In the big data era,robust solutions are obliged to be proposed to integrate and represent data from different formats and with different contents to assist the decision-making.Current cartographic and geographic info...In the big data era,robust solutions are obliged to be proposed to integrate and represent data from different formats and with different contents to assist the decision-making.Current cartographic and geographic information systems have limited capabilities for solving these problems.This paper describes an automatic and comprehensive system that conducts data fusion from all potentially related sources.In this system,a new Semantic Location Model(SemLM)is established to present the semantic concepts and location feature and demonstrate how locations are interrelated.In the SemLM,various types of location descriptors in different application scenarios can be analyzed and understood.Additionally,considering the challenges involved in data-intensive computation and visualization,this paper implements a Place-based Pan-Information System(P2S)as an innovative 4D system that dynamically associates and visualizes place-based information,using public security as the case study.展开更多
Geoportals have been the primary source of spatial information to researchers in diverse fields.Recent years have seen a growing trend to integrate spatial analysis and geovisual analytics inside Geoportals.Researcher...Geoportals have been the primary source of spatial information to researchers in diverse fields.Recent years have seen a growing trend to integrate spatial analysis and geovisual analytics inside Geoportals.Researchers could use the Geoportal to conduct basic analysis without offline processing.In practice,domain-specific analysis often requires researchers to integrate heterogeneous data sources,leverage new statistical models,or build their own customized models.These tasks are increasingly being tackled with open source tools in programming languages such as Python or R.However,it is unrealistic to incorporate the numerous open source tools in a Geoportal platform for data processing and analysis.This work provides an exploratory effort to bridge Geoportals and open source tools through Python scripting.The Geoportal demonstrated in this work is the Urban and Regional Explorer for China studies.A python package is provided to manipulate this platform in the local programming environment.The server side of the Geoportal implements a set of service endpoints that allows the package to upload,transform,and process user data and seamlessly integrate them into the existing datasets.A case study is provided that illustrated the use of this package to conduct integrated analyses of search engine data and baseline census data.This work attempts a new direction in Geoportal development,which could further promote the transformation of Geoportals into online analytical workbenches.展开更多
The COVID-19 pandemic poses unprecedented challenges around the world.Many studies have applied mobility data to explore spatiotemporal trends over time,investigate associations with other variables,and predict or sim...The COVID-19 pandemic poses unprecedented challenges around the world.Many studies have applied mobility data to explore spatiotemporal trends over time,investigate associations with other variables,and predict or simulate the spread of COVID-19.Our objective was to provide a comprehensive overview of human mobility open data to guide researchers and policymakers in conducting data-driven evaluations and decision-making for the COVID-19 pandemic and other infectious disease outbreaks.We summarized the mobility data usage in COVID-19 studies by reviewing recent publications on COVID-19 and human mobility from a data-oriented perspective.We identified three major sources of mobility data:public transit systems,mobile operators,and mobile phone applications.Four approaches have been commonly used to estimate human mobility:public transit-based flow,social activity patterns,index-based mobility data,and social media-derived mobility data.We compared mobility datasets’characteristics by assessing data privacy,quality,space–time coverage,high-performance data storage and processing,and accessibility.We also present challenges and future directions of using mobility data.This review makes a pivotal contribution to understanding the use of and access to human mobility data in the COVID-19 pandemic and future disease outbreaks.展开更多
Homeowners’Associations(HOAs)dictate landscape structure and management through legally enforceable land covenants at the neighborhood scale in the USA.Determining the location and spatial extent of HOAs is critical ...Homeowners’Associations(HOAs)dictate landscape structure and management through legally enforceable land covenants at the neighborhood scale in the USA.Determining the location and spatial extent of HOAs is critical for examining its influence.However,such analysis is confounded by the lack of spatial data at the appropriate unit for such analysis.The purpose of this paper is to develop and realize an open source implementation to automate land parcel classification,which is an initial step towards the goal of determining the impact of HOAs on urban land management.Using Maricopa County,Arizona as a testbed,we found that parcel merging processes reduce the number of subdivisions from 26,042 to 17,269,such that boundaries better align with neighborhood units to which rule sets like land covenants apply.Moreover,after an initial training period,this process was completed in just over 7 hours.This research is an important first step in enabling a number of analysis including determining the location and spatial extent of HOAs regionally and,eventually,nationally and determining proposed links between HOAs and land management outcomes.展开更多
基金This work is supported by the National Natural Science Foundation of China(grant number 41301517,41271401,41329001,41401524,1416509,and 1535031)the National Key Research and Development Program(grant number 2016YFB0502204)+3 种基金the Fundamental Research Funds for the Central Universities(grant number 413000010)National Science and Technology Support Plan,the National Key Technology R&D Program(grant number 2012BAH35B03)Guangxi Natural Science Foundation(grant number 2015GXNSFBA139191)Scientific Project of Guangxi Education Department(grant number KY2015YB189).
