National Center for Geographic Information and Analysis

Abstract

Abstract. The growth of the remote sensing field has caused and explosion in the size and complexity of Earth satellite image databases. The explosion of data is already challenging current satellite-based GIS databases. New technologies for information management will be required in the future to maintain these large geographically-oriented systems created by projects such as NASA's Earth Observing System (EOS). This paper presents a technology adapted from the planning/scheduling field in Artificial Intelligence (AI) that promises to automate and facilitate the process of creating and storing satellite images and their associated data products.     

The National Science Foundation National Center for Geographic Information and Analysis

Abstract

The National Science Foundation will soon establish a National Center devoted to geographical research and education based on geographical information systems (GIS). The Center will be located at a university chosen on the basis of competitive proposals that will be evaluated primarily on the quality of their research agendas. The winning institution will be expected to involve government agencies and private firms in Center operations and programmes, and it will be expected to serve the national GIS community. The Center arose from a suggestion made by a member of the GIS research community. A large-scale database initiative and a Foundation commitment to Science and Technology Centers provided an institutional environment hospitable to the Center. There are similarities and differences in the approach taken toward GIS research, policy and applications in the United Kingdom (UK) and in the United States (US). Those similarities and differences offer promising topics for collaborative research on GIS itself and on GIS as an information technology affecting the discipline of geography. Cross-national UK-US research would be a productive step toward the globalization of GIS and GIS research.     

The research plan of the National Center for Geographic Information and Analysis

Abstract

In August 1988 the U.S. National Science Board established a National Center for Geographic Information and Analysis. This paper, which is adapted from the proposal of the successful consortium, describes a multi-year research agenda built around the recognition of impediments to the successful application of geographical information systems technology. The impediments range in nature from technical to institutional and are organized into five major areas: spatial analysis and spatial statistics, spatial databases, artificial intelligence and expert systems, visualization, and social and economic issues. The Center's research programme consists of a series of initiatives in specific areas, which are designed to last for periods of up to two years and to address the removal of recognized impediments.     

Using a Computational Grid for Geographic Information Analysis: A Reconnaissance

High performance computing has undergone a radical transformation during the past decade. Though monolithic supercomputers continue to be built with significantly increased computing power, geographically distributed computing resources are now routinely linked using high‐speed networks to address a broad range of computationally complex problems. These confederated resources are referred to collectively as a computational Grid. Many geographical problems exhibit characteristics that make them candidates for this new model of computing. As an illustration, we describe a spatial statistics problem and demonstrate how it can be addressed using Grid computing strategies. A key element of this application is the development of middleware that handles domain decomposition and coordinates computational functions. We also discuss the development of Grid portals that are designed to help researchers and decision makers access and use geographic information analysis tools.     

Research in Geographic Learning: A Special Task Force Report to the National Council for Geographic Education

Abstract

The videotape and other technological innovations are powerful tools for enhancing classroom learning. Teachers can fall into the trap of simply turning on the VCR while students watch with unstimulated and unchallenged minds. This article offers a technique that engages students in active, reflective thought by utilizing the National Geographic Society videotape, Connections. Using the videotape narrative prior to viewing provides students with opportunities to become critical consumers of technology.     

数字城市框架下地理信息服务语义分析

构建数字城市服务公共平台,能够有效地解决异源异构数据共享的问题,实现地理信息互操作。该文以数字城市服务公共平台下的地理信息服务为例,基于本体论,利用属性枚举的语义表达方法构建地理信息服务本体,以明确且形式化的方法描述服务语义,力图解决地理信息服务语义共享的问题。最后给出数字城市公共平台部分地理信息服务的形式化语义描述,在Protégé软件中完成地理信息服务本体的构建,同时结合HermiT1.3.4实现推理过程,并以地理编码服务为例构建了一组本体结构。     

我国地理信息产业的发展现状及思考

文章讨论了地理信息和地理信息产业的涵义,以及发展我国地理信息产业的重要性,对我国地理信息产业的现状进行了思考与分析,并提出了建议。认为我国地理信息产业面临机遇与挑战,通过扶持国产GIS软件,制定空间数据标准和交换格式标准,扩大地理信息技术服务的应用领域,珍惜人才,重视教育,我国的地理信息产业将有很大的发展空间。     

