共查询到20条相似文献，搜索用时 31 毫秒
1.
Hui Yuan Qingquan Li Shih-Lung Shaw William H. K. Lam 《International journal of geographical information science》2018,32(6):1211-1246
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
2.
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
3.
Julian Hagenauer Marco Helbich 《International journal of geographical information science》2013,27(10):2026-2042
Spatial sciences are confronted with increasing amounts of high-dimensional data. These data commonly exhibit spatial and temporal dimensions. To explore, extract, and generalize inherent patterns in large spatiotemporal data sets, clustering algorithms are indispensable. These clustering algorithms must account for the distinct special properties of space and time to outline meaningful clusters in such data sets. Therefore, this research develops a hierarchical method based on self-organizing maps. The hierarchical architecture permits independent modeling of spatial and temporal dependence. To exemplify the utility of the method, this research uses an artificial data set and a socio-economic data set of the Ostregion, Austria, from the years 1961 to 2001. The results for the artificial data set demonstrate that the proposed method produces meaningful clusters that cannot be achieved when disregarding differences in spatial and temporal dependence. The results for the socio-economic data set show that the proposed method is an effective and powerful tool for analyzing spatiotemporal patterns in a regional context. 相似文献
4.
Zhanjun He Jiannan Cai Zhong Xie Qingfeng Guan Chao Yang 《International journal of geographical information science》2020,34(6):1162-1187
ABSTRACTSpatiotemporal association pattern mining can discover interesting interdependent relationships among various types of geospatial data. However, existing mining methods for spatiotemporal association patterns usually model geographic phenomena as simple spatiotemporal point events. Therefore, they cannot be applied to complex geographic phenomena, which continuously change their properties, shapes or locations, such as storms and air pollution. The most salient feature of such complex geographic phenomena is the geographic dynamic. To fully reveal dynamic characteristics of complex geographic phenomena and discover their associated factors, this research proposes a novel complex event-based spatiotemporal association pattern mining framework. First, a complex geographic event was hierarchically modeled and represented by a new data structure named directed spatiotemporal routes. Then, sequence mining technique was applied to discover the spatiotemporal spread pattern of the complex geographic events. An adaptive spatiotemporal episode pattern mining algorithm was proposed to discover the candidate driving factors for the occurrence of complex geographic events. Finally, the proposed approach was evaluated by analyzing the air pollution in the region of Beijing-Tianjin-Hebei. The experimental results showed that the proposed approach can well address the geographic dynamic of complex geographic phenomena, such as the spatial spreading pattern and spatiotemporal interaction with candidate driving factors. 相似文献
5.
A review of quantitative methods for movement data 总被引：1，自引：0，他引：1
Jed A. Long Trisalyn A. Nelson 《International journal of geographical information science》2013,27(2):292-318
6.
现代人文地理学的研究越来越多地关注人的时空行为,而获取个体在出行活动中的时空位置数据是研究人类时空行为的前提。受数据获取技术的限制,之前对时空行为的研究主要集中在室外空间。随着室内定位技术的出现和应用,这类研究由室外空间扩展至室内空间。室内定位技术和方法较多,但从数据的角度来看,根据数据获取中使用定位方法的不同,可将室内定位数据分为几何位置数据、指纹位置数据和符号位置数据3类。目前,基于室内定位数据的研究可以归结为以下4个方面,即：人在室内的时空分布、人在室内的移动模式、人在室内的行为习惯及属性推断、人与室内环境的交互作用。然而,总体上目前的研究还处于探索阶段,理论和方法体系尚未成熟。本文认为后续的研究中需要关注以下问题：①数据获取方面。相对于蓝牙、射频识别、红外等定位技术,“智能手机+WiFi”模式的定位系统具有覆盖范围广、成本低廉、无需专门设备支持、易与用户交互等优势,是一种最具应用前景的室内定位技术;②研究内容方面。时空行为特征的研究是基础,个体属性推断及个体与环境的相互作用形式和机理研究将是重点,多时空尺度数据融合分析是一种趋势;③科学伦理方面。室内定位涉及微观尺度人类活动的记录,隐私保护问题需要高度关注。 相似文献
7.
V. Nixon K. Stewart Hornsby 《International journal of geographical information science》2013,27(9):1289-1308
Geographic objects are characterized by having different durations of existence, or geolifespans. A typology based on the concept of a geolifespan is developed to model variations in the longevity of entities that are stored in geographic information systems. The typology consists of two upper-level classes: Persistent and Ephemeral. The Ephemeral class is composed of three subclasses: Temporary, Transient and Brief. The set of possible transitions between classes in the typology is described, capturing how objects can change from one class to another, e.g., from Temporary to Brief or from Transient to Persistent. A transition sequence models the geolifespan class(es) to which an object belongs over a period of time and captures the evolution of dynamic geographic objects with respect to their longevity. Geolifespan classes are applied to scenarios of spatial change as well as a geosensor network to illustrate their role in modelling geographic dynamics. 相似文献
8.
