CAREER: Formalizing and Resolving Computational Intensity of Spatial Analysis to Establish a Cyber-GIS Framework

职业：形式化和解决空间分析的计算强度，以建立网络地理信息系统框架

• 批准号: 0846655
• 负责人: Shaowen Wang
• 金额: $ 47万
• 依托单位: University of Illinois at Urbana-Champaign
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-08-01 至 2015-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0846655&HistoricalAwards=false
• 关键词: CAREER; Formalizing; Resolving; Computational; Intensity

This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).Spatial analysis is essential to the acquisition, transformation, and use of spatial data, information, and knowledge for scientific discovery and decision-making in many fields (e.g., ecology, environmental science and engineering, geography, geosciences, public health, and social sciences). As the size of spatial data and complexity of relevant analysis approaches have significantly increased, spatial analysis has become much more computationally intensive and, as a result, conventional methods for spatial analysis are often intractable within desktop computing environments. Resolving the computational intensity of spatial analysis thus represents a tremendous challenge.Dr. Shaowen Wang, Assistant Professor at the University of Illinois Urbana-Champaign will begin at five-year CAREER award to study the computational intensity of various geospatial analyses that occur over a distributed, parallel processing network. Computational intensity is defined as the magnitude of computational requirements of a problem based on the evaluation of its computational complexity and characteristics of input and output. Cyberinfrastructure promises to resolve the computational intensity of spatial analysis and facilitate collaborative spatial problem-solving. This promise, however, depends on significant research and education advances yet to be made based on bridging the fields of cyberinfrastructure, Geographic Information Science (GIScience), and spatial analysis. The purpose of this project is, therefore, to enable computationally-intensive spatial analysis through a Cyber-Geographic Information Systems (GIS) framework that couples cyberinfrastructure, GIScience, and spatial analysis capabilities based on the development of new computational intensity theory and knowledge. In particular, the objectives of the project are three-fold: 1) formalize a novel theoretical construct -- computational intensity map by integrating the representations of spatial and computational domains to guide the development of efficient and generic methods and algorithms for parallel and distributed processing of spatial analysis; 2) create spatial middleware components to encapsulate parallel and distributed spatial analysis and manage the complexity of cyberinfrastructure for large-scale spatial problem-solving; and 3) enhance spatial analysis to support geospatial problems, numbers of collaborators, and the amount of cyberinfrastructure resources through a service-oriented approach. Dr. Wang will tightly integrate research and education through investigations into representative computationally-intensive spatial analysis methods, including geostatistical modeling, local spatial clustering detection, spatial interpolation, and spatially-explicit agent-based modeling. Education materials based on computational intensity maps, parallel and distributed spatial analysis methods and algorithms, and Cyber-GIS software will synergistically provide comprehensive support for training next-generation researchers, teachers, and students to solve computationally-intensive spatial problems.This project will transform the current state-of-play of the three fields GIScience, spatial analysis, and cyberinfrastructure, while creating a new subject domain of computational intensity. A novel theoretical approach to computational intensity will enhance spatial analysis methods integrated with cyberinfrastructure and GIS. The Cyber-GIS framework will be established by developing innovative algorithms and software components based on this approach. Both real and synthetic data within a science application context of discovering geographic patterns of global climate change impact on large-scale coupled human and natural systems will be used to evaluate this framework. The project will gain fundamental knowledge for coupling the capabilities of GIS, spatial analysis, and cyberinfrastructure and will, therefore, guide the development of emerging spatial cyberinfrastructure. While this project will outreach to underrepresented and minority groups as well as general public through an on-line Cyber-GIS platform, it holds a great promise to enable widespread scientific breakthroughs that are important to the nation and society.

该奖项是根据2009年美国复苏和再投资法案（公法111-5）资助的。空间分析对于许多领域（例如，生态学、环境科学和工程学、地理学、地球科学、公共卫生和社会科学）。随着空间数据的大小和相关分析方法的复杂性显著增加，空间分析已经变得更加计算密集，并且因此，用于空间分析的常规方法在桌面计算环境中通常是棘手的。解决空间分析的计算强度是一个巨大的挑战。Shaowen Wang博士，伊利诺伊大学香槟分校的助理教授，将开始在五年的CAREER奖，研究在分布式并行处理网络上发生的各种地理空间分析的计算强度。 计算强度定义为基于对问题的计算复杂性和输入输出特性的评价而确定的问题的计算需求的大小。网络基础设施有望解决空间分析的计算强度，促进协作空间问题的解决。然而，这一承诺取决于基于桥接网络基础设施、地理信息科学（GIScience）和空间分析领域的重大研究和教育进展。因此，该项目的目的是通过网络地理信息系统（GIS）框架实现计算密集型空间分析，该框架将网络基础设施，GIScience和基于新的计算强度理论和知识的空间分析能力结合起来。具体而言，该项目的目标有三个方面：1）通过整合空间域和计算域的表示来形式化一个新的理论结构-计算强度图，以指导空间分析的并行和分布式处理的高效和通用方法和算法的发展; 2）创建空间中间件组件，以封装并行和分布式空间分析，并管理网络基础设施的复杂性，以解决大规模空间问题;以及3）通过面向服务的方法，加强空间分析，以支持地理空间问题、合作者数量和网络基础设施资源的数量。王博士将通过调查代表性的计算密集型空间分析方法，将研究和教育紧密结合起来，包括地质统计建模，局部空间聚类检测，空间插值和基于空间显式代理的建模。基于计算密集型地图、并行和分布式空间分析方法和算法以及Cyber-GIS软件的教育材料将协同为培训下一代研究人员、教师和学生解决计算密集型空间问题提供全面支持。该项目将改变GIScience、空间分析和网络基础设施三个领域的现状，同时创造了一个新的计算强度的学科领域。计算强度的新理论方法将增强与网络基础设施和GIS相结合的空间分析方法。将根据这一方法开发创新算法和软件组件，从而建立网络地理信息系统框架。将使用科学应用背景下的真实的和合成数据来评估这一框架，科学应用背景是发现全球气候变化对大规模耦合的人类和自然系统影响的地理模式。该项目将获得将地理信息系统、空间分析和网络基础设施的能力结合起来的基本知识，因此将指导新兴空间网络基础设施的发展。虽然该项目将通过在线网络地理信息系统平台向代表性不足的少数群体和公众进行宣传，但它很有希望实现对国家和社会至关重要的广泛科学突破。