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A general method of spatio-temporal clustering analysis

Science China(Information Sciences) 2013年第10期56卷 158-171页

作者： DENG Min LIU QiLiang WANG JiaQiu SHI Yan Department of Surveying and Geo-informatics Central South University

spatio-temporal clustering has been a hot topic in the feld of spatio-temporal data mining and knowledge *** can be employed to uncover and interpret developmental trends of geographic phenomenon in the real ***,existing spatio-temporal clustering methods seldom consider both spatiotemporal autocorrelations and heterogeneities among spatio-temporal entities,and the coupling in space and time has not been well *** this paper,a unifed framework for the clustering analysis of spatio-temporal data is proposed,and a novel spatio-temporal clustering algorithm is developed by means of a spatio-temporal statistics methodology and intelligence computation *** method is applied successfully to fnding spatio-temporal cluster in China’s annual temperature database for the period 1951 1992.

关键词： spatio-temporal clustering spatio-temporal autocorrelation spatio-temporal heterogeneity spatio-temporal data mining

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Interpreting map usage patterns using geovisual analytics and spatiotemporal clustering

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International Journal of Digital Earth 2015年第8期8卷 599-622页

作者： Gavin McArdle Ali Tahir Michela Bertolotto National Center for Geocomputation National University of IrelandMaynoothIreland Institute of Geographical Information Systems School of Civil and Environmental EngineeringNational University of Sciences and TechnologyIslamabadPakistan School of Computer Science and Informatics University College DublinDublinIreland

Extracting meaningful information from the growing quantity of spatial data is a *** issues are particularly evident with spatio-temporal data describing *** data typically corresponds to movement of humans,animals and machines in the physical *** article considers a special form of movement data generated through human–computer interactions with online web *** a user interacts with a web map using a mouse as a pointing tool,invisible trajectories are *** examining the spatial features on the map where the mouse cursor visits,a user’s interests and experience can be *** analyse this valuable information,we have developed a geovisual analysis tool which provides a rich insight into such user *** focus of this paper is on a clustering technique which we apply to mouse trajectories to group trajectories with similar behavioural *** experiments reveal that it is possible to identify experienced and novice users of web mapping environments using an incremental clustering *** results can be used to provide personalised map interfaces to users and provide appropriate interventions for completing spatial tasks.

关键词： geovisual analytics spatio-temporal clustering behavioural clustering map personalisation digital globe

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Space-time clustering and associated risk factors of pulmonary tuberculosis in southwest China

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Infectious Diseases of Poverty 2018年第1期7卷 940-950页

作者： Li Huang Eniola Michael Abe Xin-Xu Li Robert Bergquist Lin Xu Jing-Bo Xue Yao Ruan Chun-Li Cao Shi-Zhu Li Yunnan provincial Center for Disease Control and Prevention KunmingChina National Institute of Parasitic Diseases Chinese Center for Disease Control and PreventionRuijing Er road 207Shanghai 200025China National Research Center for Tropical Disease ShanghaiChina Key Laboratory of Parasite and Vector Biology Ministry of HealthShanghaiChina WHO Collaborating Center for Tropical Diseases ShanghaiChina Center for Drug Evaluation China Food and Drug AdministrationBeijingChina Ingerod BrastadSweden

Background:Pulmonary tuberculosis(PTB,both smear positive and smear negative)is an airborne infectious disease of major public health concern in China and other parts of the world where PTB endemicity is *** study aims at identifying PTB spatio-temporal clusters and associated risk factors in Zhaotong prefecture-level city,located in southwest China,where the PTB notification rate was higher than the average rate in the entire ***:Space-time scan statistics were carried out using PTB registered data in the nationwide TB online registration system from 2011 to 2015,to identify spatial *** patients diagnosed between October 2015 and February 2016 were selected and a structured questionnaire was administered to collect a set of variables that includes socio-economic status,behavioural characteristics,local environmental and biological *** on the discovery of detailed town-level spatio-temporal PTB clusters,we divided selected subjects into two groups including the cases that resides within and outside identified ***,logistic regression analysis was applied comparing the results of variables between the two ***:A total of 1508 subjects consented and participated in the *** for PTB cases were identified in 38 towns distributed over south-western *** regression analysis showed that history of chronic bronchitis(OR=3.683,95%CI:2.180-6.223),living in an urban area(OR=5.876,95%CI:2.381-14.502)and using coal as the main fuel(OR=9.356,95%CI:5.620-15.576)were independently associated with ***,not smoking(OR=0.340,95%CI:0.137-0.843)is the protection factor of spatial ***:We found PTB specially clustered in south-western *** strong associated factors influencing the PTB spatial cluster including:the history of chronic bronchitis,living in the urban area,smoking and the use of coal as the main fuel for cooking and ***,efforts should

关键词： Pulmonary tuberculosis spatio-temporal clustering Regression analysis method Risk factors China

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A novel method for discovering spatio-temporal clusters of different sizes, shapes, and densities in the presence of noise

