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Dr. Xintao LIU
Hong Kong Polytechnic University

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0 Complex network
0 smart city
0 Transport and Mobility

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Journal article
Published: 14 July 2021 in International Journal of Environmental Research and Public Health
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With the COVID-19 vaccination widely implemented in most countries, propelled by the need to revive the tourism economy, there is a growing prospect for relieving the social distancing regulation and reopening borders in tourism-oriented countries and regions. This need incentivizes stakeholders to develop border control strategies that fully evaluate health risks if mandatory quarantines are lifted. In this study, we have employed a computational approach to investigate the contact tracing integrated policy in different border-reopening scenarios in Hong Kong, China. Explicitly, by reconstructing the COVID-19 transmission from historical data, specific scenarios with joint effects of digital contact tracing and other concurrent measures (i.e., controlling arrival population and community nonpharmacological interventions) are applied to forecast the future development of the pandemic. Built on a modified SEIR epidemic model with a 30% vaccination coverage, the results suggest that scenarios with digital contact tracing and quick isolation intervention can reduce the infectious population by 92.11% compared to those without contact tracing. By further restricting the inbound population with a 10,000 daily quota and applying moderate-to-strong community nonpharmacological interventions (NPIs), the average daily confirmed cases in the forecast period of 60 days can be well controlled at around 9 per day (95% CI: 7–12). Two main policy recommendations are drawn from the study. First, digital contact tracing would be an effective countermeasure for reducing local virus spread, especially when it is applied along with a moderate level of vaccination coverage. Second, implementing a daily quota on inbound travelers and restrictive community NPIs would further keep the local infection under control. This study offers scientific evidence and prospective guidance for developing and instituting plans to lift mandatory border control policies in preparing for the global economic recovery.

ACS Style

Zidong Yu; Xiaolin Zhu; Xintao Liu; Tao Wei; Hsiang-Yu Yuan; Yang Xu; Rui Zhu; Huan He; Hui Wang; Man Wong; Peng Jia; Song Guo; Wenzhong Shi; Wu Chen. Reopening International Borders without Quarantine: Contact Tracing Integrated Policy against COVID-19. International Journal of Environmental Research and Public Health 2021, 18, 7494 .

AMA Style

Zidong Yu, Xiaolin Zhu, Xintao Liu, Tao Wei, Hsiang-Yu Yuan, Yang Xu, Rui Zhu, Huan He, Hui Wang, Man Wong, Peng Jia, Song Guo, Wenzhong Shi, Wu Chen. Reopening International Borders without Quarantine: Contact Tracing Integrated Policy against COVID-19. International Journal of Environmental Research and Public Health. 2021; 18 (14):7494.

Chicago/Turabian Style

Zidong Yu; Xiaolin Zhu; Xintao Liu; Tao Wei; Hsiang-Yu Yuan; Yang Xu; Rui Zhu; Huan He; Hui Wang; Man Wong; Peng Jia; Song Guo; Wenzhong Shi; Wu Chen. 2021. "Reopening International Borders without Quarantine: Contact Tracing Integrated Policy against COVID-19." International Journal of Environmental Research and Public Health 18, no. 14: 7494.

Research article
Published: 30 May 2021 in Transactions in GIS
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Urban agglomeration is an important strategy used to promote economic development and urbanization in China. Understanding the structure of urban agglomeration is therefore essential for policy-makers and planners. In this study, the Beijing–Tianjin–Hebei urban agglomeration (BTHUG) is explored through a proposed spatial network analytical framework and a large mobile phone data set (over 20 million users). We first construct a weight-directed spatial interaction network based on an origin–destination matrix derived from the data set. Several network metrics (i.e., degree, strength, the rich-club coefficient, and the assortativity coefficient) and three selected community detection algorithms (i.e., Infomap, Louvain, and Regionalization) are applied and compared to reveal the structure of the BTHUG. A four-level hierarchical structure is defined and observed: one global center, two local centers, major cities that have low mobility flow but strong linkages with the three centers, and peripheral cities that have low mobility flow and weak linkages with the three centers. In particular, the results imply that the spatial structure of the BTHUG is over-dependent on the global center (i.e., Beijing and northern Langfang). Further, ignoring spatial interaction patterns in top-down administrative planning for urban agglomeration may lead to ineffective integrated development. The implications for BTHUG planning are discussed.

ACS Style

Xintao Liu; Jianwei Huang; Jianhui Lai; Junwei Zhang; Ahmad M. Senousi; Pengxiang Zhao. Analysis of urban agglomeration structure through spatial network and mobile phone data. Transactions in GIS 2021, 1 .

AMA Style

Xintao Liu, Jianwei Huang, Jianhui Lai, Junwei Zhang, Ahmad M. Senousi, Pengxiang Zhao. Analysis of urban agglomeration structure through spatial network and mobile phone data. Transactions in GIS. 2021; ():1.

Chicago/Turabian Style

Xintao Liu; Jianwei Huang; Jianhui Lai; Junwei Zhang; Ahmad M. Senousi; Pengxiang Zhao. 2021. "Analysis of urban agglomeration structure through spatial network and mobile phone data." Transactions in GIS , no. : 1.

