Editorial

Abstract

Project GeoSim is a multidisciplinary effort by members of Virginia Tech's Departments of Geography and Computer Science, College of Education, and Learning Resources Center to develop computer-aided education (CAE) software for introductory geography and related classes. GeoSim laboratory exercises draw on the five fundamental themes of geography for their subject matter. The programs emphasize interactive learning combining the information capabilities of Geographic Information Systems (GIS) with the techniques of computer simulation. The result is a series of geographic explorations that will make available some of the most exciting aspects of geography to a potential audience of 425,000 introductory geography students per year.     

一种利用流形学习进行多影像匹配的方法

提出了一种利用流形学习方法进行多影像匹配的算法。通过两组宽基线序列影像的匹配实验,并与LE-SIFT方法、SVD-SIFT方法和基于局部线性映射的LLE-SVD方法进行了对比分析。结果表明,本文方法在获得多幅影像的共同匹配结果和利用多幅影像之间的约束实现两幅影像匹配的结果上都优于现有方法。     

Integration of Geospatial Science in Teacher Education

Abstract

One of the primary missions of our university is to train future primary and secondary teachers. Geospatial sciences, including GIS, have long been excluded from teacher education curriculum. This article explains the curriculum revisions undertaken to increase the geospatial technology education of future teachers. A general education class introducing geospatial technology to the general student body has been developed, a cartography class has been modified to provide applied geospatial experience explicitly for future teachers, and a service learning partnership with local K–12 schools has been established where students are working with teachers to integrate geospatial sciences in their academic programs.     

Learning Conservation: the role of conservation covenants in landscape redesign at Project Hindmarsh,Victoria

Biodiversity decline continues apace across the Australian landscape with a pressing need to redesign land use to address this situation. The significance of private land increasingly is recognised for the protection and enhancement of biodiversity as landholders inevitably make decisions that affect environmental quality. Biodiversity conservation is as much a social process as a physical one. Conservation covenants are perpetual agreements under which landholders choose to conserve land voluntarily, primarily for conservation purposes. The role covenants might play in landscape-scale conservation was investigated in north-western Victoria. In-depth interviews with a range of participants were undertaken, with an emphasis on the role covenantors might play as social learning and cultural change agents. Analysis of these interviews offers useful perspectives for understanding socio-cultural dimensions of landscape change and exploring the differing values of production farmers and nature conservation landholders. Consideration is then given to approaches to engaging local production farmers in nature covenants and promoting communication between this group and the largely non-production conservationists who currently form the mainstay of conservation covenants.     

Youth transitions and going to university: the perceptions of students attending a geography summer school access programme

This paper contributes to understandings of youth transitions in childhood and youth geographies through the use of a participatory diagramming exercise with students studying geography in a summer school access programme at a Scottish university. In particular, the paper explores young people's perceptions about adult/child binaries and their hopes and fears in applying to university. The discussion highlights the extended nature of youth transitions: the usefulness of participatory diagramming as a research method and teaching technique for this group; and the consequences that the increasing interest in childhood and youth geographies might have on teaching and learning in human geography.     

支持向量机及其在地震预报中的应用前景

统计学习理论(SLT)是研究小样本情况下机器学习规律的理论。支持向量机(SVM)基于统计学习理论,可以处理高度非线性分类和回归等问题,不但较好地解决了小样本、过学习、高维数、局部最小等实际难题,而且具有很强的泛化(预测)能力。本文介绍了支持向量机的分类、回归方法,分析了这一方法的特点,讨论了该方法在地震预报中的应用前景。     

Inter-organizational coordination in extreme events: The World Trade Center attacks, September 11, 2001

This paper addresses the problem of inter-organizational coordination in response to extreme events. Extreme events require coordinated action among multiple actors across many jurisdictions under conditions of urgent stress, heavy demand and tight time constraints. The problem is socio-technical in that the capacity for inter-organizational coordination depends upon the technical structure and performance of the information systems that support decision making among the participating organizations. Interactions among human managers, computers and organizations under suddenly altered conditions of operation are complex and not well understood. Yet, coordinating response operations to extreme events is an extraordinarily complex task for public and nonprofit managers. This paper will analyze the interactions among public, private and nonprofit organizations that evolved in response to the 11 September 2001 attacks, examining the relationships among organizations in terms of timely access to information and types of supporting infrastructure. The performance of the inter-organizational system is examined in the context of the events of 11 September 2001 from the theoretical perspective of complex adaptive systems. A model of auto-adaptation is proposed for implementation to improve inter- organizational performance in extreme events. This model is based on the concept of individual, organizational and collective learning in environments exposed to recurring risk, guided by a shared goal. Such a model requires public investment in the development of an information infrastructure that can support the intense demand for communication, information search, exchange and feedback that characterizes an auto-adaptive system.     

支持向量数据描述在西北暴雨预报中的应用试验

传统机器学习中通常隐含假设所研究问题是类别平衡的, 气象预报中预测灾害天气时就不满足这个假设, 这时往往需要预测重要而稀少的正类 (少数类)。传统机器学习以精度最大化为目标, 在遇到不平衡类别问题时, 容易训练出把所有实例都分为反类 (多数类) 的平庸的分类器。支持向量数据描述是从支持向量机 (SVM) 发展而来的基于核的机器学习方法, 只使用一类样本就可以工作, 适合于不平衡类别。以铜川暴雨预测作为试验对象, 对SVM和支持向量数据描述 (SVDD) 进行了对比试验。试验结果表明对于这个不平衡类别问题SVDD具有优势。     

Social geographies of learning disability: narratives of exclusion and inclusion

The social geographies of people with learning disabilities, one of the most marginalized groups in society, have largely been ignored. The paper explores these hidden geographies through the interpretation of narratives of people with learning disabilities in Scotland, within a social policy framework of social exclusion and inclusion. The paper interprets the experiences of being excluded from and included within mainstream socio-spaces, and the safe spaces that many people with learning disabilities have formed for themselves in between the positions of social exclusion and inclusion.     

Regional innovation strategies in the knowledge-based economy

This paper aims to examine major regional innovation strategies for regional development in the knowledge-based economy in Korea. Innovation policy and Regional Innovation Systems (RIS) are becoming important issues in Korea in both national and regional perspectives. These issues have been evolving since the mid 1990s, especially since the financial crisis of 1997 in Korea. Five major policy issues for promoting innovation and regional competitiveness are examined in this paper. The major policy issues are: promoting region-specific clustering; building habitats for innovation and entrepreneurship; collective learning processes and innovation networks; building a stock of social capital; and promoting local and global networks. Several strategies are suggested for each of these policy issues. These major policy issues and related strategies for regional innovation and competitiveness can be regarded as common issues required for the successful development of RIS. Taking these basic policy issues into account, each region can develop their own region-specific RIS, with appropriate consideration of distinctive regional characteristics such as the level of development, industrial specialization, local labor market, local business climate, local financial system, etc.