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1.
Mapping collective human activity in an urban environment based on mobile phone data 总被引：1，自引：0，他引：1
Identifying and characterizing variations of human activity – specifically changes in intensity and similarity – in urban environments provide insights into the social component of those eminently complex systems. Using large volumes of user-generated mobile phone data, we derive mobile communication profiles that we use as a proxy for the collective human activity. In this article, geocomputational methods and geovisual analytics such as self-organizing maps (SOM) are used to explore the variations of these profiles, and its implications for collective human activity. We evaluate the merits of SOM as a cross-dimensional clustering technique and derived temporal trajectories of variations within the mobile communication profiles. The trajectories’ characteristics such as length are discussed, suggesting spatial variations in intensity and similarity in collective human activity. Trajectories are linked back to the geographic space to map the spatial and temporal variation of trajectory characteristics. Different trajectory lengths suggest that mobile phone activity is correlated with the spatial configuration of the city, and so at different times of the day. Our approach contributes to the understanding of the space-time social dynamics within urban environments. 相似文献
2.
Simon Scheider Mark D. Huisjes 《International journal of geographical information science》2019,33(1):28-54
A most fundamental and far-reaching trait of geographic information is the distinction between extensive and intensive properties. In common understanding, originating in Physics and Chemistry, extensive properties increase with the size of their supporting objects, while intensive properties are independent of this size. It has long been recognized that the decision whether analytical and cartographic measures can be meaningfully applied depends on whether an attribute is considered intensive or extensive. For example, the choice of a map type as well as the application of basic geocomputational operations, such as spatial intersections, aggregations or algebraic operations such as sums and weighted averages, strongly depend on this semantic distinction. So far, however, the distinction can only be drawn in the head of an analyst. We still lack practical ways of automation for composing GIS workflows and to scale up mapping and geocomputation over many data sources, e.g. in statistical portals. In this article, we test a machine-learning model that is capable of labeling extensive/intensive region attributes with high accuracy based on simple characteristics extractable from geodata files. Furthermore, we propose an ontology pattern that captures central applicability constraints for automating data conversion and mapping using Semantic Web technology. 相似文献
3.
Florian Heinz Ralf Hartmut Güting 《International journal of geographical information science》2018,32(9):1737-1769
Moving object databases are designed to store and process spatial and temporal object data. An especially useful moving object type is a moving region, which consists of one or more moving polygons suitable for modeling the spread of forest fires, the movement of clouds, spread of diseases and many other real-world phenomena. Previous implementations usually allow a changing shape of the region during the movement; however, the necessary restrictions on this model result in an inaccurate interpolation of rotating objects. In this paper, we present an alternative approach for moving and rotating regions of fixed shape, called Fixed Moving Regions, which provide a significantly better model for a wide range of applications like modeling the movement of oil tankers, icebergs and other rigid structures. Furthermore, we describe and implement several useful operations on this new object type to enable a database system to solve many real-world problems, as for example collision tests, projections and intersections, much more accurate than with other models. Based on this research, we also implemented a library for easy integration into moving objects database systems, as for example the DBMS Secondo (1) (2) developed at the FernUniversität in Hagen. 相似文献
4.
It is possible to obtain vast amounts of spatiotemporal data related to human activities to support the study of human behavior and social evolution.In this context,geography,with the human-nature relationship as its core,is undergoing a transition from strictly earth observations to the observation of human activities.Geocomputation for social science is one manifestation thereof.Geocomputation for social science is an interdisciplinary approach combining remote sensing techniques,social science,and big data computation.Driven by the availability of spatially and temporally expansive big data,geocomputation for social science uses spatiotemporal statistical analyses to detect and analyze the interactions between human behavior,the natural environment,and social activities;Remote sensing(RS)observations are used as primary data.Geocomputation for social science can be used to investigate major social issues and to assess the impact of major natural and societal events,and will surely be an area of focused development in geography in the near future.We briefly review the background of geocomputation in the social sciences,discuss its definition and disciplinary characteristics,and highlight the main research foci.Several key technologies and applications are also illustrated with relevant case studies of the Syrian Civil War,typhoon transits,and traffic patterns. 相似文献
5.
地理计算是地理信息科学的核心内容之一, 主要研究地理信息科学的方法学问题, 内容 包括建模、算法、计算体系和一般方法学问题。本文介绍了地理计算的五个前沿问题: (1)地学数据 挖掘从地理学问题出发, 对各种数据作地理学的模型处理和结果计算以发现地理知识; (2)空间运 筹在地理学中的应用日益广泛, 它的算法更加简单严密、精度也更高; (3)多自主体系统模拟已经 成为地理学科学研究中除归纳和演绎之外的第三种重要研究方法; (4) 离散空间的定性计算是进 行地理空间计算的必要基础; (5)本体论的发展是地理信息科学乃至整个地理学发展的需要。 相似文献
6.