Journal article
Published: 29 May 2021 in Physica A: Statistical Mechanics and its Applications
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A robust bus transit network is of fundamental importance for sustainable development by alleviating urban problems. This paper aims to explore the robustness of 57 bus transit networks from the aspect of transferability. Bus transit networks are constructed using open-source data from the same data source for ensuring a consistent comparison, and the network robustness is analyzed using giant component (GC) to represent the maximum scale of transferability and network efficiency (NE) that characterizes the overall efficiency of transferability. (1) The results reveal a universal heavy-tailed distribution of network betweenness irrespective of cities and indicate target attack is more destructive to network robustness than random attack. (2) Different cities have different degrees of robustness, where most large cities tend to be more vulnerable than small cities and NE is more likely to be affected by target attack than GC. (3) The impact of target attack may become weaker than random attack after removing a certain percentage of nodes, which varies in different cities. (4) Thereafter, we present clusters of cities according to similarities of their network robustness. Thus, our comparative results can benefit transit planners and policymakers by enhancing the robustness of bus transit networks.

ACS Style

Tao Jia; Wenxuan Liu; Xintao Liu. A cross-city exploratory analysis of the robustness of bus transit networks using open-source data. Physica A: Statistical Mechanics and its Applications 2021, 580, 126133 .

AMA Style

Tao Jia, Wenxuan Liu, Xintao Liu. A cross-city exploratory analysis of the robustness of bus transit networks using open-source data. Physica A: Statistical Mechanics and its Applications. 2021; 580 ():126133.

Chicago/Turabian Style

Tao Jia; Wenxuan Liu; Xintao Liu. 2021. "A cross-city exploratory analysis of the robustness of bus transit networks using open-source data." Physica A: Statistical Mechanics and its Applications 580, no. : 126133.

Journal article
Published: 08 May 2021 in ISPRS International Journal of Geo-Information
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A city is a complex system that never sleeps; it constantly changes, and its internal mobility (people, vehicles, goods, information, etc.) continues to accelerate and intensify. These changes and mobility vary in terms of the attributes of the city, such as space, time and cultural affiliation, which characterise to some extent how the city functions. Traditional urban studies have successfully modelled the ‘low-frequency city’ and have provided solutions such as urban planning and highway design for long-term urban development. Nevertheless, the existing urban studies and theories are insufficient to model the dynamics of a city’s intense mobility and rapid changes, so they cannot tackle short-term urban problems such as traffic congestion, real-time transport scheduling and resource management. The advent of information and communication technology and big data presents opportunities to model cities with unprecedented resolution. Since 2018, a paradigm shift from modelling the ‘low-frequency city’ to the so-called ‘high-frequency city’ has been introduced, but hardly any research investigated methods to estimate a city’s frequency. This work aims to propose a framework for the identification and analysis of indicators to model and better understand the concept of a high-frequency city in a systematic manner. The methodology for this work was based on a content analysis-based review, taking into account specific criteria to ensure the selection of indicator sets that are consistent with the concept of the frequency of cities. Twenty-two indicators in five groups were selected as indicators for a high-frequency city, and a framework was proposed to assess frequency at both the intra-city and inter-city levels. This work would serve as a pilot study to further illuminate the ways that urban policy and operations can be adjusted to improve the quality of city life in the context of a smart city.

ACS Style

Ahmad Senousi; Junwei Zhang; Wenzhong Shi; Xintao Liu. A Proposed Framework for Identification of Indicators to Model High-Frequency Cities. ISPRS International Journal of Geo-Information 2021, 10, 317 .

AMA Style

Ahmad Senousi, Junwei Zhang, Wenzhong Shi, Xintao Liu. A Proposed Framework for Identification of Indicators to Model High-Frequency Cities. ISPRS International Journal of Geo-Information. 2021; 10 (5):317.

Chicago/Turabian Style

Ahmad Senousi; Junwei Zhang; Wenzhong Shi; Xintao Liu. 2021. "A Proposed Framework for Identification of Indicators to Model High-Frequency Cities." ISPRS International Journal of Geo-Information 10, no. 5: 317.

Journal article
Published: 08 March 2021 in International Journal of Environmental Research and Public Health
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The measurement of medical service accessibility is typically based on driving or Euclidean distance. However, in most non-emergency cases, public transport is the travel mode used by the public to access medical services. Yet, there has been little evaluation of the public transport system-based inequality of medical service accessibility. This work uses massive real smart card data (SCD) and an improved potential model to estimate the public transport-based medical service accessibility in Beijing, China. These real SCD data are used to calculate travel costs in terms of time and distance, and medical service accessibility is estimated using an improved potential model. The spatiotemporal variations and patterns of medical service accessibility are explored, and the results show that it is unevenly spatiotemporally distributed across the study area. For example, medical service accessibility in urban areas is higher than that in suburban areas, accessibility during peak periods is higher than that during off-peak periods, and accessibility on weekends is generally higher than that on weekdays. To explore the association of medical service accessibility with socio-economic factors, the relationship between accessibility and house price is investigated via a spatial econometric analysis. The results show that, at a global level, house price is positively correlated with medical service accessibility. In particular, the medical service accessibility of a higher-priced spatial housing unit is lower than that of its neighboring spatial units, owing to the positive spatial spillover effect of house price. This work sheds new light on the inequality of medical service accessibility from the perspective of public transport, which may benefit urban policymakers and planners.

