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Generation and refinement of a continental-scale digital elevation model by integrating cartographic and remotely sensed data: A GIS-based approach.

机译:通过集成制图和遥感数据生成和完善大陆规模的数字高程模型:一种基于GIS的方法。

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摘要

Digital Elevation Models (DEMs) are of fundamental importance to a wide range of geo-scientific and environmental studies. This research addresses technical and theoretical issues involved in the construction of a large-scale DEM with multiple data sources. Enormous data volume, diverse data sources and different terrain types complicate the large-scale DEM generation process. To tackle technical difficulties and challenges, several new methods have been developed and some existing algorithms have been improved. Having these newly developed and extended methods and algorithms along with available GIS functions, we constructed a complete, consistent, and high-resolution DEM over the Antarctic by integrating a variety of cartographic and remotely sensed data.;This research demonstrates that the GIS technology represents an effective means of integrating not only various types of topographical data, but also a pool of alternative computational methods and techniques for the creation of large-scale DEMs. Nevertheless, currently available GIS software did not provide an entire solution to the development and refinement of large-scale DEMs.;In this research, a number of error detection techniques have been developed for efficiently checking and eliminating gross errors in source data. New interpolation procedures were designed for gridding traverse data and contour-based topographical data. The determination of an optimal interpolation spacing was pursued. A conceptual framework was proposed for integrating and fusing complementary and competitive topographical data. In the case of the Antarctic, a set of criteria were developed for the selection of competitive data to exploit the best elements of available sources. It is also demonstrated that spatially and functionally complementary topographical data sources can be synergistically combined during the interpolation stage to create a more reliable and accurate elevation model than what a single source could create alone. A new algorithm was developed for merging individual DEM data sets into a seamless DEM mosaic along irregular lines. For DEM refinement, the potential of the state-of-the-art remote sensing techniques, including shape-from-shading, SAR stereo and interferometric SAR (InSAR), are discussed and demonstrated. A technical strategy is formulated for future improvement of the Antarctic DEM.;The accuracy and error pattern of the resultant Antarctic DEM were evaluated in a number of ways. Comparisons with high-resolution satellite images at different scales demonstrate that the DEM not only describes the broad topographical configuration and true ice drainage pattern, but also captures unprecedented detail of the terrain surface. We believe that this DEM product represents the most detailed and accurate digital description of the Antarctic topography published to date.
机译:数字高程模型(DEM)对于广泛的地质科学和环境研究至关重要。这项研究解决了构建具有多个数据源的大规模DEM涉及的技术和理论问题。庞大的数据量,不同的数据源和不同的地形类型使大规模DEM生成过程变得复杂。为了解决技术难题和挑战,已经开发了几种新方法并且已经改进了一些现有算法。有了这些新近开发和扩展的方法和算法以及可用的GIS功能,我们通过集成各种制图和遥感数据构建了一个完整,一致且高分辨率的南极DEM。该研究表明GIS技术代表了一种有效的方法,不仅可以集成各种类型的地形数据,还可以集成用于创建大规模DEM的替代计算方法和技术库。然而,当前可用的GIS软件不能为大规模DEM的开发和完善提供完整的解决方案。在这项研究中,已经开发了许多错误检测技术来有效地检查和消除源数据中的重大错误。设计了新的插值程序,以对导线数据和基于轮廓的地形数据进行网格化。追求最佳插值间距的确定。提出了一个概念框架,用于整合和融合补充性和竞争性地形数据。就南极而言,为选择竞争性数据制定了一套标准,以利用现有资源的最佳要素。还表明,在插值阶段可以将空间和功能互补的地形数据源进行协同组合,以创建比单个数据源可以单独创建的更加可靠和准确的海拔模型。开发了一种新算法,用于沿不规则线将单个DEM数据集合并为无缝DEM镶嵌。为了完善DEM,讨论并展示了最新的遥感技术的潜力,其中包括阴影形状,SAR立体和干涉SAR(InSAR)。为未来的南极DEM制定了一项技术策略。用多种方法评估了所得南极DE​​M的准确性和错误模式。与不同比例的高分辨率卫星图像的比较表明,DEM不仅描述了广阔的地形构造和真实的冰层排水模式,而且还捕捉到了前所未有的地形表面细节。我们认为,该DEM产品代表了迄今为止发布的南极地形的最详细,最准确的数字描述。

著录项

  • 作者

    Liu, Hongxing.;

  • 作者单位

    The Ohio State University.;

  • 授予单位 The Ohio State University.;
  • 学科 Geography.;Physical Geography.
  • 学位 Ph.D.
  • 年度 1999
  • 页码 227 p.
  • 总页数 227
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

  • 入库时间 2022-08-17 11:48:20

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