基于可见性预处理的地形模型视相关简化算法

提出了一种基于可见性预处理的点删除简化算法。该算法针对海量地形数据,首先建立了高效的空间索引系统,利用这一索引系统快速完成了视锥截取、背面剔除和隐藏面消除等可见性测试,再对预处理后的网格模型依据顶点曲率大小进行点删除简化。实验表明,采用可见性预处理可大大提高绘制速度,并且绘制帧速率基本独立于模型的复杂度。     

高速网上3维海量地形数据的实时交互浏览的实现

针对高速网上3维海量地形数据传输和显示特点，提出了一套海量地形数据处理、存储方法，包括数据的预处理和数据的存储结构，数据存储有利于高速网络访问；并根据人的视觉生理特征，提出了一种多分辨率地形表示模板形成，较好地处理了实时交互游览地形的真实感和巨大数据需求之间的冲突。设计了一种适合网络实时传输海量地形数据的传输协议，使系统充分利用网络带宽同时又不浪费带宽。通过在中国高速互联试验网络NFSCNet上的大量演示，表明所提出的技术方案是切实可行的，证明了高速网对3维海量地形实时交互浏览的必要性和可行性。     

地图综合软件AutoMap的界面设计

一个好的应用程序 ,不仅要有强大的功能 ,还要有美观实用的用户界面。到目前为止 ,在众多的图形软件中还没有产生一套专门进行地图自动化综合的软件 ,尽管不少地图软件 ,例如 Dyna GEN和 MAS,在某些环节不同程度地开发了一些综合功能模块 ,但都是单项的 ,缺乏完善的解决策略 ,与完全自动化还相距很远。作者试图从使软件会思考这一角度出发 ,结合人机工程学 ,开发出了更多的自动化综合模块 ,并且做出了一套软件 Auto Map。Auto Map是一个实用型的图形编辑与综合软件 ,它的重点在于对图形的编辑和综合操作。本文介绍了有关Auto Map界面设计的指导原则及其评价     

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.     

Promoting Lifelong Professional Development in Geography Education: International Perspectives on Developing the Scholarship of Teaching in Higher Education in the Twenty‐First Century*

Whereas the global march towards the professional development of geography teachers in schools was, perhaps, the major achievement in geography education of the twentieth century, promoting the professional development of faculty teaching geography in higher education is one of the major challenges that faces us in geography education for the twenty‐first century. What little educational development is currently provided for faculty teaching in universities is largely generic. There is a need for a disciplinary specific component in educational development, both for the initial training of faculty and for their continuing professional development. This article explores how the professional development of faculty is related to the international debate about developing the scholarship of teaching and learning in higher education. It reviews some recent initiatives, particularly from the United States and the United Kingdom, and examines the role of national associations and international networks in supporting faculty teaching geography in higher education. Some of the challenges involved in professionalizing teaching geography in higher education are discussed. The article ends with some suggestions for promoting lifelong professional development in geography in higher education nationally and internationally.     

Man–computer interactive method on cloud classification based on bispectral satellite imagery

A bispectral cloud classification method based on man-computer interactive way, i.e. a unit feature space clasification method (UFSCM), has been presented in this paper. Apart from land and water, six types of clouds including cumulonimbus, multilayer cloud system, thin / think cirrus, middle and low level clouds are recognized. The method has been tested by using more than two hundred samples, with total accuracy reaching 87.1%.     

Restructuring of Australian higher education: information technology in geography teaching and learning

Australian higher education has experienced substantial change since the early 1980s, with a transition to mass higher education, closer alignment to national political objectives, increasing Federal Government control, a growing emphasis on ‘quality’ and ‘value for money’, and organisational restructuring with manifestations ranging from the creation of the Unified National System to the merger or closure of individual departments. At the same time, evolving conceptions of learning and new patterns of demand, with growing emphasis on lifelong learning and flexible access to education, pose new challenges for educators. Now, the policies of the new Federal Coalition Government are likely to engender further change, with growing differentiation of universities a probable outcome. Information technology has so far played a relatively peripheral role in teaching and learning in higher education, but important changes there, including rapid shifts in the relationship between cost and computing power, and the explosive emergence of the World Wide Web, are now providing the basis on which information technology can become increasingly central to teaching and learning. Higher education is close to the limits of incremental adjustment to pressures for change and it seems likely that it will experience major restructuring, with its eventual reconstruction around the capabilities of information technology. Geography has already been much affected by restructuring pressures, including above‐average growth in teaching loads and threats to its disciplinary identity because of internal reorganisation of many universities. Despite a tradition of innovative, high‐quality teaching, geography has not generally been a leader in the development and application of information technology. Nevertheless, a case study of an experimental use of the World Wide Web provides an example of directions that teaching and learning in the discipline might take.     

基于多源数据和集成学习的城市住宅地价分布模拟——以武汉市为例

精准刻画城市住宅地价分布特征,对于科学引导城市空间布局规划、有效实现城市精明增长等具有重要意义。而城市住宅地价与其潜在影响因素之间的复杂非线性关系,给地价分布精细模拟带来了挑战。论文旨在探索基于地理大数据和集成学习的城市住宅地价分布模拟方法体系,以满足快速、精准监测地价动态变化的需要。选取武汉市为典型区,以住宅用地交易样点、兴趣点(points of interest, POI)和夜间灯光影像为数据源,以500 m分辨率网格为估价单元,提取POI核密度和夜间灯光强度作为住宅地价预测变量,采用机器学习算法和bagging、stacking集成方法构建住宅地价预测模型,并对比分析其精度。研究发现：① 单个机器学习算法中,支持向量回归(support vector regression, SVR)预测精度最高,接下来依次是k最近邻算法(k-nearest neighbor algorithm, k-NN)、高斯过程回归(Gaussian process regression, GPR)和BP神经网络(back propagation neural networks, BP-NN);② 在提升单个算法预测精度方面,stacking方法的性能优于bagging方法,使用stacking集成SVR和k-NN的地价预测模型精度最高,其平均绝对百分误差仅为8.29%,拟合优度R²达0.814;③ 基于论文所构建模型生成的城市住宅地价分布图能有效表征价格圈层分布特征和局部奇异性。研究结果可为城市住宅地价评估提供新的思路和方法借鉴。     

基于RNN的空气污染时空预报模型研究

针对空气污染物时间序列中包含缺失值以及现有时间序列预报模型缺乏对时序特征状态建模的问题,该文构建了基于缺失值处理算法和RNN(循环神经网络)的时空预报框架。对空气污染物时序数据设计了3种缺失值处理算法(前向递补、均值替代和权重衰减),用缺失标签和缺失时长对缺失值建模,并在此基础上搭建含有全连接层与LSTM层的深度循环神经网络(DRNN)用于时空预报。使用深度全连接神经网络(DFNN)作为DRNN的对照,用京津冀区域的空气质量和气象数据训练模型,并比较不同模型的预测精度。通过实验,比较了3种缺失值处理方法的效果,结果表明,LSTM在空气污染时空序列预测上的表现优于传统的全连接神经网络层,证实了提出的基于深度学习的时空预报框架的有效性。