ACS Style

Xintao Liu; Ziwei Lin; Jianwei Huang; He Gao; Wenzhong Shi. Evaluating the Inequality of Medical Service Accessibility Using Smart Card Data. International Journal of Environmental Research and Public Health 2021, 18, 2711 .

AMA Style

Xintao Liu, Ziwei Lin, Jianwei Huang, He Gao, Wenzhong Shi. Evaluating the Inequality of Medical Service Accessibility Using Smart Card Data. International Journal of Environmental Research and Public Health. 2021; 18 (5):2711.

Chicago/Turabian Style

Xintao Liu; Ziwei Lin; Jianwei Huang; He Gao; Wenzhong Shi. 2021. "Evaluating the Inequality of Medical Service Accessibility Using Smart Card Data." International Journal of Environmental Research and Public Health 18, no. 5: 2711.

Journal article
Published: 15 December 2020 in ISPRS International Journal of Geo-Information
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Many cities around the world face the challenge of an aging population. A full understanding of the mobility behavior characteristics of the elderly is one necessary and urgent consideration as regards the current aging trend if sustainable urban development is to be fully realized. This paper presents a systematic approach to analyzing the dynamic mobility characteristics of the elderly who travel by bus using smart card big data. The characteristics include temporal distribution, travel distance, travel duration, travel frequency, and also the spatial distribution of such travelers. The findings of these mobility characteristics can directly contribute to both public transport policy making, service, and management. In this study, the analytics of the elderly are also compared with that of the average adult group so as to identify both the similarities and differences between the two groups. Beijing, a megacity, with a very high life expectancy and in which the bus is the dominant mode of public transport for the elderly, was used as the study area. The significance of this research concerns a newly developed systematic approach that is able to analyze the dynamic mobility characteristics of the elderly using smart card data.

ACS Style

Zhicheng Shi; Lilian S. C. Pun-Cheng; Xintao Liu; Jianhui Lai; Chengzhuo Tong; Anshu Zhang; Min Zhang; Wenzhong Shi. Analysis of the Temporal Characteristics of the Elderly Traveling by Bus Using Smart Card Data. ISPRS International Journal of Geo-Information 2020, 9, 751 .

AMA Style

Zhicheng Shi, Lilian S. C. Pun-Cheng, Xintao Liu, Jianhui Lai, Chengzhuo Tong, Anshu Zhang, Min Zhang, Wenzhong Shi. Analysis of the Temporal Characteristics of the Elderly Traveling by Bus Using Smart Card Data. ISPRS International Journal of Geo-Information. 2020; 9 (12):751.

Chicago/Turabian Style

Zhicheng Shi; Lilian S. C. Pun-Cheng; Xintao Liu; Jianhui Lai; Chengzhuo Tong; Anshu Zhang; Min Zhang; Wenzhong Shi. 2020. "Analysis of the Temporal Characteristics of the Elderly Traveling by Bus Using Smart Card Data." ISPRS International Journal of Geo-Information 9, no. 12: 751.

Journal article
Published: 02 December 2020 in IEEE Intelligent Transportation Systems Magazine
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ACS Style

Susan Jia Xu; Qian Xie; Joseph Y.J. Chow; Xintao Liu. An Empirical Validation of Network Learning With Taxi GPS Data From Wuhan, China. IEEE Intelligent Transportation Systems Magazine 2020, 13, 42 -58.

AMA Style

Susan Jia Xu, Qian Xie, Joseph Y.J. Chow, Xintao Liu. An Empirical Validation of Network Learning With Taxi GPS Data From Wuhan, China. IEEE Intelligent Transportation Systems Magazine. 2020; 13 (1):42-58.

Chicago/Turabian Style

Susan Jia Xu; Qian Xie; Joseph Y.J. Chow; Xintao Liu. 2020. "An Empirical Validation of Network Learning With Taxi GPS Data From Wuhan, China." IEEE Intelligent Transportation Systems Magazine 13, no. 1: 42-58.

Original article
Published: 10 September 2020 in Environmental Earth Sciences
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Earthquakes are one of the destructive natural disasters. Immediate emergency response in the first few hours is important for life rescue. The near real-time ground deformation maps generated after earthquakes are crucial for hazard assessments, which normally take a couple of hours or longer to be generated using conventional ways. In this study, we propose a near real-time coseismic ground deformation map generation system with the aim of assisting rapid seismic hazard evaluations and emergency responses. This framework adopts the source parameters published by seismological agencies and uses the empirical equations to generate the near real-time coseismic ground deformation maps. The source parameters of an earthquake, such as the focal mechanism, are programmatically accessed from the United States Geological Survey National Earthquake Information Center (USGS-NEIC) in a nearly real-time manner. The ground deformation estimated using empirical equations is integrated as self-adapting spatial data fusion and visualized on an interactive WebGIS platform. We develop the WebGIS platform, namely QuickDeform at https://www.insar.com.cn, and successfully applied the system to several recent large magnitude earthquakes. We find that the proposed framework functions robustly and proficiently to automatically generate the seismic deformation map within several minutes after the occurrence of an earthquake. The generated deformation map shows good agreement when compared to the data from real earthquakes. QuickDeform can be used as a volunteered geographic information platform for crowdsourcing disaster data for rescue and model validation.