文摘In the big data era,robust solutions are obliged to be proposed to integrate and represent data from different formats and with different contents to assist the decision-making.Current cartographic and geographic information systems have limited capabilities for solving these problems.This paper describes an automatic and comprehensive system that conducts data fusion from all potentially related sources.In this system,a new Semantic Location Model(SemLM)is established to present the semantic concepts and location feature and demonstrate how locations are interrelated.In the SemLM,various types of location descriptors in different application scenarios can be analyzed and understood.Additionally,considering the challenges involved in data-intensive computation and visualization,this paper implements a Place-based Pan-Information System(P2S)as an innovative 4D system that dynamically associates and visualizes place-based information,using public security as the case study.
文摘Geoportals have been the primary source of spatial information to researchers in diverse fields.Recent years have seen a growing trend to integrate spatial analysis and geovisual analytics inside Geoportals.Researchers could use the Geoportal to conduct basic analysis without offline processing.In practice,domain-specific analysis often requires researchers to integrate heterogeneous data sources,leverage new statistical models,or build their own customized models.These tasks are increasingly being tackled with open source tools in programming languages such as Python or R.However,it is unrealistic to incorporate the numerous open source tools in a Geoportal platform for data processing and analysis.This work provides an exploratory effort to bridge Geoportals and open source tools through Python scripting.The Geoportal demonstrated in this work is the Urban and Regional Explorer for China studies.A python package is provided to manipulate this platform in the local programming environment.The server side of the Geoportal implements a set of service endpoints that allows the package to upload,transform,and process user data and seamlessly integrate them into the existing datasets.A case study is provided that illustrated the use of this package to conduct integrated analyses of search engine data and baseline census data.This work attempts a new direction in Geoportal development,which could further promote the transformation of Geoportals into online analytical workbenches.
基金supported by the NSF[National Science Foundation]under grant 1841403,2027540,and 2028791.
文摘The COVID-19 pandemic poses unprecedented challenges around the world.Many studies have applied mobility data to explore spatiotemporal trends over time,investigate associations with other variables,and predict or simulate the spread of COVID-19.Our objective was to provide a comprehensive overview of human mobility open data to guide researchers and policymakers in conducting data-driven evaluations and decision-making for the COVID-19 pandemic and other infectious disease outbreaks.We summarized the mobility data usage in COVID-19 studies by reviewing recent publications on COVID-19 and human mobility from a data-oriented perspective.We identified three major sources of mobility data:public transit systems,mobile operators,and mobile phone applications.Four approaches have been commonly used to estimate human mobility:public transit-based flow,social activity patterns,index-based mobility data,and social media-derived mobility data.We compared mobility datasets’characteristics by assessing data privacy,quality,space–time coverage,high-performance data storage and processing,and accessibility.We also present challenges and future directions of using mobility data.This review makes a pivotal contribution to understanding the use of and access to human mobility data in the COVID-19 pandemic and future disease outbreaks.
文摘Homeowners’Associations(HOAs)dictate landscape structure and management through legally enforceable land covenants at the neighborhood scale in the USA.Determining the location and spatial extent of HOAs is critical for examining its influence.However,such analysis is confounded by the lack of spatial data at the appropriate unit for such analysis.The purpose of this paper is to develop and realize an open source implementation to automate land parcel classification,which is an initial step towards the goal of determining the impact of HOAs on urban land management.Using Maricopa County,Arizona as a testbed,we found that parcel merging processes reduce the number of subdivisions from 26,042 to 17,269,such that boundaries better align with neighborhood units to which rule sets like land covenants apply.Moreover,after an initial training period,this process was completed in just over 7 hours.This research is an important first step in enabling a number of analysis including determining the location and spatial extent of HOAs regionally and,eventually,nationally and determining proposed links between HOAs and land management outcomes.