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International Journal of Digital Earth 2014年第2期7卷 138-157页

作者： Qiliang Liu Min Deng Jiantao Bi Wentao Yang Department of Surveying and Geo-informatics Central South UniversityChangshaChina Department of Land Surveying and Geo-Informatics Hong Kong Polytechnic UniversityHong Kong Center for Earth Observation and Digital Earth Chinese Academy of SciencesBeijingChina

The discovery of spatio-temporal clusters in complex spatio-temporal data-sets has been a challenging issue in the domain of spatio-temporal data mining and knowledge *** this paper,a novel spatio-temporal clustering method based on spatio-temporal shared nearest neighbors(STSNN)is proposed to detect spatio-temporal clusters of different sizes,shapes,and densities in spatiotemporal databases with a large amount of *** concepts of windowed distance and shared nearest neighbor are utilized to define a novel spatiotemporal density for a spatio-temporal entity with definite mathematical ***,the density-based clustering strategy is employed to uncover spatio-temporal *** spatio-temporal clustering algorithm developed in this paper is easily implemented and less sensitive to density variation among spatio-temporal *** are undertaken on several simulated datasets to demonstrate the effectiveness and advantage of the STSNN ***,the real-world applications on two seismic databases show that the STSNN algorithm has the ability to uncover foreshocks and aftershocks effectively.

关键词： spatio-temporal clustering shared nearest neighbor windowed distance spatio-temporal density foreshocks and aftershocks data mining Digital Earth geo-spatial science geospatial data integration

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FunnelCloud:a cloud-based system for exploring tornado events

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International Journal of Digital Earth 2017年第10期10卷 1030-1054页

作者： Jie Lian Michael P.McGuire Todd W.Moore Department of Computer and Information Sciences Towson UniversityTowsonMDUSA Department of Geography and Environmental Planning Towson UniversityTowsonMDUSA

Recent research has shown an increase in the number of extreme tornado outbreaks per *** characterization of the spatio-temporal pattern of tornado events is therefore a critical task in the analysis of meteorological ***,there are a large number of available meteorological datasets that can be used for such ***,much of these data are distributed across multiple websites and are not accessible in a central *** poses a significant challenge for a scientist who is interested in exploring meteorological patterns associated with tornado *** paper presents a novel system which uses cloud-based technology for integrating,storing,exploring,analyzing,and visualizing meteorological data associated with tornado *** system employs a novel NoSQL database schema and web services architecture for data integration and provides a user friendly interface that allows scientists to explore the spatio-temporal pattern of tornado ***,scientists can use this interface to analyze the relationship between different meteorological variables and properties of tornado outbreaks using a number of spatio-temporal statistical and data mining *** efficacy of the system is demonstrated on a use case centered on the analysis of climatic indicators of large spatio-temporally clustered tornado outbreaks.

关键词： tornado data warehouse cloud-based system NoSQL data integration spatio-temporal clustering web-mapping

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spatio-temporal analysis of the incidence of colorectal cancer in Guangzhou,2010-2014

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Chinese Journal of Cancer 2017年第10期36卷 516-523页

作者： Ke Li Guo-Zhen Lin Yan Li Hang Dong Huan Xu Shao-Fang Song Ying-Ru Liang Hua-Zhang Liu Department of Biostatistics and Cancer Registration Guangzhou Center for Disease Control and PreventionGuangzhou 510440GuangdongP.R.China

Introduction: Colorectal cancer(CRC) is a common type of neoplasm. This study examined the spatio?temporal distribution of the CRC incidence in Guangzhou during 2010–***: Colorectal cancer incidence data were obtained from the Guangzhou Cancer Registry System. Spatial autocorrelation analysis and a retrospective spatio?temporal scan were used to assess the spatio?temporal cluster distribution of CRC ***: A total of 14,618 CRC cases were registered in Guangzhou during 2010–2014, with a crude incidence of 35.56/100,000 and an age?standardized rate of incidence by the world standard population(ASRIW) of 23.58/100,000. The crude incidence increased by 19.70% from 2010(32.88/100,000) to 2014(39.36/100,000) with an average annual percentage change(AAPC) of 4.33%. The AAPC of ASRIW was not statistically significant. The spatial autocorrelation analysis revealed a CRC incidence hot spot in central urban areas in Guangzhou City, which included 25 streets in southwestern Baiyun District, northwestern Haizhu District, and the border region between Liwan and Yuexiu Dis?tricts. Three high? and five low?incidence clusters were identified according to spatio?temporal scan of CRC incidence clusters. The high?incidence clusters were located in central urban areas including the border regions between Bai?yun, Haizhu, Liwan, and Yuexiu ***: This study revealed the spatio?temporal cluster pattern of the incidence of CRC in Guangzhou. This information can inform allocation of health resources for CRC screening.

关键词： Colorectal cancer Spatial analysis Spatial autocorrelation spatio-temporal clustering

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