ACS Style

Rui Zhao; Xintao Liu; Wenbin Xu. Integration of coseismic deformation into WebGIS for near real-time disaster evaluation and emergency response. Environmental Earth Sciences 2020, 79, 1 -11.

AMA Style

Rui Zhao, Xintao Liu, Wenbin Xu. Integration of coseismic deformation into WebGIS for near real-time disaster evaluation and emergency response. Environmental Earth Sciences. 2020; 79 (18):1-11.

Chicago/Turabian Style

Rui Zhao; Xintao Liu; Wenbin Xu. 2020. "Integration of coseismic deformation into WebGIS for near real-time disaster evaluation and emergency response." Environmental Earth Sciences 79, no. 18: 1-11.

Review article
Published: 01 September 2020 in Environmental Modelling & Software
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Sensitivity analysis (SA) has been used to evaluate the behavior and quality of environmental models by estimating the contributions of potential uncertainty sources to quantities of interest (QoI) in the model output. Although there is an increasing literature on applying SA in environmental modeling, a pragmatic and specific framework for spatially distributed environmental models (SD-EMs) is lacking and remains a challenge. This article reviews the SA literature for the purposes of providing a step-by-step pragmatic framework to guide SA, with an emphasis on addressing potential uncertainty sources related to spatial datasets and the consequent impact on model predictive uncertainty in SD-EMs. The framework includes: identifying potential uncertainty sources; selecting appropriate SA methods and QoI in prediction according to SA purposes and SD-EM properties; propagating perturbations of the selected potential uncertainty sources by considering the spatial structure; and verifying the SA measures based on post-processing. The proposed framework was applied to a SWAT (Soil and Water Assessment Tool) application to demonstrate the sensitivities of the selected QoI to spatial inputs, including both raster and vector datasets - for example, DEM and meteorological information - and SWAT (sub)model parameters. The framework should benefit SA users not only in environmental modeling areas but in other modeling domains such as those embraced by geographical information system communities.

ACS Style

Hyeongmo Koo; Takuya Iwanaga; Barry F.W. Croke; Anthony J. Jakeman; Jing Yang; Hsiao-Hsuan Wang; Xifu Sun; Guonian Lü; Xin Li; Tianxiang Yue; Wenping Yuan; Xintao Liu; Min Chen. Position paper: Sensitivity analysis of spatially distributed environmental models- a pragmatic framework for the exploration of uncertainty sources. Environmental Modelling & Software 2020, 134, 104857 .

AMA Style

Hyeongmo Koo, Takuya Iwanaga, Barry F.W. Croke, Anthony J. Jakeman, Jing Yang, Hsiao-Hsuan Wang, Xifu Sun, Guonian Lü, Xin Li, Tianxiang Yue, Wenping Yuan, Xintao Liu, Min Chen. Position paper: Sensitivity analysis of spatially distributed environmental models- a pragmatic framework for the exploration of uncertainty sources. Environmental Modelling & Software. 2020; 134 ():104857.

Chicago/Turabian Style

Hyeongmo Koo; Takuya Iwanaga; Barry F.W. Croke; Anthony J. Jakeman; Jing Yang; Hsiao-Hsuan Wang; Xifu Sun; Guonian Lü; Xin Li; Tianxiang Yue; Wenping Yuan; Xintao Liu; Min Chen. 2020. "Position paper: Sensitivity analysis of spatially distributed environmental models- a pragmatic framework for the exploration of uncertainty sources." Environmental Modelling & Software 134, no. : 104857.

Letter
Published: 30 July 2020 in Sensors
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Received signal strength indicator (RSSI)-based positioning is suitable for large-scale applications due to its advantages of low cost and high accuracy. However, it suffers from low stability because RSSI is easily blocked and easily interfered with by objects and environmental effects. Therefore, this paper proposed a tri-partition RSSI classification and its tracing algorithm as an RSSI filter. The proposed filter shows an available feature, where small test RSSI samples gain a low deviation of less than 1 dBm from a large RSSI sample collected about 10 min, and the sub-classification RSSIs conform to normal distribution when the minimum sample count is greater than 20. The proposed filter also offers several advantages compared to the mean filter, including lower variance range with an overall range of around 1 dBm, 25.9% decreased sample variance, and 65% probability of mitigating RSSI left-skewness. We experimentally confirmed the proposed filter worked in the path-loss exponent fitting and location computing, and a 4.45-fold improvement in positioning stability based on the sample standard variance, and positioning accuracy improved by 20.5% with an overall error of less than 1.46 m.

ACS Style

Yong Shi; Wenzhong Shi; Xintao Liu; Xianjian Xiao. An RSSI Classification and Tracing Algorithm to Improve Trilateration-Based Positioning. Sensors 2020, 20, 4244 .