Shifen Cheng Peng Peng 《International journal of geographical information science》2020,34(9):1849-1872
ABSTRACT Missing data is a common problem in the analysis of geospatial information. Existing methods introduce spatiotemporal dependencies to reduce imputing errors yet ignore ease of use in practice. Classical interpolation models are easy to build and apply; however, their imputation accuracy is limited due to their inability to capture spatiotemporal characteristics of geospatial data. Consequently, a lightweight ensemble model was constructed by modelling the spatiotemporal dependencies in a classical interpolation model. Temporally, the average correlation coefficients were introduced into a simple exponential smoothing model to automatically select the time window which ensured that the sample data had the strongest correlation to missing data. Spatially, the Gaussian equivalent and correlation distances were introduced in an inverse distance-weighting model, to assign weights to each spatial neighbor and sufficiently reflect changes in the spatiotemporal pattern. Finally, estimations of the missing values from temporal and spatial were aggregated into the final results with an extreme learning machine. Compared to existing models, the proposed model achieves higher imputation accuracy by lowering the mean absolute error by 10.93 to 52.48% in the road network dataset and by 23.35 to 72.18% in the air quality station dataset and exhibits robust performance in spatiotemporal mutations. 相似文献
9.
Jin Xing Renee E. Sieber 《International journal of geographical information science》2016,30(3):573-593
ABSTRACTBig 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
10.
Sonja Pravilovic Donato Malerba 《International journal of geographical information science》2018,32(1):191-212
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
12.
把握人类活动的时空特征是地理学研究中探究人地关系、提升人类福祉的重要基础和核心内容,日益普及的Wi-Fi网络能够为此提供可靠的数据支持。为明确Wi-Fi数据融入地理学研究的切入点和发展方向,论文通过与GPS、手机信令、蓝牙等位置感应数据的比较,认为Wi-Fi数据具有更高的采样精度和更强的采样代表性,能够获取个体在室内外各类城市空间的连续活动轨迹,支撑精细尺度下的人类活动研究。通过系统梳理人群活动状态监测、个体间的社会关系识别、建筑物的功能识别和降低隐私泄露风险等方面的研究进展,认为Wi-Fi数据将会在基于实时动态人口数据的城市功能设施规划、融合多源数据的人地关系探究、以居民福祉为导向的宜居城市建设等方面具有应用前景,有望成为地理学研究人类活动的新支点。 相似文献
13.
地理事件作为描述地理过程的基本单元,逐渐成为地理信息科学（GIS）核心研究内容。由于受人类活动数据获取限制,GIS对地理事件的建模和分析主要关注事件所引起的地理空间要素变化及要素之间的相互影响与作用机制。然而,近年来随着基于位置服务数据（LBS）爆炸式的增长和人类活动大数据定量刻画手段的快速发展,地理事件对人类活动的影响以及公众对地理事件的网络参与度都引起了多个领域的广泛关注,对地理事件的时空认知、建模方法和分析框架提出了巨大的挑战。对此,本文首先深入分析了大数据时代地理事件的概念与分类体系;其次,基于地理事件的时空语义给出了基于图模型的事件数据建模,建立了事件本体及其次生或级联事件的“节点—边”表达结构,开展了事件自身时空演化及其前“因”后“果”的形式化描述;第三,从时空数据分析与挖掘的角度,给出了大数据时代地理事件建模与分析的整体框架,拟突破传统“地理实体空间”事件探测与分析方法的局限性,融合“虚拟空间”事件发现与传播模拟思路,实现多源地理大数据支撑下的面向地理事件的人类活动多尺度时空响应与区域差异分析;最后,本文以城市暴雨事件为例诠释了本文所提出的地理事件建模与分析方法,从城市和城市内部两个尺度进行了暴雨事件与人类活动的一致性响应及区域差异分析,得到了明确的结论,验证了前文分析框架的可行性与实用性。 相似文献
14.
Tetsuya Shoji 《Natural Resources Research》2008,17(3):155-165
A series of rainfalls observed in central Japan from noon on the 13th to midnight on the 14th, August 1999 (36 h), has been
analyzed by spatiotemporal variograms in order to reveal the continuity of rain precipitation in a 3-D space defined by geographic
coordinates and time. All instances of zero precipitation are considered, but have been treated as four different cases: case
0 excludes all zero data, case 1 includes a zero datum neighboring to each finite value, case 2 includes a zero neighboring
to each finite value and the next neighboring zero, and a fourth case (termed case A) includes all zeros. Hourly precipitation
has a statistical distribution best approximated by a Weibull model, and somewhat less well by a normal distribution, in all
four cases. A rectangular variogram of measured values of total precipitation shows that the best continuity appears approximately
along the N-S direction (the ranges given by directional variograms are 500 and 80 km in the N-S and W-E directions, respectively).
