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1.
Abstract

The multidimensional nature of many types of data in modern geography calls for creative and innovative approaches to their analysis. Statisticians have recently developed methods for exploring and visualizing large, multivariate datasets, but cartographers and geographers in general have only recently begun to integrate these methods for use with spatial and spatiotemporal datasets that are multivariate in character. This article will present an example of such an integration—an environment for visualization of health statistics—as a case study to demonstrate the philosophical and practical advantages of geovisualization systems for the exploration of complex spatiotemporal information. Emphasis is placed on the encouragement of creative thinking about geographic phenomena through the use of such data-rich graphical tools.

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2.
Spatiotemporal proximity analysis to determine spatiotemporal proximal paths is a critical step for many movement analysis methods. However, few effective methods have been developed in the literature for spatiotemporal proximity analysis of movement data. Therefore, this study proposes a space-time-integrated approach for spatiotemporal proximal analysis considering space and time dimensions simultaneously. The proposed approach is based on space-time buffering, which is a natural extension of conventional spatial buffering operation to space and time dimensions. Given a space-time path and spatial tolerance, space-time buffering constructs a space-time region by continuously generating spatial buffers for any location along the space-time path. The constructed space-time region can delimit all space-time locations whose spatial distances to the target trajectory are less than a given tolerance. Five space-time overlapping operations based on this space-time buffering are proposed to retrieve all spatiotemporal proximal trajectories to the target space-time path, in terms of different spatiotemporal proximity metrics of space-time paths, such as Fréchet distance and longest common subsequence. The proposed approach is extended to analyze space-time paths constrained in road networks. The compressed linear reference technique is adopted to implement the proposed approach for spatiotemporal proximity analysis in large movement datasets. A case study using real-world movement data verifies that the proposed approach can efficiently retrieve spatiotemporal proximal paths constrained in road networks from a large movement database, and has significant computational advantage over conventional space-time separated approaches.  相似文献   

3.
中国历史时期土地覆被数据集地理空间重建进展评述   总被引：3，自引：0，他引：3  
重建长时间序列具有空间属性的土地覆被数据集,对研究历史时期土地利用/土地覆被变化及其气候和生态效应具有重要意义。近年来,国内外学者就定量重建中国区域历史土地覆被数据集进行了积极探索。但由于历史时期土地利用数据来源多元、重建方法多样、验证方式各异等原因,不同学者的重建结果迥异,其中重建方法是导致差异形成的重要原因之一。本文从重建思路、假设和方法、结果验证等方面对覆盖中国区域的主要空间数据集进行了综合评述,结果表明：①基于历史记录的还原法和基于地理空间模型的重建法是历史土地覆被空间重建的主要方法,而根据建模过程,后者又可进一步分为“自上而下”的配置模型和“自下而上”的演化模型法。②基于数量重建进行空间重建是当前历史土地覆被数据集重建的主流,在缺少充分、客观历史数据的条件下,对基础数据、分布控制因素和限制因子进行合理假设是取得合理结果的重要条件。③为提高研究成果的解释力,需要对重建结果进行检验,直接验证法虽较为准确,但受时空尺度限制,具有显著的局限性,间接验证法可作为有效的补充。  相似文献   

4.
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5.
地理学时空数据分析方法   总被引：13，自引：4，他引：9  
随着地理空间观测数据的多年积累,地球环境、社会和健康数据监测能力的增强,地理信息系统和计算机网络的发展,时空数据集大量生成,时空数据分析实践呈现快速增长。本文对此进行了分析和归纳,总结了时空数据分析的7类主要方法,包括：时空数据可视化,目的是通过视觉启发假设和选择分析模型;空间统计指标的时序分析,反映空间格局随时间变化;时空变化指标,体现时空变化的综合统计量;时空格局和异常探测,揭示时空过程的不变和变化部分;时空插值,以获得未抽样点的数值;时空回归,建立因变量和解释变量之间的统计关系;时空过程建模,建立时空过程的机理数学模型;时空演化树,利用空间数据重建时空演化路径。通过简述这些方法的基本原理、输入输出、适用条件以及软件实现,为时空数据分析提供工具和方法手段。  相似文献   

6.
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.  相似文献   

7.
时空大数据背景下并行数据处理分析挖掘的进展及趋势   总被引：3，自引：3，他引：0  
关雪峰  曾宇媚 《地理科学进展》2018,37(10):1314-1327
随着互联网、物联网和云计算的高速发展,与时间、空间相关的数据呈现出“爆炸式”增长的趋势,时空大数据时代已经来临。时空大数据除具备大数据典型的“4V”特性外,还具备丰富的语义特征和时空动态关联特性,已经成为地理学者分析自然地理环境、感知人类社会活动规律的重要资源。然而在具体研究应用中,传统数据处理和分析方法已无法满足时空大数据高效存取、实时处理、智能挖掘的性能需求。因此,时空大数据与高性能计算/云计算融合是必然的发展趋势。在此背景下,本文首先从大数据的起源出发,回顾了大数据概念的发展历程,以及时空大数据的特有特征;然后分析了时空大数据研究应用产生的性能需求,总结了底层平台软硬件的发展现状;进而重点从时空大数据的存储管理、时空分析和领域挖掘3个角度对并行化现状进行了总结,阐述了其中存在的问题;最后指出了时空大数据研究发展趋势。  相似文献   