AMA Style

Yong Shi, Wenzhong Shi, Xintao Liu, Xianjian Xiao. An RSSI Classification and Tracing Algorithm to Improve Trilateration-Based Positioning. Sensors. 2020; 20 (15):4244.

Chicago/Turabian Style

Yong Shi; Wenzhong Shi; Xintao Liu; Xianjian Xiao. 2020. "An RSSI Classification and Tracing Algorithm to Improve Trilateration-Based Positioning." Sensors 20, no. 15: 4244.

Journal article
Published: 30 July 2020 in Remote Sensing
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Urban functional area (UFA) recognition is one of the most important strategies for achieving sustainable city development. As remote-sensing and social-sensing data sources have increasingly become available, UFA recognition has received a significant amount of attention. Research on UFA recognition that uses a single dataset suffers from a low update frequency or low spatial resolution, while data fusion-based methods are limited in efficiency and accuracy. This paper proposes an integrated model to identify UFA using satellite images and taxi global positioning system (GPS) trajectories in four steps. First, blocks were generated as spatial units in the study area, and the spatiotemporal information entropy of the taxi GPS trajectory (STET) for each block was calculated. Second, a 24-hour time-frequency series was formed based on the pick-up and drop-off points extracted from taxi trajectories and used as the interpretation indicator of the blocks. The K-Means++ and k-Nearest Neighbor (kNN) algorithm were used to identify their social functions. Third, a multilabel classification method based on the residual neural network (MLC-ResNets) and “You Only Look Once” (YOLO) target detection algorithms were used to identify the features of the typical and atypical spatial textures, respectively, of the satellite images in the blocks. The confidence scores of the features of the blocks were categorized by the decision tree algorithm. Fourth, to find the best way to integrate the two sub-models for UFA identification, the 10-fold cross-validation method based on stratified random sampling was applied to determine the most optimal STET thresholds. The results showed that the average accuracy reached 82.0%, with an average kappa of 73.5%—significant improvements over most existing studies. This paper provides new insights into how the advantages of satellite images and taxi trajectories in UFA identification can be fully exploited to support sustainable city management.

ACS Style

Zhen Qian; Xintao Liu; Fei Tao; Tong Zhou. Identification of Urban Functional Areas by Coupling Satellite Images and Taxi GPS Trajectories. Remote Sensing 2020, 12, 2449 .

AMA Style

Zhen Qian, Xintao Liu, Fei Tao, Tong Zhou. Identification of Urban Functional Areas by Coupling Satellite Images and Taxi GPS Trajectories. Remote Sensing. 2020; 12 (15):2449.

Chicago/Turabian Style

Zhen Qian; Xintao Liu; Fei Tao; Tong Zhou. 2020. "Identification of Urban Functional Areas by Coupling Satellite Images and Taxi GPS Trajectories." Remote Sensing 12, no. 15: 2449.

Journal article
Published: 20 May 2020 in Geocarto International
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ACS Style

Ahmad M. Senousi; Xintao Liu; Junwei Zhang; Jianwei Huang; Wenzhong Shi. An empirical analysis of public transit networks using smart card data in Beijing, China. Geocarto International 2020, 1 -21.

AMA Style

Ahmad M. Senousi, Xintao Liu, Junwei Zhang, Jianwei Huang, Wenzhong Shi. An empirical analysis of public transit networks using smart card data in Beijing, China. Geocarto International. 2020; ():1-21.

Chicago/Turabian Style

Ahmad M. Senousi; Xintao Liu; Junwei Zhang; Jianwei Huang; Wenzhong Shi. 2020. "An empirical analysis of public transit networks using smart card data in Beijing, China." Geocarto International , no. : 1-21.

Research article
Published: 19 May 2020 in Transactions in GIS
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Weather radar data play an important role in meteorological analysis and forecasting. In particular, web‐based real‐time 3D visualization will enable and enhance various meteorological applications by avoiding the dissemination of a large amount of data over the internet. Despite that, most existing studies are either limited to 2D or small‐scale data analytics due to methodological limitations. This article proposes a new framework to enable web‐based real‐time 3D visualization of large‐scale weather radar data using 3D tiles and WebGIS technology. The 3D tiles technology is an open specification for online streaming massive heterogeneous 3D geospatial datasets, which is designed to improve rendering performance and reduce memory consumption. First, the weather radar data from multiple single‐radar sites across a large coverage area are organized into a spliced grid data (i.e., weather radar composing data, WRCD). Next, the WRCD is converted into a widely used 3D tile data structure in four steps: data preprocessing, data indexing, data transformation, and 3D tile generation. Last, to validate the feasibility of the proposed strategy, a prototype, namely Meteo3D at https://202.195.237.252:82, is implemented to accommodate the WRCD collected from all the weather radar sites over the whole of China. The results show that near real‐time and accurate visualization for the monitoring and early warning of strong convective weather can be achieved.

ACS Style

Mingyue Lu; Xinhao Wang; Xintao Liu; Min Chen; Shuoben Bi; Yadong Zhang; Tengfei Lao. Web‐based real‐time visualization of large‐scale weather radar data using 3D tiles. Transactions in GIS 2020, 25, 25 -43.

