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Gary J. Hunter

Bio: Gary J. Hunter is an academic researcher from University of Melbourne. The author has contributed to research in topics: Usability & Information system. The author has an hindex of 15, co-authored 33 publications receiving 1146 citations. Previous affiliations of Gary J. Hunter include University of California, Santa Barbara.

Papers
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TL;DR: A simple technique for assessing the positional accuracy of digitized linear features that can be implemented using standard functions and a standard scripting language in any raster or vector GIS.
Abstract: In this paper we propose a simple technique for assessing the positional accuracy of digitized linear features. The approach relies on a comparison with a representation of higher accuracy, and estimates the percentage of the total length of the low accuracy representation that is within a specified distance of the high accuracy representation. The approach deals successfully with three deficiencies of other methods: it is statistically based; is relatively insensitive to extreme outliers; and does not require matching of points between representations. It can be implemented using standard functions and a standard scripting language in any raster or vector GIS. We present the results of a test using data from the Digital Chart of the World.

316 citations

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TL;DR: A general-purpose model of DEM errors is proposed in which a spatially auto-regressive random field is added as a disturbance term to elevations in order to reduce the uncertainty in estimates of slope and aspect.
Abstract: Estimates of slope and aspect are commonly made from digital elevation models (DEMs), and are subject to the uncertainty present in such models We show that errors in slope and aspect depend on the spatial structure of DEM errors We propose a general-purpose model of DEM errors in which a spatially auto-regressive random field is added as a disturbance term to elevations In addition, we propose a general procedure for propagating such errors through GIS operations In the absence of explicit information on the spatial structure of DEM errors, we demonstrate the potential utility of a worst-case analysis A series of simulations are used to make general observations about the nature and severity of slope and aspect errors

196 citations

Journal Article
TL;DR: In this article, three basic approaches for modeling and communicating error in spatial databases are examined, and the authors suggest that the application of simple probability theory, when combined with the error estimates supplied by data producers and current computer graphics capabilities, can provide users with more meaningful information concerning the error of their spatial database products.
Abstract: There is now a considerable body of literature on the techniques available for modeling and communicating error in spatial databases. Some error models have solid statistical foundations, while the basis for others is not so strong. In this paper, three basic approaches to the problem are examined. The application investigated is a fundamental one ― to determine the position of a given terrain elevation value and to portray the resultant error of the answer. Such a problem can be of critical concern to communities in cases of flood plain mapping, determination of rising sea levels resulting from global warming, or delineation of the full supply level for a proposed reservoir. In this instance, the authors suggest that the application of simple probability theory, when combinede with the error estimates supplied by data producers and current computer graphics capabilities, can provide users with more meaningful information concerning the error of their spatial database products. In turn, this information may allow them to better deal with an issue of growing concer

109 citations

Journal ArticleDOI
TL;DR: A simple spatio‐temporal model of population location that might improve risk assessment and damage analysis for decision‐making in both the Finnish Fire and Rescue Services and the Finnish Defence Forces is developed and implemented.
Abstract: The aim of this research is to develop and implement a simple spatio-temporal model of population location that might improve risk assessment and damage analysis for decision-making in both the Finnish Fire and Rescue Services and the Finnish Defence Forces. The motivation for the research is that present risk models do not take into account the temporal variation in population location during different times of the day. We use spatio-temporal modelling methods to model the population dynamics, and visualization techniques to represent the model outcomes. In addition, we apply the developed model to a damage-analysis application. The case study site is located in the centre of Helsinki. The model uses a basic population and workplace dataset maintained by the Helsinki Metropolitan Area Council. By means of this model, we intend to advance risk assessment, which considers the consequences of accidents. This model has the potential to help decision-makers evaluate their plans in several application areas-such as achieving better preparedness by having more reliable evacuation plans and resource allocation. In addition to the application-related technological research, a more generic framework about decision-making supported by spatio-temporal knowledge and visualization is presented.

