Through the Looking Glass: Designing a Multi-Scale National Hydrographic Database

Professor of Geography, University of Colorado-BoulderPlatinum Sponsors KU Institute for Policy & Social Research Gold Sponsors Bartlett & West KU Department of Geography KU Libraries State of Kansas Data Access and Support Center (DASC) Silver Sponsors Kansas Biological Survey KU Center for Global & International Studies KU Environmental Studies Program Bronze Sponsors Global Information Systems KU Center for Remote Sensing of Ice Sheets (CReSIS) TREKK Design Group, LL

Inductive Explorations of Information Space Geography

Traditional approaches to mapping information space derive the space\u27s coordinate system from the postulates of a theory pertaining to the objective characteristics of the space. Examples of such approaches can be found in Dömel (1994), Girardin (1995), Hauck (1996) or Nielsen (1995). A good overview of these approaches is provided by Skupin (1998). Notwithstanding the usefulness of these approaches, especially for purposes of mapping the contents of information spaces, one could question the validity of the chosen coordinate system. Alternatively, one might try to inductively infer the coordinate system from navigational data generated by those traversing the space while in search of information. Unlike the traditional and normative approaches, such an inductive approach would result in the mapping of the information space as it is used rather than as it is defined. For information spaces implemented on the world-wide web, the navigational data for such an inductive approach exist in the transaction logs kept by the server through which the information is served

LOCALIS: Locally-adaptive Line Simplification for GPU-based Geographic Vector Data Visualization

Visualization of large vector line data is a core task in geographic and cartographic systems. Vector maps are often displayed at different cartographic generalization levels, traditionally by using several discrete levels-of-detail (LODs). This limits the generalization levels to a fixed and predefined set of LODs, and generally does not support smooth LOD transitions. However, fast GPUs and novel line rendering techniques can be exploited to integrate dynamic vector map LOD management into GPU-based algorithms for locally-adaptive line simplification and real-time rendering. We propose a new technique that interactively visualizes large line vector datasets at variable LODs. It is based on the Douglas-Peucker line simplification principle, generating an exhaustive set of line segments whose specific subsets represent the lines at any variable LOD. At run time, an appropriate and view-dependent error metric supports screen-space adaptive LOD levels and the display of the correct subset of line segments accordingly. Our implementation shows that we can simplify and display large line datasets interactively. We can successfully apply line style patterns, dynamic LOD selection lenses, and anti-aliasing techniques to our line rendering

Dasymetric distribution of votes in a dense city

[EN] A large proportion of electoral analyses using geography are performed on a small area basis, such as polling units. Unfortunately, polling units are frequently redrawn, provoking breaks in their data series. Previous electoral results play a key role in many analyses. They are used by political party workers and journalists to present quick assessments of outcomes, by political scientists and electoral geographers to perform detailed scrutinizes and by pollsters and forecasters to anticipate electoral results. In this paper, we study to what extent more complex geographical approaches (based on a proper location of electors on the territory using dasymetric techniques) are of value in comparison to simple methods (like areal weighting) for the problem of reallocating votes in a large, dense city. Barcelona is such a city and, having recently redrawn the boundaries of its census sections, it is an ideal candidate for further scrutiny. Although previous studies show the approaches based on dasymetric techniques outperforming simpler solutions for interpolating census figures, our results show that improvements in the process of reallocating votes are marginal. This brings into question the extra effort that entails introducing ancillary sources of information in a dense urban area for this kind of data. Additional research is required to know whether and when these results are extendable. (C) 2017 Elsevier Ltd. All rights reserved.This work was supported by the Spanish Ministry of Economics and Competitiveness under Grant CSO2013-43054-R.Pavia, JM.; Cantarino-Martí, I. (2017). Dasymetric distribution of votes in a dense city. Applied Geography. 86:22-31. https://doi.org/10.1016/j.apgeog.2017.06.021S22318

Methodologic issues and approaches to spatial epidemiology

Spatial epidemiology is increasingly being used to assess health risks associated with environmental hazards. Risk patterns tend to have both a temporal and a spatial component; thus, spatial epidemiology must combine methods from epidemiology, statistics, and geographic information science. Recent statistical advances in spatial epidemiology include the use of smoothing in risk maps to create an interpretable risk surface, the extension of spatial models to incorporate the time dimension, and the combination of individual- and area-level information. Advances in geographic information systems and the growing availability of modeling packages have led to an improvement in exposure assessment. Techniques drawn from geographic information science are being developed to enable the visualization of uncertainty and ensure more meaningful inferences are made from data. When public health concerns related to the environment arise, it is essential to address such anxieties appropriately and in a timely manner. Tools designed to facilitate the investigation process are being developed, although the availability of complete and clean health data, and appropriate exposure data often remain limiting factors

Geographic information systems and digital libraries: Issues of size and scalability

The term "scalability" has specific connotations in Geographic Information Systems (GIS) that conventionally relate to monitoring and predicting growth of geographic phenomena. A family of computational models has been developed to predict changes in structure associated with changes in size. These models have been applied in physical science, social science, and cartographic science to study growth and may assist in monitoring the growth of digital libraries as well. As the size of the digital library increases, challenges for data organization and collection maintenance tasks will also increase. However, the rate of increase may not be in linear proportion to library size. At some critical scales, existing procedures will fail and new procedures must be implemented to accommodate further growth. Allometric principles may be applied to estimate these critical scales. Three aspects (data volume, indexing, and metadata recordation) will be discussed in the context of implementing and maintaining a digital library containing spatial data archives distributed across local or global electronic networks.published or submitted for publicatio