AMA Style

Mingyue Lu, Xinhao Wang, Xintao Liu, Min Chen, Shuoben Bi, Yadong Zhang, Tengfei Lao. Web‐based real‐time visualization of large‐scale weather radar data using 3D tiles. Transactions in GIS. 2020; 25 (1):25-43.

Chicago/Turabian Style

Mingyue Lu; Xinhao Wang; Xintao Liu; Min Chen; Shuoben Bi; Yadong Zhang; Tengfei Lao. 2020. "Web‐based real‐time visualization of large‐scale weather radar data using 3D tiles." Transactions in GIS 25, no. 1: 25-43.

Article
Published: 25 April 2020 in GeoInformatica
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A group event such as human and traffic congestion can be very roughly divided into three stages: converging stage before congestion, gathered stage when congestion happens, and dispersing stage that congestion disappears. It is of great interest in modeling and identifying converging behaviors before gathered events actually happen, which helps to proactively predict and handle potential public incidents such as serious stampedes. However, most of existing literature put too much emphasis on the second stage, only a few of them is dedicated to the first stage. In this paper, we propose a novel group pattern, namely converging, which refers to a group of moving objects converging from different directions during a certain period before gathered. To discover efficiently such converging patterns, we develop a framework for converging pattern mining (CPM) by examining how moving objects form clusters and the process of the “cluster containment”. The framework consists of three phases: snapshot cluster discovery phase, cluster containment join phase, and converging detection phase. As cluster containment mining is the key step, we develop three algorithms to discover cluster containment matches: a containment-join-algorithm, called SSCCJ, by using spatial proximity; a signature tree-based cluster-containment-join-algorithm, called STCCJ, which takes advantage of the cluster containment relations and signature techniques to filter enormous unqualified candidates in an efficient and effective way; and third, to keep the advantages of the above algorithms while avoiding their flaws, we further propose a signature quad-tree based cluster-containment-join algorithm, called SQTCCJ, which can identify efficiently matches by considering cluster spatial proximity as well as containment relations simultaneously. To assess the proposed methods, we redefine two evaluation metrics based on the concept of “Precision and Recall” in the field of information retrieval and the characteristics of converging patterns. We also propose a new indicator for measuring the duration of the converging stage in a group event. Finally, the effectiveness of the CPM and the efficiency of the mining algorithms are evaluated using three types of trajectory datasets, and the results show that the SQTCCJ algorithm demonstrates a superior performance.

ACS Style

Bin Zhao; Xintao Liu; Jinping Jia; GenLin Ji; Shengxi Tan; Zhaoyuan Yu. A Framework for Group Converging Pattern Mining using Spatiotemporal Trajectories. GeoInformatica 2020, 24, 745 -776.

AMA Style

Bin Zhao, Xintao Liu, Jinping Jia, GenLin Ji, Shengxi Tan, Zhaoyuan Yu. A Framework for Group Converging Pattern Mining using Spatiotemporal Trajectories. GeoInformatica. 2020; 24 (4):745-776.

Chicago/Turabian Style

Bin Zhao; Xintao Liu; Jinping Jia; GenLin Ji; Shengxi Tan; Zhaoyuan Yu. 2020. "A Framework for Group Converging Pattern Mining using Spatiotemporal Trajectories." GeoInformatica 24, no. 4: 745-776.

Journal article
Published: 20 March 2020 in Cities
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Understanding cab drivers' stay activities is essential for planning and managing certain urban facilities. This study analyzes cab drivers' stay behaviors using a taxi GPS trajectory dataset collected in Wuhan, China. By extracting cab drivers' stay activities from the dataset, we measure the activity frequency at the level of traffic analysis zones (TAZs) and examine their spatiotemporal dynamics. We then derive several built environment indicators and assess their associations with these activities using ordinary least squares regression (OLS) and geographically weighted regression (GWR) models. According to the results, the stay frequency decays dramatically over the TAZs, indicating that these activities tend to be concentrated in particular areas of the city. The rates of decay, as reflected by the rank-size and power-law distributions, are similar on weekdays and weekends. Cab drivers' stay activities exhibit similar spatial patterns during the same period on weekdays and weekends. The adjusted R-squared of OLS is 0.742 for weekdays and 0.676 for weekends, which suggests a close relationship between stay activities and built environment characteristics. The GWR models further reveal the spatial variations of the activity-environment linkage across the study area. The study provides useful insights that support future urban design and transport planning.

ACS Style

Pengxiang Zhao; Yang Xu; Xintao Liu; Mei-Po Kwan. Space-time dynamics of cab drivers' stay behaviors and their relationships with built environment characteristics. Cities 2020, 101, 102689 .

AMA Style

Pengxiang Zhao, Yang Xu, Xintao Liu, Mei-Po Kwan. Space-time dynamics of cab drivers' stay behaviors and their relationships with built environment characteristics. Cities. 2020; 101 ():102689.

