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Identifying stops from mobile phone location data by introducing uncertain segments 总被引：1，自引：0，他引：1 
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下载免费PDF全文 Zhiyuan Zhao Ling Yin Shih‐Lung Shaw Zhixiang Fang Xiping Yang Fan Zhang 《Transactions in GIS》2018,22(4):958-974
Identifying stops is a primary step in acquiring activity‐related information from mobile phone location data to understand the activity patterns of individuals. However, signal jumps in mobile phone location data may create “fake moves,” which will generate fake activity patterns of “stops‐and‐moves.” These “fake moves” share similar spatiotemporal features with real short‐distance moves, and the stops and moves of trajectories (SMoT), which is the most extensively used stop identification model, often fails to distinguish them when the dataset has coarse temporal resolution. This study proposes the stops, moves, and uncertainties of trajectories (SMUoT) model to address this issue by introducing uncertain segment analysis to distinguish “fake moves” and real short‐distance moves. A real mobile phone location dataset collected in Shenzhen, China is used to evaluate the performance of SMUoT. We find that SMUoT improves the performance (i.e., 15 and 19% increase in accuracy and recall rate for a one‐hour temporal resolution dataset, respectively) of stop identification and exhibits high robustness to parameter settings. With a better reliability of “stops‐and‐moves” pattern identification, the proposed SMUoT can benefit various individual activity‐related research based on mobile phone location data for many fields, such as urban planning, traffic analysis, and emergency management. 相似文献
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This paper outlines exploratory research undertaken by the “A New Sense of Place?” Project in Bristol, UK, into the potential new, location sensitive, computing technologies may have for enhancing urban children's socio‐spatial practices. The paper describes a series of workshops held with children in which mapping activities and use of the technologies are supported by the use of a Geographic Information System (GIS). The paper suggests that sound‐enabled GIS could play a major role in the management of such technologies. 相似文献
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This article studies the analysis of moving object data collected by location‐aware devices, such as GPS, using graph databases. Such raw trajectories can be transformed into so‐called semantic trajectories, which are sequences of stops that occur at “places of interest.” Trajectory data analysis can be enriched if spatial and non‐spatial contextual data associated with the moving objects are taken into account, and aggregation of trajectory data can reveal hidden patterns within such data. When trajectory data are stored in relational databases, there is an “impedance mismatch” between the representation and storage models. Graphs in which the nodes and edges are annotated with properties are gaining increasing interest to model a variety of networks. Therefore, this article proposes the use of graph databases (Neo4j in this case) to represent and store trajectory data, which can thus be analyzed at different aggregation levels using graph query languages (Cypher, for Neo4j). Through a real‐world public data case study, the article shows that trajectory queries are expressed more naturally on the graph‐based representation than over the relational alternative, and perform better in many typical cases. 相似文献
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Because SQL for querying data from spatial databases is ineffective, the query based on natural or visual language becomes an attractive research field gradually. However, how to define and represent natural languages related to spatial data are still gigantic problems. Because existing models of direction relations can't describe by use of some common concepts. First of all, detailed direction relations are proposed to describe the directions related to the interior of spatial objects, such as “east part of a region”, “east boundary of a region”, and so on. Secondly, by integrating the detailed directions with exterior direction relations and topological relations, several NLSRs are defined, such as “a road goes across the east part of a lake”, “a river goes along the east boundary of a province”, etc. Finally, based on the NLSRs abovementioned, a natural spatial query language (NSQL) is formed to retrieve data from spatial databases. 相似文献
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《制图学和地理信息科学》2013,40(2):107-116
