移动电子地图空间认知与信息传输的研究

移动电子地图是目前新发展起来的一种地图模式,并且越来越受到广大用户的欢迎。但是目前的信息传输理论不能够正确地指导这种地图模式的发展。文章分析了目前的信息传输模式,并结合用户对移动电子地图的新需求,提出了新的信息传输模式,以适应移动电子地图的发展。     

空间认知驱动的自适应路径引导

为了生成符合人们认知习惯、反映用户空间知识并易于利用自然语言表达的路径引导, 提出了一个将路径抽象为一系列结构统一、具有时序性和多粒度性且可以被加工为指导用户沿路径前进的短语或句子的指示单元的表达框架,并说明了利用环境结构、路径特征、先验知识等上下文因素生成多粒度的指示单元, 从中选择最合适的指示单元, 进而实现自适应路径引导的方法。通过与传统的采用“Distance-to-Turn”模式的路径引导进行对比可以发现, 基于空间认知的自适应路径引导更加符合人们描述路径的方式, 能够降低用户的认知压力并提高导航的效率。     

一种适于空间特征探测的三角网模型

对地理数据所隐含空间特征的探测是GIS理论研究和工程应用的关键问题之一。提出了一种基于Delaunay三角网的空间特征探测模型,该模型可用于点、线、面等多种几何类型的多种空间特征的探测,如点群目标的空间分布范围、分布密度和分布轴线探测,线目标的弯曲特征探测,多边形目标的瓶颈区域探测,多边形群的分组聚类特征探测等。实验证...     

移动电子地图空间认知与信息传输的研究

移动电子地图是目前新发展起来的一种地图模式,并且越来越受到广大用户的欢迎。但是目前的信息传输理论不能够正确地指导这种地图模式的发展。文章分析了目前的信息传输模式,并结合用户对移动电子地图的新需求,提出了新的信息传输模式,以适应移动电子地图的发展。     

极地驻留时间对认知功能的影响

记忆、空间认知等基本认知功能是影响考察人员能否在南极高寒、单调、孤立、封闭的极端环境下完成复杂任务的基础认知能力.关于极地驻留时间长短对认知功能的影响尚缺乏专门的研究.本文通过计算机记录反应时技术,追踪自度夏到越冬中期,中国南极第25次队长城站越冬人员短时再认、记忆搜索、空间认知能力随驻留时间延长发生的变化.结果表明:...     

基于地理信息可视化的空间认知研究

地理信息可视化是在地理数据库驱动下,以地图形式表达地理信息的过程,它是可视化表达的重要组成部分。从空间认知的角度,深入研究地理信息可视化的过程;结合地理信息可视化的特点,提出了空间地理信息的表现形式以及空间认知的基本模式。     

Editorial

Abstract

This paper describes the conservation of the first edition of the six-inches-to-one-mile Ordnance Survey maps of Ireland. It outlines the general problem of the acidity of paper on which nineteenth-century Ordnance Survey maps are printed and the peculiar problems of conserving a hand-coloured presentation set. Each stage in the process is described up to the final encapsulation of the maps in Melinex polyester film.     

农村劳动力转移就业环境认知研究体系与方法

根据行为地理学观点,通过农村劳动力转移就业决策过程分析,认为农村劳动力转移就业环境认知,是指农村劳动力面临多样化的就业地和就业环境,对其进行的环境外观感觉以及整体认识和综合解释过程。依据地理认知理论,构建了农村劳动力转移就业环境认知研究体系:基于目标与过程的转移就业环境认知研究;基于个体变量与群体文化因子的转移就业环境认知研究;转移就业环境认知层次(环境特征感知、环境对象认知、环境格局认知)研究。探讨了农村劳动力转移就业环境认知研究的基本方法:民族志方法、定量关系模型、时空路径等。可以预测,农村劳动力转移就业环境认知研究将促进混合研究路径的发展。     

Extracting urban landmarks from geographical datasets using a random forests classifier

ABSTRACT

Urban landmarks are of significant importance to spatial cognition and route navigation. However, the current landmark extraction methods mainly focus on the visual salience of landmarks and are insufficient for obtaining high extraction accuracy when the size of the geographical dataset varies. This study introduces a random forests (RF) classifier combining with the synthetic minority oversampling technique (SMOTE) in urban landmark extraction. Both GIS and social sensing data are employed to quantify the structural and cognitive salience of the examined urban features, which are available from basic spatial databases or mainstream web service application programming interfaces (APIs). The results show that the SMOTE-RF model performs well in urban landmark extraction, with the values of recall, precision, F-measure and AUC reaching 0.851, 0.831, 0.841 and 0.841, respectively. Additionally, this method is suitable for both large and small geographical datasets. The ranking of variable importance given by this model further indicates that certain cognitive measures – such as feature class, Weibo popularity and Bing popularity – can serve as crucial factors for determining a landmark. The optimal variable combination for landmark extraction is also acquired, which might provide support for eliminating the variable selection requirement in other landmark extraction methods.     

Cognitive effects of long-term residence in the Antarctic environment

This study examined whether prolonged residence in the Antarctica had a significant impact on cognitive performance. Participants were members of the 24th and 25th Chinese National Antarctic Research Expeditions. Cognitive performance was measured with tests designed to evaluate short-term recognition, memory search and spatial cognition, measured four times： January, March, April, and June 2010. Age was controlled as a covariate, and data were analyzed using repeated-measures ANOVA. The results revealed that subjects＇ short-term memory and recognition ability remained stable, while 82% of team members exhibited improved scores on a spatial cognitive ability test. These findings have important implications for furthering our understanding of cognitive functioning in extreme environments.