In contrast, temporally stacked rectangular variograms of hourly precipitation shows that the best continuity direction is
W-E in all cases (the ranges in case A are 50 and 100 km along the N-S and W-E directions, respectively). A spatial variogram
gives a spatial range independently of time, whereas a temporal variogram gives a temporal range. When geographic coordinates
are normalized by the spatial range (here 80 km given by the temporally stacked omnidirectional variogram in case A), and
time is normalized by the temporal range (here 7 h given by the spatially stacked temporal variogram), geographic coordinates
and time can be treated as equivalent variables. Consequently, a spatiotemporal variogram can be calculated along a given
direction in 3-D space using the normalized coordinates. The continuity direction of a series of rainfalls can be best understood
by display on a Wulff net, where each range value is written at a point corresponding to the direction. The direction of the
best continuity is N0°W+20° in the normalized space. A rectangular variogram in the normalized space, in which the horizontal
and vertical axes represent N-S direction and time, respectively, suggests that the series of heavy rainfalls examined here
had a continuity pattern that was elongated from west to east (the range values are 20–30 km and 100 km along N-S and W-E,
respectively), and that migrated from south to north with a speed of 30 km/h. 相似文献
15.
Alan Kwok Lun Cheung David O’sullivan Gary Brierley 《International journal of geographical information science》2013,27(4):580-605
The structure of computational spatial analysis has mostly built on data lattices inherited from cartography, where visualization of information takes priority over analysis. In these framings, spatial relationships cannot easily be encoded into traditional data lattices. This hinders spatial analysis that emphasizes how interactions among spatial entities reflect mutual inter-relationships. This paper explores how graph theoretic principles can support spatiotemporal analysis by enabling assessment of spatial and temporal relationships in landscape monitoring. 相似文献
16.
17.
To study the development of spatial and social behavior of preschool children, micro-level spatiotemporal data were collected for the first time in both spatial and social context using a novel behavioral coding system. These unique behavioral data enable us to explore the group-level, dynamic, spatial, and social patterns of preschool children's playing behavior from a hybrid geographic and social perspective. In this research, GIS and exploratory spatial data analysis (ESDA) techniques are employed together to study group-level spatial and social behavior emerging from children's everyday activities and interactions. ESDA with social weights is proposed to explore spatial and social patterns of preschool children's behavior at the same time. The results highlight the utility of this approach for studying the relationships between preschool children's playing behavior and preschool's environmental settings and the relationships between preschool children's personal activities and the formation of their social network space. 相似文献
18.
《Geografisk tidskrift / udgivet af Bestyrelsen for Det Kongelige danske geografiske selskab》2012,112(2):146-162
ABSTRACTOnline travel searches are important forms of travel virtual spaces. Previous studies have neglected to analyze the spatial features of the travel searches themselves, and the spatial heterogeneity of their influencing factors. In this study, a travel search index based on the Baidu index was established for analyzing travel searches. Meanwhile, a local spatial model was created for the linear features in order to discuss the spatiotemporal heterogeneity of the influencing factors. The results of this study indicated that travel searches have obvious spatial inequality, and economically developed regions had displayed advantages in the travel search network. The fitting results of the local model were found to be superior to global model. The number of attractions and the GDP of the origin were found to have promoting effects on the travel searches, whereas distances had shown inhibiting effects. These effects presented significant spatiotemporal heterogeneity. It was also found that within the travel search virtual space, the distance effects still existed, but the intensity was weaker than in the real space. The local spatial model for the linear features provided a new spatial analysis method for understanding the travel search network, as well as other types of networks (flow patterns). 相似文献
19.
Jonathan L. Goodall David R. Maidment 《International journal of geographical information science》2013,27(2):233-247
Despite a long history of synergy, current techniques for integrating Geographic Information System (GIS) software with hydrologic simulation models do not fully utilize the potential of GIS for modeling hydrologic systems. Part of the reason for this is a lack of GIS data models appropriate for representing fluid flow in space and time. Here we address this challenge by proposing a spatiotemporal data model designed specifically for large‐scale river basin systems. The data model builds from core concepts in geographic information science and extends these concepts to accommodate mathematical representations of fluid flow at a regional scale. Space–time is abstracted into three basic objects relevant to hydrologic systems: a control volume, a flux and a flux coupler. A control volume is capable of storing mass, energy or momentum through time, a flux represents the movement of these quantities within space–time and a flux coupler insures conservation of the quantities within an overall system. To demonstrate the data model, a simple case study is presented to show how the data model could be applied to digitally represent a river basin system. 相似文献
20.
Dasymetric Spatiotemporal Interpolation 总被引：2，自引：0，他引：2
Jeremy Mennis 《The Professional geographer》2016,68(1):92-102
This research applies the principles of dasymetric mapping to spatiotemporal interpolation by extending the spatial concepts of zone and area to their temporal analogs of interval and duration, respectively. An example application of dasymetric spatiotemporal interpolation using crime event data is presented. Results indicate that dasymetric spatiotemporal interpolation significantly improves the accuracy of estimates over areal or duration weighting. In addition, even when dasymetric interpolation in either the spatial or temporal dimension is relatively weak, combining dasymetric estimation in both space and time dimensions simultaneously has the potential to amplify the accuracy of the overall dasymetric estimation. 相似文献