GPS-based pedestrian navigation systems have become increasingly popular. Different interface technologies can be used to communicate/convey route directions to pedestrians. This paper aims to empirically study the influence of different interface technologies on spatial knowledge acquisition in the context of GPS-based pedestrian navigation. A field experiment was implemented to address this concern. Firstly, the suitability of the evaluation methods in assessing spatial knowledge acquisition was analyzed empirically (focusing on the ability of differentiating “familiar” and “unfamiliar” participants). The suitable methods were then used to compare the influence of mobile maps, augmented reality, and voice on spatial learning. The field test showed that in terms of spatial knowledge acquisition, the three interface technologies led to comparable results, which were not significantly different from each other. The results bring some challenging issues for consideration when designing mobile pedestrian navigation systems. 相似文献
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Access to GIS data from mobile platforms continues to be a challenge and there is a wide range of fields where it is extremely useful. In this work, we combined three key aspects: climate data sensors, mobile platforms and spatial proximity operations. We published and made use of a web 2.0 network of climate data, where content is user‐collected, by means of their meteorological stations, and exposed as available information for the virtual community. Moreover, we enriched this data by giving the users the opportunity to directly inform the system with different climate measures. In general, management of this type of information from a mobile application could result in an important decision tool, as it enables us to provide climate‐related data according to a context and a geographical location. Therefore, we implemented a native mobile application for iPhone and iPad platforms by using ArcGIS SDK for iOS and by integrating a series of ArcGIS webmaps, which allows us to perform geospatial queries based on the user's location, offering, at the same time, access to all the data provided by the climate data sensor network and from direct users. 相似文献
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Dave Kolas 《Transactions in GIS》2008,12(Z1):5-18
Though the intersection of spatial data and semantic web technologies holds significant promise, there are still many challenges before this promise can be realized. One of these challenges is query representation. History suggests that an appropriate solution is a specialized query language for spatial data; however, with a broad interpretation of the SPARQL specification and extensions that would be useful outside the spatial realm, one can use SPARQL to query spatial concepts effectively. This article establishes a set of desiderata for a query language capable of dealing with spatial Semantic Web‐based data, discusses the challenges facing such a query language, and addresses these challenges with straightforward solutions that are broadly applicable. The effectiveness of these extensions is demonstrated using example queries. 相似文献
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随着云计算、物联网、移动通信、移动互联网等技术的发展,研发智能化、多维度、全方位的旅游管理信息系统,已成为旅游信息化的发展趋势。本文以青岛八大关为例,综合利用基于位置与多传感器的跟踪注册技术、瓦片地图技术、三维景观地图技术和移动增强现实系统虚实叠加技术,研究并实现了面向旅游业的移动化、信息化、智能化、个性化的智能旅游服务系统,为游客提供认知周围景观的全新视角,获得全新的交互体验。系统包括三维景观地图、虚拟漫游、路线导航、环境识别、历史建筑查询、热力图显示、好友足迹、个人轨迹、微信分享等功能模块,游客在享受旅途的同时可以获得更加智能便捷的服务。 相似文献
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When individuals of a species utilize an environment, they generate movement patterns at a variety of spatial and temporal scales. Field observations coupled with location technologies (e.g. GPS tags) enable the capture of detailed spatio‐temporal data regarding these movement patterns. These patterns contain information about species‐specific preferences regarding individual decision‐making, locational choices and the characteristics of the habitat in which the animal resides. Spatial Data Mining approaches can be used to extract repeated spatio‐temporal patterns and additional habitat preferences hidden within large spatially explicit movement datasets. We describe a method to determine the periodicity and directionality in movement exhibited by a migratory bird species. Results using a High Arctic‐nesting Svalbard Barnacle Goose movement data yielded undetected patterns that were secondarily corroborated with expert field knowledge. Individual revisits by the geese to specific locations in the breeding and wintering grounds of Svalbard, Norway and Solway, Scotland, occurred with a periodicity of 334 days . Further, the orientation of this movement was detected to be mostly north‐south. During long‐range migration the geese use the north‐south oriented Norwegian islands as “stepping stones”, Short‐range movement between mudbank roosts to feeding fields in Solway also retained a north‐south orientation. 相似文献
