable and socially acceptable. In order to answer the research question, the doctoral student will employ an integrative form-and-process methodology for urban land-use modeling, where generative spatial optimization is coupled with exploratory spatial agent-based simulation. The methodology will be tested on a small exurban community of Chelan City in the state of Washington, which has been subject to two opposing and competing spatial development forces: endangered salmon protection and a recreation and retirement-bound influx of people from the Puget Sound metropolitan area. The first step of the research will be to generate a number of spatial solutions using a multiobjective land-allocation model, where population growth is directed to infill and redevelopment, with promotion of mixed uses and high build-out density. Whether such sustainable patterns are possible at all in practice given the inconsistency of human spatial decision-making is a major research question. The student will investigate it by using spatial agent-based simulation to test the achievability of sustainable growth management scenarios in an artificial society. The spatial outcomes from the optimization and simulation models will be further used for comparative analysis to identify social interactions among local developers that could lead to sustainable land-use patterns in the real world.

The results of this research will contribute to better understanding of the factors that could be used to promote sustainable land use development. Moreover, this study integrates geography with a body of knowledge related to psychology of choice. Prospect decision-making theory, explaining choice-making under various risk attitudes, will be investigated in a number of configurations to verify the social acceptance of anti-sprawl land use arrangements. The novelty of this research lies in its emphasis on the generative and exploratory role of modeling for more informed land use policymaking. The two complementary models will serve as inference engines for browsing through landscapes of spatial information and creating new possibilities of growth accommodation. This research may also lead to an increased recognition of geographic modeling in understanding the complexities of spatio-temporal dynamics of land use change. As a Doctoral Dissertation Research Improvement award, this award will also provide support to enable a promising student to establish a strong independent research career.

This Geography and Spatial Sciences (GSS) project will develop novel methods for understanding and categorizing uncertainty in complex spatial models of human and environmental systems interactions. Increasingly scientists are utilizing such models to understand the dynamics of various processes including urban expansion, climate change, deforestation, and nonpoint pollution of water bodies. An inherent complexity in these processes, leading to model uncertainty, is the variability over both space and time. For example, the dynamics of urban expansion in Detroit are different than those in Cleveland, and their dynamics today are different than those ten years ago. Models of such systems typically require a large number of explanatory variables that describe the economic, social, political, and environmental components of the overall system. To address model uncertainty, scientists use sensitivity analysis: a technique employed to understand how different values of an explanatory variable affect the outcome of interest. For example, how do increasing payments to farmers affect their willingness to convert agricultural lands for conservation purposes? This project will develop a new theoretical framework for applying sensitivity analysis to complex human-environment systems models exhibiting great variability over space and time. Specifically, the framework will facilitate 1) the identification of explanatory variables that account for the greatest variability in model outcomes leading to model simplification; 2) the exploration of the model outcome variability over space and time; and 3) the simulation of system dynamics to understand the implications of various policy scenarios. The developed framework will be tested on a model designed to understand agricultural land conservation decisions and their effects on lakes, local economies, and people.

This project will contribute greatly to scientists', policy-makers', and citizens' abilities to understand the extent to which various drivers in human-environment systems models affect model outcomes. Moreover, the project will facilitate the development of simpler systems models with greater explanatory power. As such, the methods developed will improve the transparency of such models potentially allowing greater community use, understanding, and participation in such modeling exercises. The framework will also provide methods for prioritizing data acquisition, improving the robustness of complex human-environment models, and enhancing the usefulness of such modeling endeavors for policy and decision making to address major societal problems. The project will train students, through graduate student mentoring and a modeling certification graduate program, to employ the new methods developed in order to describe and solve complex human-environment systems problems. The results of our research, including a spatiotemporal sensitivity analysis toolbox (ST-SA), will be disseminated electronically online, in peer reviewed manuscripts, and at professional conferences.

This award will support a workshop that will bring together experts from a broad range of fields to examine and advance the development and use of agent-based models (ABMs) in the social, human-environment, and life sciences. The conference will facilitate community-wide consideration of issues that enhance and broaden the value and utility of agent-based modeling for scholarly and practical purposes. The conference will advance a multi-faceted, community-based examination of current strengths and shortcomings of ABM development and use. The conference and its follow-up products will identify incentives and directions for many related fields to develop more robust, user-friendly tools based on service-oriented ABM designs and platforms. The workshop also has the potential to facilitate interactions between academic-based ABM developers and users and commercial companies in ways that may facilitate advances in ABM software and capabilities. Because of the diversity of fields from which participants are drawn, the conference will promote more interdisciplinary development and use of advanced methodologies.

