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Holistic geographic visualization of spatial data with applications in avalanche forecasting.

机译：空间数据的整体地理可视化及其在雪崩预测中的应用。

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摘要

Avalanche forecasters are faced with ever-increasing pressure to make more informed decisions and accurate predictions. Decisions often need to be made very quickly and face criticism from many different parties. Therefore, forecasters need a means to be able to synthesize data efficiently and effectively. The development of a better support system for decision makers and avalanche forecasters by incorporating new methodology into time-honored and proven methods is the goal of this research.; With the vast amount of data being produced, visualization is an improved and effective method for organizing, analyzing, and communicating complex data. This finding is supported by studies showing that the human mind assimilates complex information better when displayed graphically versus text-based or numerical representations. In order for visualization to be effective, it needs to be presented in a manner that is consistent with the cognitive, perceptual, and response-based mental representations of the user.; This research develops a new method to visualize multiple spatial data sets that are factors in determining snow pack stability in an intelligible holistic form that maintains the contribution of each data set. The spatial visualization model synthesizes multiple qualitative and quantitative spatial data sets into a single, clear, more comprehensible representation without losing important information. The visualization method allows the user to be able to drill down deeper or drill up to analyze individual data sets. In addition, a range comparison technique is developed to allow a set of chosen parameters to be compared with historic data in order to determine similar historic analogs. The result is an intuitive software program that allows users to analyze multiple complex data sets through a graphical user interface. The potential benefit of the visualization model is assessed through a user evaluation conducted along the Wasatch Front in the state of Utah.
机译：雪崩预报员面临越来越大的压力，他们需要做出更明智的决策和准确的预测。决策通常需要非常迅速地做出，并面临许多不同方面的批评。因此，预报员需要一种能够高效地合成数据的方法。本研究的目标是通过将新的方法学纳入久经考验的方法中，为决策者和雪崩预报员开发更好的支持系统。随着大量数据的产生，可视化是一种组织，分析和交流复杂数据的改进而有效的方法。研究表明，与基于文本或数字表示的图形显示相比，人的大脑可以更好地吸收复杂的信息，这一发现得到了支持。为了使可视化有效，需要以与用户的认知，知觉和基于响应的心理表征相一致的方式进行呈现。这项研究开发了一种新方法，以可视化的整体形式可视化多个空间数据集，而这些空间数据集是确定积雪稳定性的因素，可以保持每个数据集的贡献。空间可视化模型将多个定性和定量的空间数据集合成为单个，清晰，更易理解的表示形式，而不会丢失重要信息。可视化方法使用户能够更深入地钻取或向上钻取以分析单个数据集。另外，开发了范围比较技术以允许将一组所选参数与历史数据进行比较，以便确定类似的历史类似物。结果是一个直观的软件程序，使用户可以通过图形用户界面分析多个复杂的数据集。可视化模型的潜在好处是通过在犹他州的Wasatch Front进行的用户评估来评估的。

著录项

  • 作者

    McNeally, Phoebe Belle.;

  • 作者单位

    The University of Utah.;

  • 授予单位 The University of Utah.;
  • 学科 Geography.; Architecture.
  • 学位 Ph.D.
  • 年度 2008
  • 页码 146 p.
  • 总页数 146
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 自然地理学;建筑科学;
  • 关键词

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