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
With the rise of smart phones,mobile applications have been widely used in daily life.However,the relationship between individuals’mobile application usage and cities’economic development has yet to be investigated....With the rise of smart phones,mobile applications have been widely used in daily life.However,the relationship between individuals’mobile application usage and cities’economic development has yet to be investigated.To study this question,this work utilizes a dataset containing users’history of mobile application usage records(MAURs)and investigates how MAURs are related to Chinese cities’economic development.Our analysis shows the cities’GDP and number of MAURs are highly correlated,and at the individual level,people in wealthier cities(higher GDP per capita)tend to have more active mobile application usage(MAURs per capita).The results also demonstrate the relevance between cities’GDP and MAURs varies significantly among different demographic groups,with male users’relevance consistently higher than female users’and working-age people’s relevance higher than other age groups.A boosted tree regression model is then applied to predict cities’GDP with MAURs and proves to achieve high goodness-of-fit(over 0.8 R-square)and good prediction accuracy,especially for the economically developed and populous regions in China.To the best of our knowledge,this is the first time that the relationship between MAURs and cities’economic development is revealed,which contributes to novel knowledge discovery for regionalization and urban development.展开更多
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Wuhan University State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing,No.21S02。
文摘With the rise of smart phones,mobile applications have been widely used in daily life.However,the relationship between individuals’mobile application usage and cities’economic development has yet to be investigated.To study this question,this work utilizes a dataset containing users’history of mobile application usage records(MAURs)and investigates how MAURs are related to Chinese cities’economic development.Our analysis shows the cities’GDP and number of MAURs are highly correlated,and at the individual level,people in wealthier cities(higher GDP per capita)tend to have more active mobile application usage(MAURs per capita).The results also demonstrate the relevance between cities’GDP and MAURs varies significantly among different demographic groups,with male users’relevance consistently higher than female users’and working-age people’s relevance higher than other age groups.A boosted tree regression model is then applied to predict cities’GDP with MAURs and proves to achieve high goodness-of-fit(over 0.8 R-square)and good prediction accuracy,especially for the economically developed and populous regions in China.To the best of our knowledge,this is the first time that the relationship between MAURs and cities’economic development is revealed,which contributes to novel knowledge discovery for regionalization and urban development.
