Collaborative Research: Integration of Geographic Complexity and Dynamics in Geographic Information Systems

协作研究：地理信息系统中地理复杂性和动态性的集成

• 批准号: 0416208
• 负责人: May Yuan
• 金额: $ 8.58万
• 依托单位: University of Oklahoma Norman Campus
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-08-01 至 2007-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0416208&HistoricalAwards=false
• 关键词: Collaborative; Research; Integration; Geographic; Complexity

While the infinite complexity and dynamics of geographic worlds have long been recognized in the geographic information science (GIScience) literature, current geographic information systems (GIS) technology has not yet incorporated data models, query functions, or analytic tools that can adequately handle geographic complexity and dynamics. This research project aims to integrate these features into GIS data models, query, and analysis. Such integration will lay a foundation for the next generations of GIS technology to further empower GIS support for scientific understanding and discovery of geographic worlds. To achieve this integration, the investigators will examine geographic complexity and dynamics. The basic premise is that geographic conceptualizations need to go beyond separate field- and object-based views of geographic worlds. The investigators will focus on geographic complexity that arises from the interwoven properties of fields and objects embedded in phenomena and relationships at different spatial and temporal scales. They will consider geographic dynamics that reflect on propagation and evolution in space and time as analyzed by Lagrangian (focusing on the stationary action of flows) or Hamiltonian (focusing on the motion of a particle of mass) dynamics. Field- or object-based conceptualization alone cannot capture complexity and dynamics critical to an accurate representation of geography. The investigators will incorporate two additional views of geographic worlds: fields of objects (o-fields) and objects of fields (f-objects) to incorporate geographic complexity and dynamics. They therefore expect to extend the dual geographic conceptualization to a spectrum of objects, f-objects, o-fields, and fields, with scale and resolution are as functions that allow a shift in perspective along the spectrum. With the spectrum of geographic conceptualizations, they will develop a data model that incorporates geographic complexity and dynamics with uncertainty, formulates queries and analytical functions, and builds a prototype system for proof of concepts.The collaborative project brings together researchers from the University of Oklahoma, University of California-Santa Barbara, and University of Utah to expand on their work on geospatial data modeling. In separate ventures, they have examined the use of combined fields and objects on geographic representation and demonstrated that such combination effectively extends geographic representation to incorporate much richer, more complex geographic semantics. Central to the research project is the idea of modeling GIS data based on geographic complexity and dynamics, as an alternative to the conventional data models that are built upon how data are captured. The research project promises a broader, more comprehensive inspection of issues related to the integration of fields and objects and the development of a holistic theory of the representation of geographic complexity and dynamics. This new approach to GIS data modeling extends static representation to a complex and dynamic view of the world and thus enhances GIS technology to be better suited for scientific research.

虽然地理信息科学 (GIScience) 文献早已认识到地理世界的无限复杂性和动态性，但当前的地理信息系统 (GIS) 技术尚未纳入能够充分处理地理复杂性的数据模型、查询功能或分析工具和动态。 该研究项目旨在将这些功能集成到 GIS 数据模型、查询和分析中。 这种集成将为下一代 GIS 技术奠定基础，进一步增强 GIS 对地理世界的科学理解和发现的支持。 为了实现这种整合，研究人员将检查地理复杂性和动态。 基本前提是地理概念化需要超越地理世界的单独的基于场和基于对象的视图。 研究人员将重点关注不同时空尺度的现象和关系中嵌入的场和对象的交织特性所产生的地理复杂性。他们将考虑反映空间和时间传播和演化的地理动力学，如拉格朗日（专注于流动的静止作用）或哈密顿（专注于质量粒子的运动）动力学分析。 仅基于场或基于对象的概念化无法捕获对于地理的准确表示至关重要的复杂性和动态。 研究人员将结合地理世界的两个附加视图：对象场（o-fields）和场对象（f-objects），以纳入地理复杂性和动态性。 因此，他们希望将双重地理概念化扩展到一系列物体、f 物体、o 场和场，其尺度和分辨率是允许沿该频谱变换视角的函数。 通过地理概念化的范围，他们将开发一个数据模型，将地理复杂性和动态性与不确定性相结合，制定查询和分析函数，并构建用于概念验证的原型系统。该合作项目汇集了来自俄克拉荷马大学的研究人员，加州大学圣巴巴拉分校和犹他大学扩大了他们在地理空间数据建模方面的工作。 在不同的项目中，他们研究了地理表示中组合字段和对象的使用，并证明这种组合有效地扩展了地理表示，以纳入更丰富、更复杂的地理语义。 该研究项目的核心是基于地理复杂性和动态性对 GIS 数据进行建模的想法，作为基于数据捕获方式构​​建的传统数据模型的替代方案。 该研究项目有望对与领域和对象整合相关的问题进行更广泛、更全面的检查，并发展地理复杂性和动态表示的整体理论。 这种新的 GIS 数据建模方法将静态表示扩展到复杂且动态的世界视图，从而增强 GIS 技术，使其更适合科学研究。