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Despite their increasing popularity in human mobility studies, few studies have investigated the geo‐spatial quality of GPS‐enabled mobile phone data in which phone location is determined by special queries designed to collect location data with predetermined sampling intervals (hereafter “active mobile phone data”). We focus on two key issues in active mobile phone data—systematic gaps in tracking records and positioning uncertainty—and investigate their effects on human mobility pattern analyses. To address gaps in records, we develop an imputation strategy that utilizes local environment information, such as parcel boundaries, and recording time intervals. We evaluate the performance of the proposed imputation strategy by comparing raw versus imputed data with participants’ online survey responses. The results indicate that imputed data are superior to raw data in identifying individuals’ frequently visited places on a weekly basis. To assess the location accuracy of active mobile phone data, we investigate the spatial and temporal patterns of the positional uncertainty of each record and examine via Monte Carlo simulation how inaccurate location information might affect human mobility pattern indicators. Results suggest that the level of uncertainty varies as a function of time of day and the type of land use at which the position was determined, both of which are closely related to the location technology used to determine the location. Our study highlights the importance of understanding and addressing limitations of mobile phone derived positioning data prior to their use in human mobility studies. 相似文献
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In this work we investigate the effectiveness of different types of visibility models for use within location‐based services. This article outlines the methodology and results for our experiments, which were designed to understand the accuracy and effects of model choices for mobile visibility querying. Harnessing a novel mobile media consumption and authoring application called Zapp, the levels of accuracy of various digital surface representations used by a line of sight visibility algorithm are extensively examined by statistically assessing randomly sampled viewing sites across the 1 km2 study area, in relation to points of interest (POI) across the University of Nottingham campus. Testing was carried out on three different surface models derived from 0.5 m LiDAR data by visiting physical sites on each surface model with 14 random point of interest masks being viewed from between 10 and 16 different locations, totalling 190 data points. Each site was ground‐truthed by determining whether a given POI could be seen by the user and could also be identified by the mobile device. Our experiments in a semi‐urban area show that choice of surface model has important implications for mobile applications that utilize visibility in geospatial query operations. 相似文献
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Recently, increasing numbers of mobile phones are appearing on the market that feature advanced navigation capabilities: embedded GPS receivers for global positioning, integrated digital compasses for detecting the heading of the device, or accelerometer‐based tilt sensors will potentially enable upcoming and future mobile phones to measure their location and orientation in 3D space. In this paper, we present an application framework for building spatially aware mobile applications – applications that visualize, process or exchange geospatial information – on mobile phones equipped with such features. The core component of the framework is a novel, platform‐independent XML data exchange format for the interface between application server and mobile device that describes the geographic vicinity of the user. The format enables a variety of new mobile interaction styles and user interface types – from traditional text‐based local search and information interfaces to innovative real‐time user interfaces like Geo‐Wands and Smart Compasses. 相似文献
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With the wide use of laser scanning technology, point cloud data collected from airborne sensors and terrestrial sensors are often integrated to depict a complete scenario from the top and ground views, even though points from different platforms and sensors have quite different densities. These massive point clouds with various structures create many problems for both data management and visualization. In this article, a hybrid spatial index method is proposed and implemented to manage and visualize integrated point cloud data from airborne and terrestrial scanners. This hybrid spatial index structure combines an extended quad‐tree model at the global level to manage large area airborne sensor data, with a 3‐D R‐tree to organize high density local area terrestrial point clouds. These massive point clouds from different platforms have diverse densities, but this hybrid spatial index system has the capability to organize the data adaptively and query efficiently, satisfying the requirements for fast visualization. Experiments using point cloud data collected from the Dunhuang area were conducted to evaluate the efficiency of our proposed method. 相似文献