Chicago/Turabian Style

Pengxiang Zhao; Yang Xu; Xintao Liu; Mei-Po Kwan. 2020. "Space-time dynamics of cab drivers' stay behaviors and their relationships with built environment characteristics." Cities 101, no. : 102689.

Journal article
Published: 19 December 2019 in ISPRS International Journal of Geo-Information
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The social function of areas of interest (AOIs) is crucial to the identification of urban functional zoning and land use classification, which has been a hot topic in various fields such as urban planning and smart city fields. Most existing studies on urban functional zoning and land use classification either largely rely on low-frequency remote sensing images, which are constrained to the block level due to their spatial scale limitation, or suffer from low accuracy and high uncertainty when using dynamic data, such as social media and traffic data. This paper proposes an hour-day-spectrum (HDS) approach for generating six types of distribution waveforms of taxi pick-up and drop-off points which serve as interpretation indicators of the social functions of AOIs. To achieve this goal, we first performed fine-grained cleaning of the drop-off points to eliminate the spatial errors caused by taxi drivers. Next, buffer and spatial clustering were integrated to explore the associations between travel behavior and AOIs. Third, the identification of AOI types was made by using the standard HDS method combined with the k-nearest neighbor (KNN) algorithm. Finally, some matching tests were carried out by similarity indexes of a standard HDS and sample HDS, i.e., the Gaussian kernel function and Pearson coefficient, to ensure matching accuracy. The experiment was conducted in the Chongchuan and Gangzha Districts, Nantong, Jiangsu Province, China. By training 50 AOI samples, six types of standard HDS of residential districts, schools, hospitals, and shopping malls were obtained. Then, 108 AOI samples were tested, and the overall accuracy was found to be 90.74%. This approach generates value-added services of the taxi trajectory and provides a continuous update and fine-grained supplementary method for the identification of land use types. In addition, the approach is object-oriented and based on AOIs, and can be combined with image interpretation and other methods to improve the identification effect.

ACS Style

Tong Zhou; Xintao Liu; Zhen Qian; Haoxuan Chen; Fei Tao. Automatic Identification of the Social Functions of Areas of Interest (AOIs) Using the Standard Hour-Day-Spectrum Approach. ISPRS International Journal of Geo-Information 2019, 9, 7 .

AMA Style

Tong Zhou, Xintao Liu, Zhen Qian, Haoxuan Chen, Fei Tao. Automatic Identification of the Social Functions of Areas of Interest (AOIs) Using the Standard Hour-Day-Spectrum Approach. ISPRS International Journal of Geo-Information. 2019; 9 (1):7.

Chicago/Turabian Style

Tong Zhou; Xintao Liu; Zhen Qian; Haoxuan Chen; Fei Tao. 2019. "Automatic Identification of the Social Functions of Areas of Interest (AOIs) Using the Standard Hour-Day-Spectrum Approach." ISPRS International Journal of Geo-Information 9, no. 1: 7.

Journal article
Published: 03 December 2019 in Sustainability
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This paper proposes a novel method for dynamically extracting and monitoring the entrances of areas of interest (AOIs). Most AOIs in China, such as buildings and communities, are enclosed by walls and are only accessible via one or more entrances. The entrances are not marked on most maps for route planning and navigation in an accurate way. In this work, the extraction scheme of the entrances is based on taxi trajectory data with a 30 s sampling time interval. After fine-grained data cleaning, the position accuracy of the drop-off points extracted from taxi trajectory data is guaranteed. Next, the location of the entrances is extracted, combining the density-based spatial clustering of applications with noise (DBSCAN) with the boundary of the AOI under the constraint of the road network. Based on the above processing, the dynamic update scheme of the entrance is designed. First, a time series analysis is conducted using the clusters of drop-off points within the adjacent AOI, and then, a relative heat index ( R H I ) is applied to detect the recent access status (closed or open) of the entrances. The results show the average accuracy of the current extraction algorithm is improved by 24.3% over the K-means algorithm, and the R H I can reduce the limitation of map symbols in describing the access status. The proposed scheme can, therefore, help optimize the dynamic visualization of the entry symbols in mobile navigation maps, and facilitate human travel behavior and way-finding, which is of great help to sustainable urban development.

ACS Style

Tong Zhou; Xintao Liu; Zhen Qian; Haoxuan Chen; Fei Tao. Dynamic Update and Monitoring of AOI Entrance via Spatiotemporal Clustering of Drop-Off Points. Sustainability 2019, 11, 6870 .

AMA Style

Tong Zhou, Xintao Liu, Zhen Qian, Haoxuan Chen, Fei Tao. Dynamic Update and Monitoring of AOI Entrance via Spatiotemporal Clustering of Drop-Off Points. Sustainability. 2019; 11 (23):6870.

Chicago/Turabian Style

Tong Zhou; Xintao Liu; Zhen Qian; Haoxuan Chen; Fei Tao. 2019. "Dynamic Update and Monitoring of AOI Entrance via Spatiotemporal Clustering of Drop-Off Points." Sustainability 11, no. 23: 6870.

