国际经济地理学研究的知识图谱分析

基于Web of Science核心数据库收录的1982－2020年7 260篇期刊论文及其参考文献,借助CiteSpace绘制国际经济地理学的知识图谱,梳理该领域的知识基础、研究热点和研究前沿。结果发现：1）知识基础的演进轨迹遵循了新区域主义——制度、社会、文化、演化转向的时序变化,21世纪以来,关系、演化经济地理学下的经典文献成为主要的知识来源。2）研究热点突出,创新和增长始终是研究核心,近年来韧性、全球生产网络、金融地理、全球城市、不平等、企业家精神等成为新的研究热点。3）研究前沿具有较强的问题导向,主要基于西方发达国家的产业发展实践。4）研究空间呈现英美主导的两级格局,大部分国家仍处于边缘地带。5）国际经济地理学呈现明显的数字转向、可持续转型趋势,新冠疫情对学科走向也有一定影响。借鉴国际研究经验,中国经济地理学应加强理论创新并提出具有中国实践特色的理论体系,同时推动多学科之间的交叉融合并加强从社会学视角解读社会经济活动的地理学意义。     

基于CiteSpace和VOSviewer的国内半城市化研究可视化分析

随着新型城镇化和国土空间规划工作的推进,半城市化地区的科学发展与治理已成为城乡融合发展的重要环节。基于文献计量分析方法,运用CiteSpace和VOSviewer可视化工具,对近30年来国内半城市化研究进行知识图谱分析。结果表明：1）作者与机构研究力量分散,地域分布特征明显;2）研究热点聚焦于分析北京、广州、上海等发达城市的土地利用、景观格局、失地农民、影响因素等问题,其内容可聚类为形态特征、空间界定、驱动机制、协调发展4类主题;3）半城市化研究发展经历了3个阶段,研究区域从东南沿海向内陆转移,内容从定性理论分析向定量实证探讨转化,视角也由自然特性分析向社会发展研究转变,体现出更多人文关怀。最后,从半城市化地区空间范围界定、人居环境建设、农业转移人口市民化路径探讨和基本公共服务均等化实施4个方面进行展望,旨在为中国半城市化地区的发展提供参考。     

国外儿童地理学研究进展与启示

20世纪70至80年代,在地理学“空间转向”的背景下,国外儿童地理学研究兴起。2003年Children’s Geographies诞生,成为儿童地理学的旗帜性刊物,标志着儿童地理学的发展进入新阶段。借助可视化工具,系统梳理国外儿童地理学研究的核心主题、研究热点以及研究方法。研究发现：（1）国外儿童地理学的科研人员、科研机构以及研究所属区域都呈现高度集中性,欧美国家占据主导地位;（2）核心研究主题包括移民与流动身份、伦理与地区差异、教育与青年志向、童年与多元空间以及游戏与情感体验等;（3）亚洲儿童地理研究成为近期研究热点,聚焦于“跨国儿童移民”以及“亚洲青年教育及就业问题”两部分;（4）研究方法历经探索期、发展期、繁盛期以及信息技术广泛应用时期的演进,技术手段随时代发展不断更新。     

Bayesian area-to-point kriging using expert knowledge as informative priors

Area-to-point (ATP) kriging is a common geostatistical framework to address the problem of spatial disaggregation or downscaling from block support observations (BSO) to point support (PoS) predictions for continuous variables. This approach requires that the PoS variogram is known. Without PoS observations, the parameters of the PoS variogram cannot be deterministically estimated from BSO, and as a result, the PoS variogram parameters are uncertain. In this research, we used Bayesian ATP conditional simulation to estimate the PoS variogram parameters from expert knowledge and BSO, and quantify uncertainty of the PoS variogram parameters and disaggregation outcomes. We first clarified that the nugget parameter of the PoS variogram cannot be estimated from only BSO. Next, we used statistical expert elicitation techniques to elicit the PoS variogram parameters from expert knowledge. These were used as informative priors in a Bayesian inference of the PoS variogram from BSO and implemented using a Markov chain Monte Carlo algorithm. ATP conditional simulation was done to obtain stochastic simulations at point support. MODIS (Moderate Resolution Imaging Spectroradiometer) atmospheric temperature profile data were used in an illustrative example. The outcomes from the Bayesian ATP inference for the Matérn variogram model parameters confirmed that the posterior distribution of the nugget parameter was effectively the same as its prior distribution; for the other parameters, the uncertainty was substantially decreased when BSO were introduced to the Bayesian ATP estimator. This confirmed that expert knowledge brought new information to infer the nugget effect at PoS while BSO only brought new information to infer the other parameters. Bayesian ATP conditional simulations provided a satisfactory way to quantify parameters and model uncertainty propagation through spatial disaggregation.     