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We introduce a novel scheme for automatically deriving synthetic walking (locomotion) and movement (steering and avoidance) behavior in simulation from simple trajectory samples. We use a combination of observed and recorded real‐world movement trajectory samples in conjunction with synthetic, agent‐generated, movement as inputs to a machine‐learning scheme. This scheme produces movement behavior for non‐sampled scenarios in simulation, for applications that can differ widely from the original collection settings. It does this by benchmarking a simulated pedestrian's relative behavioral geography, local physical environment, and neighboring agent‐pedestrians; using spatial analysis, spatial data access, classification, and clustering. The scheme then weights, trains, and tunes likely synthetic movement behavior, per‐agent, per‐location, per‐time‐step, and per‐scenario. To prove its usefulness, we demonstrate the task of generating synthetic, non‐sampled, agent‐based pedestrian movement in simulated urban environments, where the scheme proves to be a useful substitute for traditional transition‐driven methods for determining agent behavior. The potential broader applications of the scheme are numerous and include the design and delivery of location‐based services, evaluation of architectures for mobile communications technologies, what‐if experimentation in agent‐based models with hypotheses that are informed or translated from data, and the construction of algorithms for extracting and annotating space‐time paths in massive data‐sets. 相似文献
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One of the fundamental issues of geographical information science is to design GIS interfaces and functionalities in a way that is easy to understand, teach, and use. Unfortunately, current geographical information systems (including ArcGIS) remains very difficult to use as spatial analysis tools, because they organize and expose functionalities according to GIS data structures and processing algorithms. As a result, GIS interfaces are conceptually confusing, cognitively complex, and semantically disconnected from the way human reason about spatial analytical activities. In this article, we propose an approach that structures GIS analytical functions based on the notion of “analytical intent”. We describe an experiment that replaces ArcGIS desktop interface with a conversational interface, to enable mixed‐initiative user‐system interactions at the level of analytical intentions. We initially focus on the subset of GIS functions that are relevant to “finding what's inside” as described by Mitchell, but the general principles apply to other types of spatial analysis. This work demonstrates the feasibility of delegating some spatial thinking tasks to computational agents, and also raises future research questions that are key to building a better theory of spatial thinking with GIS. 相似文献
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Blogs, micro‐blogs and online forums underpin a more interconnected world. People communicate ever more and are increasingly keen to explain and illustrate their lives; showing where they are and what they are doing. Desktop, online and mobile mapping landscapes have never been as rich or diverse yet this challenges cartography to adapt and remain relevant in the modern mapping world. We explore the spatial expression and potential value of micro‐blogging and Twitter as a social networking tool. Examples of “twitter maps” are reviewed that leverage the Twitter API and online map services to locate some component of the “tweet”. Scope, function and design are illustrated through development of two proof‐of‐concept map mashups that support collaborative real‐time mapping and the organisation and display of information for mass user events. Through the experiments in using and organising data in this way we demonstrate the value of “cartoblography”– a framework for mapping the spatial context of micro‐blogging. 相似文献
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Geo‐SOM is a useful geovisualization technique for revealing patterns in spatial data, but is ineffective in supporting interactive exploration of patterns hidden in different Geo‐SOM sizes. Based on the divide and group principle in geovisualization, the article proposes a new methodology that combines Geo‐SOM and hierarchical clustering to tackle this problem. Geo‐SOM was used to “divide” the dataset into several homogeneous subsets; hierarchical clustering was then used to “group” neighboring homogeneous subsets for pattern exploration in different levels of granularity, thus permitting exploration of patterns at multiple scales. An artificial dataset was used for validating the method's effectiveness. As a case study, the rush hour motorcycle flow data in Taipei City, Taiwan were analyzed. Compared with the best result generated solely by Geo‐SOM, the proposed method performed better in capturing the homogeneous zones in the artificial dataset. For the case study, the proposed method discovered six clusters with unique data and spatial patterns at different levels of granularity, while the original Geo‐SOM only identified two. Among the four hierarchical clustering methods, Ward's clustering performed the best in pattern discovery. The results demonstrated the effectiveness of the approach in visually and interactively exploring data and spatial patterns in geospatial data. 相似文献