Yukio Sadahiro 《Transactions in GIS》2021,25(1):534-550
This article proposes a new method for analyzing the spatial expansion and shrinkage of point patterns. Spatial expansions of epidemic diseases and market areas are represented as the expansions of point patterns when disease cases and store customers are represented as points. The spatial expansion and shrinkage have been studied in many scientific fields. Existing analytical methods, however, are not sufficient for treating complicated spatiotemporal patterns. To answer this demand, this article develops a new method for analyzing the expansion and shrinkage of points. Three vector measures evaluate the degree and direction of expansion and shrinkage as functions of location and time. They are visualized as vector maps, which are valid for capturing the global spatiotemporal pattern as well as for discussing the local variation. Summary measures of these vectors allow us to grasp the overall spatiotemporal pattern efficiently. To test the validity of the proposed method, this article applies it to the analysis of visitors to Shinjuku and Ginza in Tokyo. The proposed measures permitted us to evaluate the spatiotemporal pattern of the visitors in detail and to consider its underlying structure from various perspectives, which indicated the soundness of the technique. 相似文献
7.
Claire Jarvis 《International journal of geographical information science》2013,27(7):1214-1215
Conventionally, a raster operation that needs to scan the entire image employs only one scanning order (i.e., single scanning order (SSO)), and the scan usually runs from upper left to lower right and row by row. We explore the idea of alternately applying multiple scanning orders (MSO) to raster operations that are based on the local direction, using the flow accumulation (FA) calculation as an example. We constructed several FA methods based on MSO, and compared them with those widely used methods. Our comparison includes experiments over digital elevation models (DEMs) of different landforms and DEMs of different resolutions. For each DEM, we calculated both single-direction FA (SD-FA) and multi-direction FA (MD-FA). In the theoretical aspect, we deducted the time complexity of an MSO sequential algorithm (MSOsq) for FA based on empirical equations in hydrology. Findings from the experiments include the following: (1) an MSO-based method is generally superior to its counterpart SSO-based method. (2) The advantage of MSO is more significant in the SD-FA calculation than in the MD-FA calculation. (3) For SD-FA, the best method among the compared methods is the one that combines the MSOsq and the depth-first algorithm. This method surpasses the commonly recommended dependency graph algorithm, in both speed and memory use. (4) The differences between the compared methods are not sensitive to specific landforms. (5) For SD-FA, the advantage of MSO-based methods is more obvious in a higher DEM resolution, but this does not apply to MD-FA. 相似文献
8.
由于技术发展和地理学内部计量革命的兴起,自动化地理学在20世纪80年代的欧美国家应运而生,20世纪90年代逐渐被地理计算学取代。自动化地理学是指通过对一系列自动化工具和技术的综合选择和使用,研究空间现象,解决地理问题。自动化地理学一经提出,引起诸多学者的关注和反响。对其审视和批判的角度丰富多样,包括技术、学术、应用、社会政治等多个视角。这些评论和观点促使我们从不同的角度理解在数字环境下的地理表达及其产生的社会结果,也从概念和技术上为自动化地理学的发展提供了推动力。同时,对于我国GIS学科和地理学的发展也有深刻的借鉴意义。 相似文献
9.
旅游集散地规划的地计算模型及案例 总被引：13，自引：1，他引：12
从地计算的角度出发,分析了地计算在旅游集散地规划中的问题,以江西上饶为例,运用可计算模型对旅游地域系统规划中的旅游中心集散地选择问题,旅游服务设施区位以及宾馆床位数的最优化问题进行了研究。这些问题的共同特征是它们是区域规划性质的、地理学的,而不是建筑学的景点景观设计。研究发现,地计算对于提高规划水平,是有效的,同时表明一般的空间分析问题,可以建立可计算模型。所有模型采用Visual Basic6.0(VB)编写程序实现计算,程序中调用了GIS软件中的MapObjects2.0控件实现地理显示、分析功能。这一工作显示VB与GIS软件结合,可以获取强大的空间分析功能。 相似文献
10.
Michael J. Widener Neal C. Crago Jared Aldstadt 《International journal of geographical information science》2013,27(9):1707-1723
As geospatial researchers' access to high-performance computing clusters continues to increase alongside the availability of high-resolution spatial data, it is imperative that techniques are devised to exploit these clusters' ability to quickly process and analyze large amounts of information. This research concentrates on the parallel computation of A Multidirectional Optimal Ecotope-Based Algorithm (AMOEBA). AMOEBA is used to derive spatial weight matrices for spatial autoregressive models and as a method for identifying irregularly shaped spatial clusters. While improvements have been made to the original ‘exhaustive’ algorithm, the resulting ‘constructive’ algorithm can still take a significant amount of time to complete with large datasets. This article outlines a parallel implementation of AMOEBA (the P-AMOEBA) written in Java utilizing the message passing library MPJ Express. In order to account for differing types of spatial grid data, two decomposition methods are developed and tested. The benefits of using the new parallel algorithm are demonstrated on an example dataset. Results show that different decompositions of spatial data affect the computational load balance across multiple processors and that the parallel version of AMOEBA achieves substantially faster runtimes than those reported in related publications. 相似文献