基于引文网络的Cyberspace研究进展

以Web of Science数据库收录的有关研究Cyberspace的大量文献为数据源,采用文献计量学的分析方法,借助信息可视化软件CiteSpace Ⅱ对所采集的数据进行统计分析;获取1993 ～2013年检索数据,通过可视化图谱的方法挖掘出该领域的研究重点和学科分布;从地理学角度,揭示了该领域的研究热点和方向.     

知识经济条件下的高校图书馆文献信息服务

知识经济时代文献信息资源是知识创新的源泉，信息服务业成为知识经济的先导产业。以高校高科技产业为例，说明了高校图书馆要立足于知识经济社会，只有拓宽文献信息服务的内容，同时为教学、科研服务，发展高科技产业。并对知识经济时代的高校图书馆文献信息服务提出了一些建议。     

知识经济时代图书馆人力资源的开发与管理

在知识经济条件下，如何提高图书馆人力资源开发与管理的质量，调动广大图书工作者的积极性发挥他们的创造力，将直接影响到图书馆的发展和服务能力。     

EXPLORING SPATIAL FAMILIARITY*

Spatial familiarity is a natural language concept that has no well-defined technical interpretation. We explore here some possible dimensions of the concept, provide subjective measurements of the dimensions, and evaluate their independence. The four dimensions examined are locational knowledge, visual recognition, name identification, and interaction frequency. We suggest that both cognitive and behavioral dimensions are embedded in the concept of spatial familiarity and must be part of the meaning of the concept and of any attempt to make it operational.     

Centrifuge modelling of landslides and landslide hazard mitigation: A review

Landslides are serious geohazards that occur under a variety of climatic conditions and can cause many casualties and significant economic losses. Centrifuge modelling, as a representative type of physical modelling, provides a realistic simulation of the stress level in a small-scale model and has been applied over the last 50 years to develop a better understanding of landslides. With recent developments in this technology, the application of centrifuge modelling in landslide science has significantly increased. Here, we present an overview of physical models that can capture landslide processes during centrifuge modelling. This review focuses on (i) the experimental principles and considerations, (ii) landslide models subjected to various triggering factors, including centrifugal acceleration, rainfall, earthquakes, water level changes, thawing permafrost, excavation, external loading and miscellaneous conditions, and (iii) different methods for mitigating landslides modelled in centrifuge, such as the application of nails, piles, geotextiles, vegetation, etc. The behaviors of all the centrifuge models are discussed, with emphasis on the deformation and failure mechanisms and experimental techniques. Based on this review, we provide a best-practice methodology for preparing a centrifuge landslide test and propose further efforts in terms of the seven aspects of model materials, testing design and equipment, measurement methods, scaling laws, full-scale test applications, landslide early warning, and 3D modelling to better understand the complex behaviour of landslides.     

区域地质调查文本中文命名实体识别

作为我国地质调查领域最重要的数据源之一,地质调查报告中蕴含着丰富的地学知识及地质体描述等关键信息,准确高质量地抽取地质命名实体为地学知识图谱构建、知识推理及知识演化提供基础。笔者等在阐述地质命名实体识别任务基础上,分析地质实体不仅包含大量专业术语,还存在实体嵌套、大量长实体等领域特性,进一步增加了地质命名实体识别难度。笔者等提出一种基于轻量级预训练模型(ALBERT)—双向长短时记忆网络(BiLSTM)—条件随机场(CRF)模型的地质命名实体识别方法。首先利用ALBERT对输入字符上下文特征进行建模,并采用BiLSTM对其进行进一步上下文特征表征,最后采用CRF实现标注序列预测。实验结果表明,在构建的地质命名实体识别数据集上,相比于主流的命名实体识别模型算法,本文所提出的方法具有更好的抽取性能,提出的命名实体识别模型能为领域实体识别提供借鉴,同时为地学领域实体关系抽取和地学知识图谱构建提供有力方法支撑。