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GeoSpatial Visual Analytics

Geographical Information Processing and Visual Analytics for Environmental Security

  • Conference proceedings
  • © 2009

Overview

Editors:
  1. Raffaele De Amicis

    1. Fondazione GraphiTech Center for Advanced Computer Graphics Technologies, Trento, Italy

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  2. Radovan Stojanovic

    1. University of Montenegro, Podgorica, Montenegro

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  3. Giuseppe Conti

    1. Fondazione GraphiTech Center for Advanced Computer Graphics Technologies, Trento, Italy

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  • Highlights the importance of Visual Analytics for environmental security
  • Stresses the role of harmonization for environmental data access and processing
  • Provides a broad view on a large range of issues related to environmental security
  • Presents best practices on the use of IT technologies for sustainable development
  • Presents different political, economical and social factors

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Table of contents (40 papers)

  1. Front Matter

    Pages i-x
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  3. Signal and Data Processing

    1. Sorting Spatial Data by Spatial Occupancy

      • Hanan Samet
      Pages 31-43

    2. Gis Model Applications for Sustainable Development and Environmental Planning at the Regional Level

      • Joerg Schaller, Cristina Mattos
      Pages 45-57

    3. Application of Neural Networks In Image Processing and Visualization

      • Paul Dan Cristea
      Pages 59-71

    4. Data Processing for Heavy Metals Accumulation in Urban Areas

      • Dragana Ðorđević
      Pages 73-83

    5. A Multi-Criteria Decision Making Conceptual Approach to Optimal Landfill Monitoring

      • Ana M. Lazarevska, Nicole Fischer, Andreas Haarstrick, Kai MüNnich
      Pages 85-96

    6. Environmental Protection and Industry: Parameters Necessary for Environmentally Related Decision Making

      • Aleksandar NošPal, Ana M. Lazarevska
      Pages 97-112

    7. Time-Frequency Analysis for Sar and Isar Imaging

      • Igor Djurović, Ljubiša Stanković, Vesna Popović, Miloš Daković, Thayananthan Thayaparan
      Pages 113-127

    8. Processing of Multichannel Remote Sensing Data for Environment Monitoring

      • Vladimir Lukin
      Pages 129-138

  5. Scientific Visualization

    1. Visual Processing of Geographic and Environmental Information in the Basque Country: Two Basque Case Studies

      • Alvaro Segura, Aitor Moreno, Igor García, Naiara Aginako, Mikel Labayen, Jorge Posada et al.
      Pages 199-207

    2. Dynamic Terrains: Cities and Real-Time Video on Gigantic Terrain Models

      • Carlos Andújar, Pere Brunet, José Diaz
      Pages 209-213

    3. Digital Terrain Models: A Tool for Establishing Reliable and Qualitative Environmental Control Processes

      • Yerach Doytsher, Sagi Dalyot, Yaron Katzil
      Pages 215-234

    4. Advanced Clustering Analysis for Environmental Indicators

      • Ido A. Iurgel, Maribel Yasmina Santos
      Pages 235-250
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Keywords

About this book

Access, distribution and processing of Geographic Information (GI) are basic preconditions to support strategic environmental decision-making. The heterogeneity of information on the environment today available is driving a wide number of initiatives, on both sides of the Atlantic, all advocating both the strategic role of proper management and processing of environme- related data as well as the importance of harmonized IT infrastructures designed to better monitor and manage the environment. The extremely wide range of often multidimensional environmental information made available at the global scale poses a great challenge to technologists and scientists to find extremely sophisticated yet effective ways to provide access to relevant data patterns within such a vast and highly dynamic information flow. In the past years the domain of 3D scientific visualization has developed several solutions designed for operators requiring to access results of a simulation through the use of 3D visualization that could support the understanding of an evolving phenomenon. However 3D data visualization alone does not provide model and hypothesis-making neither it provide tools to validate results. In order overcome this shortcoming, in recent years scientists have developed a discipline that combines the benefits of data mining and information visualization, which is often referred to as Visual Analytics (VA).

Editors and Affiliations

  • Fondazione GraphiTech Center for Advanced Computer Graphics Technologies, Trento, Italy

    Raffaele De Amicis, Giuseppe Conti

  • University of Montenegro, Podgorica, Montenegro

    Radovan Stojanovic

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