The use of agent-based models has increased rapidly over the last two decades. The number of articles reporting the development or use of ABMs has increased at an exponential rate since the 1990s, spanning a diverse range of scientific communities that includes geography, ecology, human-environmental science, land-system science, and sociology. A strength of agent-based models has been the potential for representing agent-agent and agent-environment interactions, local-level information and heterogeneity, nonlinearity, feedback, and individual-level activity and decision-making. ABMs also are useful for integrating data and models across multiple systems and for addressing problems across spatial, temporal, and organizational scales. Despite these advances, a number of challenges confront ABM developers and users, including difficulty in model verification and validation, steep learning curves for non-modeling experts, and the lack of common standards or protocols, and limitations regarding their transparency and reusability. To address these challenges, more than three dozen individuals who are ABM modelers and users will gather to identify strengths and weaknesses in the state-of-the-science of agent-based modeling. Participants will engage in a set of discussions on a range of topics that may include model validation, modeling of human decisions, model transparency and reusability, and developing ABMs that can better use "big data." Participants also will identify resources, areas for collaboration, potential tasks, and future directions for the ABM community. Insights and products after the conclusion of the conference are expected to include a synthesis paper and several topical papers dealing with ABMs; a book about ABM science, technology, and application; and an online repository that shares useful ABM resources. Organizers expect this conference to be conducted during the spring months of 2017, most likely in San Diego, California.

This doctoral dissertation research project will examine public attitudes towards geoprivacy and the extent to which Internet users attempt to obscure or mask their personal locations in order to protect privacy when they engage in online activity. The project will provide new knowledge about the strategies individuals employ to prevent their personal identifiability when location is requested, and it will provide new insights into the relationships between privacy attitudes and behavior in responding to location requests. While much work on geoprivacy focuses on strategies for researchers to protect the anonymity of human subjects, this project will emphasize the role individuals play in managing their own location profiles. This project will enhance basic understanding of the factors associated with the propensity to mask location, which will inform future research that assumes self-reported location to be factual by providing a sounder basis for error calculation. Improved knowledge about who is masking their data online and why they are doing so will help application developers better understand how to serve those individuals. Results will be disseminated broadly to a wide range of potential beneficiaries, including non-profit groups that seek to protect digital privacy and governmental organizations like the National Geospatial Advisory Committee. As a Doctoral Dissertation Research Improvement award, this award also will provide support to enable a promising student to establish a strong independent research career.

Geoprivacy refers to the right of individuals to control when and how their personal location data are shared. Amid increasingly pervasive locational data collection, attempts by the public to exercise this control largely remain unexplored. This doctoral student conducting this project will examine the ways in which adults mask their location data online as well as how geoprivacy knowledge and attitudes influence this location-masking behavior. She will conduct an online survey of adults in California using a probability sample with a mail contact method to enhance response rate and an open sample with an online solicitation. She will analyze the correlates of both the resolution and factuality of location provided in the survey with logistic regression. Among intervening variables that the student will consider are previous privacy infringement, experience with hacking or identity theft, and data industry experience. She also will test for spatial clusters of higher and lower levels of location-masking activity.

Low-income and racially- and ethnically- diverse communities across the United States experience limited access to healthy foods, and a higher concentration of liquor, corner, and convenience stores than supermarkets, with implications for the health and well-being of residents. Walk to Healthy Foods' vision is to bridge the gap between food accessibility and community needs in underserved communities nationwide by providing communities with an approach for identifying and leveraging existing assets in their communities to address food access challenges. Walk to Healthy Foods takes an asset-based approach by identifying businesses that are already serving community residents, such as existing liquor, corner, and convenience stores, and leveraging their presence in the community to provide healthier food options. During Stage 1, through engagement and collaboration with community stakeholders, Walk to Healthy Foods will develop a site selection model for identifying existing assets in the community that can become access points for healthy foods. During Stage 2, Walk to Healthy Foods will test and calibrate the site selection model through an intervention in an underserved community in San Diego County. Specifically, the site selection model will be used to identify potential healthy food access points, and produce distribution services will be launched at these sites, resulting in increased access to fresh produce in the community.<br/><br/>The approach proposed, which includes partnering with an organization that is providing a direct service to the community (i.e., produce distribution services to selected sites), allows a true test of the site selection model and for research to address a community-identified need through a pilot that will have a direct impact on one community while testing and calibrating a model that can be implemented in others. A site selection model that can be used to identify existing assets in underserved communities that can be leveraged to address systemic challenges, such as limited food access, has the potential to redefine what is needed in communities for residents to have access to essential resources. Walk to Healthy Foods will contribute to the fields of geography, public health, city planning, and business, among others, and to the ongoing development of innovative approaches to solving pressing social issues.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.