8.
There has been a resurgence of interest in time geography studies due to emerging spatiotemporal big data in urban environments. However, the rapid increase in the volume, diversity, and intensity of spatiotemporal data poses a significant challenge with respect to the representation and computation of time geographic entities and relations in road networks. To address this challenge, a spatiotemporal data model is proposed in this article. The proposed spatiotemporal data model is based on a compressed linear reference (CLR) technique to transform network time geographic entities in three-dimensional (3D) (x, y, t) space to two-dimensional (2D) CLR space. Using the proposed spatiotemporal data model, network time geographic entities can be stored and managed in classical spatial databases. Efficient spatial operations and index structures can be directly utilized to implement spatiotemporal operations and queries for network time geographic entities in CLR space. To validate the proposed spatiotemporal data model, a prototype system is developed using existing 2D GIS techniques. A case study is performed using large-scale datasets of space-time paths and prisms. The case study indicates that the proposed spatiotemporal data model is effective and efficient for storing, managing, and querying large-scale datasets of network time geographic entities.  相似文献   

9.
流空间是认识城市网络结构和演化的重要手段。近年来大数据的快速发展为流空间研究提供了新的机遇和挑战。论文系统综述了基于大数据的流空间研究进展。首先,论文梳理了基于大数据流空间研究的背景和历史,然后总结了基于大数据的流空间研究的主题、数据类型、方法和主要发现,最后展望了未来的研究挑战。2011年以后,基于大数据的流空间研究呈指数增长趋势,中英文论文年均发表量从2010年的11篇增长到2018年的106篇。大数据主要从提供新的数据源、激发新的分析方法和提供新的研究视角三方面推进了流空间研究。常用于流空间研究的大数据主要包括手机信令数据、社交媒体签到数据、公共交通刷卡数据和出租车轨迹数据,它们比传统统计数据更能直接提供人流、物流和信息流的时空动态信息。研究方法也从传统的基于距离的重力模型发展为网络分析方法。未来在交叉学科研究、大数据和传统数据的耦合、大数据与深度学习和云计算等新方法的结合方面仍需进一步探索,从理论、数据和方法上全面深化流空间研究。  相似文献   

10.
Due to the hybrid nature of material and digital spaces, more decisions are being made online that have a direct effect on offline actions. This is increasingly true for the locations where people are choosing to consume goods and services such as restaurants or retail outlets. The growth of the GeoWeb—personal data uploaded to certain Internet sites such as social media platforms—has established large databases showing the locations where people go during their daily lives for the purposes of consumption. One such repository is the social network, Foursquare, which people use to display their physical location to their friends, digitally. In looking more closely at datasets from Foursquare overlaid with information on racial characteristics in census tracts, a pattern emerges: predominantly African‐American tracts are increasingly left out of this type of online participation. This paper will compare Foursquare data from several U.S. cities to discuss the implications of being left off of social media platforms tied to economic activity. It is likely that these virtually invisible areas will have a direct impact on the economic vitality of their physical counterparts  相似文献   

11.
Pattern analysis techniques currently common within geography tend to focus either on characterizing patterns of spatial and/or temporal recurrence of a single event type (e.g., incidence of flu cases) or on comparing sequences of a limited number of event types where relationships between events are already represented in the data (e.g., movement patterns). The availability of large amounts of multivariate spatiotemporal data, however, requires new methods for pattern analysis. Here, we present a technique for finding associations among many different event types where the associations among these varying event types are not explicitly represented in the data or known in advance. This pattern discovery method, known as T-pattern analysis, was first developed within the field of psychology for the purpose of finding patterns in personal interactions. We have adapted and extended the T-pattern method to take the unique characteristics of geographic data into account and implemented it within a geovisualization toolkit for an integrated computational-geovisual environment we call STempo. To demonstrate how T-pattern analysis can be employed in geographic research for discovering patterns in complex spatiotemporal data, we describe a case study featuring events from news reports about Yemen during the Arab Spring of 2011–2012. Using supplementary data from the Global Database of Events, Language, and Tone, we briefly summarize and reference a separate validation study, then evaluate the scalability of the T-pattern approach. We conclude with ideas for further extensions of the T-pattern technique to increase its utility for spatiotemporal analysis.  相似文献   

