一种基于微博语义的天气情感地图设计

天气情感地图是一种表达情感相关的专题地图。本文提出了一种基于微博语义的天气情感地图设计方法,基于程序获取了合肥市区2016年6月20日至2016年7月10日暴雨期间带有地理位置的新浪微博数据,通过数据清洗及标准化处理,利用情感词库,结合人工判读,将暴雨天气过程相关情感微博文本数据分为8种情感类别,设计了8种情感着色,结合GIS格网技术与核密度分析方法,制成暴雨天气过程前、中后期情感地图,并分析了暴雨天气过程3个阶段中微博用户多维情感变化。该研究可为政府相关部门在突发性天气灾害过程中制定救助与决策提供参考。     

Modelling and predicting the spatial dispersion of skin cancer considering environmental and socio-economic factors using a digital earth approach

ABSTRACT

Almost all causative factors of diseases depend on location. The Digital Earth approach is suitable for studying diseases globally. Geospatial information systems integrated with statistical models can be used to model the relationship between a disease and its causative factors. Through modelling, the most important causative factors can be extracted and the epidemiology of the disease can be observed. In this paper, skin cancer (the most common type of cancer) has been modelled based on its causative factors, including climate factors, people's occupations, nutrition habits, socio-economic factors, and usage of chemical fertiliser. To fit the model, a data framework was first designed, and then data were gathered and processed. Finally, the disease was modelled using Generalised Linear Models (GLM), a statistical model based on the location of the factors. The results of this study identify the most important causative factors together with their relative priority. Furthermore, a model was used to predict the change in skin cancer occurrences caused by a change in one of its causative factors. This work illustrates the ability of the model to predict disease occurrence. Thus, by using this Digital Earth approach, skincancer can be studied in all the key countries around the world.     

Research on the security of national geospatial data clearinghouse based on ASP

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加拿大地理信息产业发展基础与现状研究

从地理信息管理、空间基础设施、地理信息产业发展情况等方面介绍了加拿大地理信息产业发展的现状,并分析加拿大地理信息产业发展的特点,提出促进我国地理信息产业健康快速发展的对策、建议。     

Extracting and analyzing semantic relatedness between cities using news articles

News articles capture a variety of topics about our society. They reflect not only the socioeconomic activities that happened in our physical world, but also some of the cultures, human interests, and public concerns that exist only in the perceptions of people. Cities are frequently mentioned in news articles, and two or more cities may co-occur in the same article. Such co-occurrence often suggests certain relatedness between the mentioned cities, and the relatedness may be under different topics depending on the contents of the news articles. We consider the relatedness under different topics as semantic relatedness. By reading news articles, one can grasp the general semantic relatedness between cities; yet, given hundreds of thousands of news articles, it is very difficult, if not impossible, for anyone to manually read them. This paper proposes a computational framework which can ‘read’ a large number of news articles and extract the semantic relatedness between cities. This framework is based on a natural language processing model and employs a machine learning process to identify the main topics of news articles. We describe the overall structure of this framework and its individual modules, and then apply it to an experimental dataset with more than 500,000 news articles covering the top 100 US cities spanning a 10-year period. We perform exploratory visualizations of the extracted semantic relatedness under different topics and over multiple years. We also analyze the impact of geographic distance on semantic relatedness and find varied distance decay effects. The proposed framework can be used to support large-scale content analysis in city network research.     

印度地理信息产业发展基础与现状研究

主要从地理信息资源生产管理体制、空间基础设施建设、产业政策3个方面分析了印度地理信息产业发展基础,并对当前印度地理信息产业规模、市场、企业、人才培养以及发展潜力等方面的现状进行了研究,对比我国分析了当前印度地理信息产业发展的优势和存在的制约。     

城市地理空间数据集成应用探讨

城市地理空间数据是表达城市地理要素的数量、质量、分布特征、相互关系、变化规律的位置信息和属性信息。分析城市地理空间数据的组成结构、组织管理、集成利用,并将这些数据有效应用于城市地理信息系统建设之中,将在城市信息化道路上起到举足轻重的作用。该文以开发的"兰州市城关区地理信息集成系统"为例,重点阐述了城市地理空间数据的构成与获取方式,研究了城市地理空间数据与业务部门数据的集成方法,并对城市地理空间数据在晕渲图制作、三维景观生成、数据可视化等主要应用上进行了分析和探讨。     

广东西江流域地名调查工作特点与实例分析

地名调查工作涉及地域划分,地理空间,语言文化,历史文化等方面,运用"3S"技术,结合当地语言文化开展此项工作,能提高调查工作效率和准确度,有利于对存在尚未掌握的地理实体及地名信息的判断、界定和甄别。通过广东郁南县地名调查工作实例,探讨在"3S"技术背景下,根据具有地域性文化特征地区的地名调查工作所呈现的新问题、新特点,可作范例为粤语地区的地名调查提供可操作性建议。     

面向地理空间框架建设的城市大比例尺数据整合改造研究与实践

城市大比例尺基础地理信息数据蕴含了丰富的信息,是其他信息空间化、标准化处理的基础和空间依据,是数字城市地理空间框架建设的重要组成部分。本文以福建省明溪县为例,讨论了城市大比例尺数据整合改造方法的研究,以及数据制作过程中所遇技术难题的解决办法,探索了一条高效可行的城市大比例尺数据改造方法。     

A land use/land cover change geospatial cyberinfrastructure to integrate big data and temporal topology

ABSTRACT

Big data have shifted spatial optimization from a purely computational-intensive problem to a data-intensive challenge. This is especially the case for spatiotemporal (ST) land use/land cover change (LUCC) research. In addition to greater variety, for example, from sensing platforms, big data offer datasets at higher spatial and temporal resolutions; these new offerings require new methods to optimize data handling and analysis. We propose a LUCC-based geospatial cyberinfrastructure (GCI) that optimizes big data handling and analysis, in this case with raster data. The GCI provides three levels of optimization. First, we employ spatial optimization with graph-based image segmentation. Second, we propose ST Atom Model to temporally optimize the image segments for LUCC. At last, the first two domain ST optimizations are supported by the computational optimization for big data analysis. The evaluation is conducted using DMTI (DMTI Spatial Inc.) Satellite StreetView imagery datasets acquired for the Greater Montreal area, Canada in 2006, 2009, and 2012 (534 GB, 60 cm spatial resolution, RGB image). Our LUCC-based GCI builds an optimization bridge among LUCC, ST modelling, and big data.