地理信息标准一致性测试建模

为避免自然资源与地理空间基础信息库中标准体系之间出现不必要的交叉、重复乃至矛盾,确定标准之间的一致性实现程度,利用软件自动完成一致性测试并给出可信的测试结果,已成为地理信息标准化的关键问题.该文应用MVC三层体系架构,构建了一种新型地理信息标准一致性测试过程模型(GIS-CTM),设计了前置处理器和后置处理器两个客户端,通过测试问卷形式完成从ATS到可执行测试套件的转变过程,实现了测试准备、测试分析、测试结果判定及测试报告生成等功能.该模型为测试体系规定了方法和框架,保证测试结果具有足够的可信度,进而保证标准体系之间的协调一致,支持了自然资源和地理空间基础信息库的标准化建设.     

地理信息系统学科中几个基本问题探讨

地理信息科学(GISci)尚不成熟,但中国地理信息系统(GIS)高等教育发展快速,因此GIS学科发展面临许多问题和挑战。尝试从哲学本体论、认识论和方法论角度探讨GIS学科中的几个基本问题:现实世界、概念世界、数字世界、空间认知、空间表达、空间分析与研究方法,同时从社会实践角度总结了GIS应用中的组织、管理与社会问题。1)系统总结地理空间、空间认知与信息表达的关系以及地理信息的基本特征;2)回顾GIS的概念与内涵演变,论证GIS概念的多样性与同一性,分析了几个代表性的GIS研究方向;3)在回顾地理学研究范式转变的基础上,探讨空间分析、知识产生过程以及基于GIS的地理学研究范式;4)辨析GIS与组织管理间的关系、GIS与社会间的互动关系,特别强调发展中国家GIS应用面临的问题。建议围绕“空间认知与表达”、“GIS方法论”、“GIS、组织与社会”进行跨学科研究,完善GIS学科体系。     

信息技术与地理教学整合初探

随着新一轮课程改革的实施,其基本理念之一就是要充分考虑信息技术对地理教学的影响,从而营造有利于学生形成地理信息意识和能力的教学环境.本文试从信息技术与地理教学整合的的途径、方法两个方面进行初步的探讨.     

自发地理信息在灾后恢复监测中的应用研究框架

文章探讨了如何有效利用自发地理信息（Volunteered Geographic Information, VGI）大数据促进灾后恢复监测工作。首先概述了国内外VGI相关研究的发展现状,明确了VGI用于灾后恢复监测研究的不足,然后提出了一个基于VGI大数据的灾后恢复监测应用的研究框架,助力于灾后恢复监测各类具体恢复目标（如旅游业恢复、工商业恢复、生活常态恢复）的实现。该研究框架包含数据获取、数据质量控制和数据挖掘3个核心组成部分。其中,数据获取对象以VGI为主,以传统官方权威数据为辅;数据质量控制主要是通过模糊逻辑专家系统和人工神经网络（深度学习）确保VGI适用性;数据挖掘则是以变革式范例为理论基础,利用定量和定性结合的方法调查灾区基建、经济和安全3个灾后恢复主要方面的状态。最后,文章还讨论了当前利用VGI大数据促进灾后恢复监测所存在的一些局限性,包括VGI来源的可持续性问题、各VGI平台应用程序接口的数据获取限制问题和VGI应用所涉及的用户隐私问题。     

Establishing a framework for Open Geographic Information science

When conducting research within a framework of Geographic Information Science (GISc), the scientific validity of this work can be argued as highly dependent upon the extent to which the methods employed are reproducible, and that, in the strictest sense, can only be fully achieved by implementing transparent workflows that utilize both open source software and openly available data. After considering the scientific implications of non-reproducible methods, we provide a review of both open source Geographic Information Systems (GIS) and openly available data, before describing an integrated model for Open GISc. We conclude with a critical review of this embryonic paradigm, with directions for future development in supporting spatial data infrastructure.     

基于主题相关度的地理信息Web服务爬虫研究

针对通用搜索引擎对于地理信息Web服务检索存在的不足,提出了一种基于主题相关度的服务爬虫方法,利用向量空间模型表示主题特征,通过引入特征值权重的计算方法分析页面内容与主题的相关度,过滤与主题无关的页面;并利用改进的PageRank算法从URL和锚文本两方面分析链接的重要性,优化爬取队列。实验表明,该方法在服务检索效率和抓取能力上都取得了良好的效果。