12.
文章探讨了如何有效利用自发地理信息（Volunteered Geographic Information, VGI）大数据促进灾后恢复监测工作。首先概述了国内外VGI相关研究的发展现状,明确了VGI用于灾后恢复监测研究的不足,然后提出了一个基于VGI大数据的灾后恢复监测应用的研究框架,助力于灾后恢复监测各类具体恢复目标（如旅游业恢复、工商业恢复、生活常态恢复）的实现。该研究框架包含数据获取、数据质量控制和数据挖掘3个核心组成部分。其中,数据获取对象以VGI为主,以传统官方权威数据为辅;数据质量控制主要是通过模糊逻辑专家系统和人工神经网络（深度学习）确保VGI适用性;数据挖掘则是以变革式范例为理论基础,利用定量和定性结合的方法调查灾区基建、经济和安全3个灾后恢复主要方面的状态。最后,文章还讨论了当前利用VGI大数据促进灾后恢复监测所存在的一些局限性,包括VGI来源的可持续性问题、各VGI平台应用程序接口的数据获取限制问题和VGI应用所涉及的用户隐私问题。  相似文献   

13.
Travel activities are embodied as people’s needs to be physically present at certain locations. The development of Information and Communication Technologies (ICTs, such as mobile phones) has introduced new data sources for modeling human activities. Based on the scattered spatiotemporal points provided in mobile phone datasets, it is feasible to study the patterns (e.g., the scale, shape, and regularity) of human activities. In this paper, we propose methods for analyzing the distribution of human activity space from both individual and urban perspectives based on mobile phone data. The Weibull distribution is utilized to model three predefined measurements of activity space (radius, shape index, and entropy). The correlation between demographic factors (age and gender) and the usage of urban space is also tested to reveal underlying patterns. The results of this research will enhance the understanding of human activities in different urban systems and demographic groups, as well as providing novel methods to expand the important and widely applicable area of geographic knowledge discovery in the age of instant access.  相似文献   

14.
Linear features are represented on paper or digital maps with polyline geometries. Sampling, discretization, and generalization processes result in polylines of a length smaller than that of the actual features. In addition, semantics associated to the original line features may be lost. This becomes more significant for coarse sampling and/or high degree of generalization. This paper introduces a data structure that can alleviate this problem, by preserving the attributes and semantic characteristics associated to the original features in cartographic representation. The structure can handle both linear features and polygon outlines. Various compression methods have been examined. The structure has been implemented and tested with both synthetic and real datasets. Extensions to spatiotemporal features, like trajectories, have also been considered.  相似文献   

15.
Managing geophysical data generated by emerging spatiotemporal data sources (e.g. geosensor networks) presents a growing challenge to Geographic Information System science. The presence of correlation poses difficulties with respect to traditional spatial data analysis. This paper describes a novel spatiotemporal analytical scheme that allows us to yield a characterization of correlation in geophysical data along the spatial and temporal dimensions. We resort to a multivariate statistical model, namely CoKriging, in order to derive accurate spatiotemporal interpolation models. These predict unknown data by utilizing not only their own geosensor values at the same time, but also information from near past data. We use a window-based computation methodology that leverages the power of temporal correlation in a spatial modeling phase. This is done by also fitting the computed interpolation model to data which may change over time. In an assessment, using various geophysical data sets, we show that the presented algorithm is often able to deal with both spatial and temporal correlations. This helps to gain accuracy during the interpolation phase, compared to spatial and spatiotemporal competitors. Specifically, we evaluate the efficacy of the interpolation phase by using established machine-learning metrics (i.e. root mean squared error, Akaike information criterion and computation time).  相似文献   

16.
净初级生产力(NPP)是衡量碳循环、指导土地利用、评估生态安全、指示环境变化、反映粮食安全等的重要参量,其估算受模型构建机理和生态系统关键地表参数输入的影响。近年来,随着遥感数据的不断丰富和遥感处理技术的快速发展,集成遥感数据的NPP估算模型相较于仅采用气候、土壤等传统观测数据的非遥感模型,在分析时空异质性等方面的优势日益凸显。本文基于Web of Science和CNKI两大数据库,采用文献统计分析方法,系统回顾NPP研究概况及国内外集成遥感数据的NPP估算模型的近期进展;并将集成遥感数据进行NPP估算的模型分为统计模型、光能利用率模型、过程模型及耦合模型四类;重点阐述了各类遥感估算模型的机理、差异性、适宜性及局限性;最后,在分析NPP遥感估算面临困境和科学挑战的基础上,从机理与影响因素、数据基础、参数反演、时空尺度拓展、软硬件支撑等方面对未来研究进行了展望。  相似文献   