77 citations

Journal ArticleDOI
TL;DR: This paper shows that risk management offers geographical data users a range of options for responding to the adverse consequences of data uncertainty, and presents and discusses the various risk response options.
Abstract: The presence of uncertainty in geographical data has the potential to expose users to undesirable consequences in their decision making. Accordingly, our efforts to understand uncertainty seek to (a) avoid the use of data that are not suitable for their intended purpose (that is, data whose consequences are unacceptable), (b) to reduce any undesirable consequences to an acceptable level, and (c) to devise ways of living with undesirable data when the adverse consequences caused by poor data do not alter our ultimate decision choice. To assist this task, we propose an approach where the adverse consequences of uncertainty caused by the use of unsuitable geographical data are expressed in terms of risk. In this paper we first show that risk management offers geographical data users a range of options for responding to the adverse consequences of data uncertainty, and secondly we present and discuss the various risk response options.

61 citations


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6,278 citations

Journal ArticleDOI
TL;DR: Analysis of the quality of OpenStreetMap information focuses on London and England, since OSM started in London in August 2004 and therefore the study of these geographies provides the best understanding of the achievements and difficulties of VGI.
Abstract: Within the framework of Web 2.0 mapping applications, the most striking example of a geographical application is the OpenStreetMap (OSM) project. OSM aims to create a free digital map of the world and is implemented through the engagement of participants in a mode similar to software development in Open Source projects. The information is collected by many participants, collated on a central database, and distributed in multiple digital formats through the World Wide Web. This type of information was termed 'Volunteered Geographical Information' (VG!) by Goodchild, 2007. However, to date there has been no systematic analysis of the quality of VGI. This study aims to fill this gap by analysing OSM information. The examination focuses on analysis of its quality through a comparison with Ordnance Survey (OS) datasets. The analysis focuses on London and England, since OSM started in London in August 2004 and therefore the study of these geographies provides the best understanding of the achievements and difficulties of VGI. The analysis shows that OSM information can be fairly accurate: on average within about 6 m of the position recorded by the OS, and with approximately 80% overlap of motorway objects between the two datasets. In the space of four years, OSM has captured about 29% of the area of England, of which approximately 24% are digitised lines without a complete set of attributes. The paper concludes with a discussion of the implications of the findings to the study of VGI as well as suggesting future research directions.

1,493 citations

Journal ArticleDOI
TL;DR: Progress toward visual tools and methods to help analysts manage and understand information uncertainty are reviewed and progress toward frameworks for representing uncertainty, visual representation and user control of displays of information uncertainty is assessed.
Abstract: Developing reliable methods for representing and managing information uncertainty remains a persistent and relevant challenge to GIScience. Information uncertainty is an intricate idea, and recent examinations of this concept have generated many perspectives on its representation and visualization, with perspectives emerging from a wide range of disciplines and application contexts. In this paper, we review and assess progress toward visual tools and methods to help analysts manage and understand information uncertainty. Specifically, we report on efforts to conceptualize uncertainty, decision making with uncertainty, frameworks for representing uncertainty, visual representation and user control of displays of information uncertainty, and evaluative efforts to assess the use and usability of visual displays of uncertainty. We conclude by identifying seven key research challenges in visualizing information uncertainty, particularly as it applies to decision making and analysis.

540 citations

01 Jan 2002
TL;DR: In this paper, the authors present a schedule of teaching assistant hours for the Geogtamuedu Teaching Assistants Program at the University of Guo et al. (GAMEDU).
Abstract: Instructor: Dr Hongxing Liu Office hours: Tue and Thur 2:30-4:30PM, OM Email: liu@geogtamuedu Teaching Assistants Sindhu George Office hours: Wed 1:45-2:45pm, Thur 1:15-2:15pm, O&M 816 Email: sindhu@geogtamuedu Jongwon Lee Office hours: Tue 1:00-2:00pm, Wed 4:30-5:30pm, O&M 209B Email: jongwon@geogtamuedu Zengwang Xu Lab support hours: Mon 9:00-10:00pm, Tue, Wed, and Thur 5:00-10:00pm

494 citations