Journal article
Published: 10 October 2019 in ISPRS International Journal of Geo-Information
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Public transport plays an important role in developing sustainable cities. A better understanding of how different public transit modes (bus, metro, and taxi) interact with each other will provide better sustainable strategies to transport and urban planners. However, most existing studies are either limited to small-scale surveys or focused on the identification of general interaction patterns during times of regular traffic. Transient demographic changes in a city (i.e., many people moving out and in) can lead to significant changes in such interaction patterns and provide a useful context for better investigating the changes in these patterns. Despite that, little has been done to explore how such interaction patterns change and how they are linked to the built environment from the perspective of transient demographic changes using urban big data. In this paper, the tap-in-tap-out smart card data of bus/metro and taxi GPS trajectory data before and after the Chinese Spring Festival in Shenzhen, China, are used to explore such interaction patterns. A time-series clustering method and an elasticity change index (ECI) are adopted to detect the changing transit mode patterns and the underlying dynamics. The findings indicate that the interactions between different transit modes vary over space and time and are competitive or complementary in different parts of the city. Both ordinary least-squares (OLS) and geographically weighted regression (GWR) models with built environment variables are used to reveal the impact of changes in different transit modes on ECIs and their linkage with the built environment. The results of this study will contribute to the planning and design of multi-modal transport services.

ACS Style

Jianwei Huang; Xintao Liu; Pengxiang Zhao; Junwei Zhang; Mei-Po Kwan. Interactions between Bus, Metro, and Taxi Use before and after the Chinese Spring Festival. ISPRS International Journal of Geo-Information 2019, 8, 445 .

AMA Style

Jianwei Huang, Xintao Liu, Pengxiang Zhao, Junwei Zhang, Mei-Po Kwan. Interactions between Bus, Metro, and Taxi Use before and after the Chinese Spring Festival. ISPRS International Journal of Geo-Information. 2019; 8 (10):445.

Chicago/Turabian Style

Jianwei Huang; Xintao Liu; Pengxiang Zhao; Junwei Zhang; Mei-Po Kwan. 2019. "Interactions between Bus, Metro, and Taxi Use before and after the Chinese Spring Festival." ISPRS International Journal of Geo-Information 8, no. 10: 445.

Journal article
Published: 06 September 2019 in IEEE Access
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ACS Style

Tong Zhou; Wenzhong Shi; Xintao Liu; Fei Tao; Zhen Qian; Ruijia Zhang. A Novel Approach for Online Car-Hailing Monitoring Using Spatiotemporal Big Data. IEEE Access 2019, 7, 128936 -128947.

AMA Style

Tong Zhou, Wenzhong Shi, Xintao Liu, Fei Tao, Zhen Qian, Ruijia Zhang. A Novel Approach for Online Car-Hailing Monitoring Using Spatiotemporal Big Data. IEEE Access. 2019; 7 ():128936-128947.

Chicago/Turabian Style

Tong Zhou; Wenzhong Shi; Xintao Liu; Fei Tao; Zhen Qian; Ruijia Zhang. 2019. "A Novel Approach for Online Car-Hailing Monitoring Using Spatiotemporal Big Data." IEEE Access 7, no. : 128936-128947.

Journal article
Published: 13 June 2019 in Physica A: Statistical Mechanics and its Applications
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Regions are subdivisions of the earth’s surface, and many systems of regionalization were proposed. Recently, with the availability of geotagged data, it raises the question of whether regions formed by human interactions agree with government districts. Thus, using network partitioning method with spatial constraint, we derive regional delineations at different spatial scales and examine their agreement with administrative districts. Experiments were conducted using the social media data of Shenzhen, China. Aggregately, the results show that the derived regions become inconsistent with administrative districts by increasing the spatial effect value, which can be largely attributed to the involvement of long human movements. However, the regions tend to keep stable when more long edges are included, which suggests the limitation of long movements effect. Individually, most northern administrative districts display high inconsistency with the derived regions, whereas most southern districts show high consistency. Besides, regions far from the downtown are less connected to the rest of the city, regions near the downtown are more connected, and particularly, regions in Nanshan, Futian, and Luohu are highly connected with each other, which form the backbone of total flows irrespective of spatial effect value. The results were finally validated at specific areas and compared with those using other methods, another dataset, and different spatial units, which suggest the feasibility of our regions for decision making in urban planning and management.

ACS Style

Tao Jia; Xuesong Yu; Wenzhong Shi; Xintao Liu; Xin Li; Yang Xu. Detecting the regional delineation from a network of social media user interactions with spatial constraint: A case study of Shenzhen, China. Physica A: Statistical Mechanics and its Applications 2019, 531, 121719 .

AMA Style

Tao Jia, Xuesong Yu, Wenzhong Shi, Xintao Liu, Xin Li, Yang Xu. Detecting the regional delineation from a network of social media user interactions with spatial constraint: A case study of Shenzhen, China. Physica A: Statistical Mechanics and its Applications. 2019; 531 ():121719.

Chicago/Turabian Style

Tao Jia; Xuesong Yu; Wenzhong Shi; Xintao Liu; Xin Li; Yang Xu. 2019. "Detecting the regional delineation from a network of social media user interactions with spatial constraint: A case study of Shenzhen, China." Physica A: Statistical Mechanics and its Applications 531, no. : 121719.