17.
全球历史森林数据中国区域的可靠性评估   总被引：2，自引：1，他引：2  
全球历史土地利用数据集对于深入理解全球或区域环境变化具有重要意义。历史森林数据作为其重要组成部分,在区域尺度上的可靠性至今鲜有评估。以中国区域为研究对象,依据中国学者基于历史文献资料重建的中国历史森林数据（CHFD）,采用趋势、数量和空间格局等对比法,对全球数据集（SAGE、PJ和KK10）中国森林数据的可靠性进行评估。结果表明：① 虽然全球数据集中国森林数据与CHFD在近300年的变化趋势上均呈减少态势,但数量上差异较大。其中,SAGE数据集对中国1700年以来的森林面积估算较CHFD高出约20%~40%;KK10数据集重建的1700-1850年森林数量则高出约32%~46%;而PJ数据集由于吸纳了区域性研究成果,其总量与CHFD较为接近,多数时点的数量差异低于20%。② 在省区尺度上,从总量与CHFD较为接近的PJ数据集来看,其与CHFD数据集森林变化趋势差异较大省区占到84%,而数量差异较大的省区占比高达92%。③ 在网格尺度上,PJ与CHFD数据集相对差异率> 70%的网格占比高达60%~80%,二者的时空动态格局差异明显。④ 全球数据集中国历史森林数据未能客观反映该区域森林变化的过程与格局特征,造成这一现象的原因在于全球与区域性数据集重建历史数据所依据的资料源不同,以及基于不同空间尺度构建的重建方法的差异等。  相似文献   

18.
“一带一路”若干区域社会发展态势大数据分析   总被引：1，自引：0，他引：1  
“一带一路”倡议已成为中国的基本国际政策,及时掌握沿线国家的社会发展态势,对确保该倡议的稳步推进与顺利实施至关重要。为此,论文将GDELT数据库作为数据来源,获取了“一带一路”沿线25个国家近5 a的英文新闻全文数据,引入主题模型,结合无监督方法(LDA)与监督方法(Labeled LDA)挖掘新闻数据中蕴含的主题,构建社会稳定度模型,分析各国社会发展态势。研究发现：① 沿线国家社会发展态势不均衡,可划分为4类,即稳定型,如阿曼、越南等;较稳定型,如乌兹别克斯坦、伊朗等;较高风险型,如科威特、约旦、巴基斯坦、缅甸;高风险型,如叙利亚、阿富汗等。② 通过新闻主题时空挖掘,可有效发现热点区域,例如论文发现安集延对中亚地区社会发展与稳定具有重要影响。③ 利用监督主题模型,能够发现乌兹别克斯坦经济产业结构,识别出重大社会事件,发现其社会安全风险及变化趋势。采用论文方法可有效挖掘新闻事件时空变化规律,发现各国潜在风险,支撑对沿线国家社会发展态势的实时动态监控,为“一带一路”倡议的实施提供辅助决策支持,具有重要的应用价值。  相似文献   

19.
了解城市人群移动行为和空间结构对城市规划、交通管理、应急响应等具有重要的意义。近年来,随着信息技术(ICT)的快速发展,采集大规模、长时间序列的人群移动定位大数据变得容易,为人群移动行为研究带来了新的机遇和挑战。本文首先介绍了目前用于城市人群移动行为和空间结构研究的主要数据源及其特征,并分别从人群移动行为、城市空间结构2个方面对近3年国内外相关研究进行归纳总结。目前的研究主要从移动定位大数据中挖掘人群移动模式,理解人群移动时空规律,进一步透视城市的空间结构特征;而对城市空间结构与人群移动行为影响的研究较少。未来可通过融合多源时空数据,综合研究人群移动行为与城市空间结构之间的相互作用,发展大规模群体移动行为时空分析理论和模型,进一步深入理解人群移动行为与城市空间结构的耦合关系。  相似文献   

20.
针对资料稀缺地区水文模拟计算难题,开展多源再分析降水数据在拉萨河流域应用对比研究,本文基于HIMS系统构建了拉萨河流域分布式水文模型,以气象站实测数据为参照,对比分析了中国区域地面降水格点日值数据集和中国区域高时空分辨率地面气象要素驱动数据集两套遥感再分析数据集的气象数据在拉萨河流域的径流模拟效果。结果表明：在日和月时间尺度上,气象站实测降水数据的径流模拟精度最好,驱动集降水数据径流模拟结果要好于网格点降水数据。总体上,基于气象站实测降水数据的径流模拟纳西效率系数为0.86(日过程)和0.93(月过程),相关系数均在0.9以上。基于两类再分析数据的降水径流模拟纳西效率系数均在0.7(日过程)和0.8(月过程)以上,相关系数均在0.9左右。对于资料稀缺地区,多源再分析降水数据是重要的可用数据来源。借助于降水—径流模型,探讨多源再分析降水数据对径流模拟精度的影响,是完善多源再分析降水数据产品质量的一个重要环节。  相似文献   

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