Effective spatial data maintenance during the operation and maintenance phase of airports is imperative for the infrastructure safety,operational effectiveness,and compliance with regulations.However,airports encounte...Effective spatial data maintenance during the operation and maintenance phase of airports is imperative for the infrastructure safety,operational effectiveness,and compliance with regulations.However,airports encounter serious challenges such as lack of management support,insufficient funding,and poor-quality data sources.Despite the recognised potential of emerging technologies such as digital twins,digital threads,ontologies,scalable data architectures,and governance frameworks,their integrated application for airport spatial data management remains unexplored.The existing literature focuses on analysing these technologies individually,leaving a large gap for their combined application for end-to-end comprehensive spatial data maintenance.To bridge this gap,this research proposes a comprehensive,literature-based framework using qualitative research as the underlying approach with the inclusion of a comprehensive literature review,and semi-structured interviews with experts for practical significance and theoretical richness.By employing inductive thematic analysis,we identified critical drivers and challenges in the practice of spatial data maintenance.The proposed framework brings together digital twins for realistic infrastructure simulation,digital threads for end-to-end data traceability,ontologies for semantic interoperability,data lakehouses for cost-optimisation,and a governance layer for compliance and data integrity.The integrated ecosystem addresses the identified challenges by leveraging the identified drivers and technological synergies,enhancing data-driven decision-making capabilities across diversified airport settings.Although the proposed framework is theoretically validated,it must be tested on real airports,representing a critical limitation.Additionally,the scope of the research is constrained by stakeholder insights primarily from medium-sized U.S.airports,which may limit applicability for large airports or other regulatory frameworks.Future research will involve piloting the framework for empirical testing of performance and adaptability,enhancing stakeholder engagement across the world,examining the strategies for mainstreaming with existing airport systems,and addressing ethical and cybersecurity issues.展开更多
A novel Hilbert-curve is introduced for parallel spatial data partitioning,with consideration of the huge-amount property of spatial information and the variable-length characteristic of vector data items.Based on the...A novel Hilbert-curve is introduced for parallel spatial data partitioning,with consideration of the huge-amount property of spatial information and the variable-length characteristic of vector data items.Based on the improved Hilbert curve,the algorithm can be designed to achieve almost-uniform spatial data partitioning among multiple disks in parallel spatial databases.Thus,the phenomenon of data imbalance can be significantly avoided and search and query efficiency can be enhanced.展开更多
In this paper we propose a service-oriented architecture for spatial data integration(SOA-SDI)in the context of a large number of available spatial data sources that are physically sitting at different places,and deve...In this paper we propose a service-oriented architecture for spatial data integration(SOA-SDI)in the context of a large number of available spatial data sources that are physically sitting at different places,and develop web-based GIS systems based on SOA-SDI,allowing client applications to pull in,analyze and present spatial data from those available spatial data sources.The proposed architecture logically includes 4 layers or components;they are layer of multiple data provider services,layer of data in-tegration,layer of backend services,and front-end graphical user interface(GUI)for spatial data presentation.On the basis of the 4-layered SOA-SDI framework,WebGIS applications can be quickly deployed,which proves that SOA-SDI has the potential to reduce the input of software development and shorten the development period.展开更多
In order to provide a provincial spatial database,this paper presents a scheme for spatial database construction to meet the needs of China.The objective and overall technical route of spatial database construction ar...In order to provide a provincial spatial database,this paper presents a scheme for spatial database construction to meet the needs of China.The objective and overall technical route of spatial database construction are described.The logical and physical database models are designed.Key issues are addressed,such as integration of multi-scale heterogeneous spatial databases,spatial data version management based on metadata and integrative management of map cartography and spatial database.展开更多
To improve the performance of the traditional map matching algorithms in freeway traffic state monitoring systems using the low logging frequency GPS (global positioning system) probe data, a map matching algorithm ...To improve the performance of the traditional map matching algorithms in freeway traffic state monitoring systems using the low logging frequency GPS (global positioning system) probe data, a map matching algorithm based on the Oracle spatial data model is proposed. The algorithm uses the Oracle road network data model to analyze the spatial relationships between massive GPS positioning points and freeway networks, builds an N-shortest path algorithm to find reasonable candidate routes between GPS positioning points efficiently, and uses the fuzzy logic inference system to determine the final matched traveling route. According to the implementation with field data from Los Angeles, the computation speed of the algorithm is about 135 GPS positioning points per second and the accuracy is 98.9%. The results demonstrate the effectiveness and accuracy of the proposed algorithm for mapping massive GPS positioning data onto freeway networks with complex geometric characteristics.展开更多
The mathematic theory for uncertainty model of line segment are summed up to achieve a general conception, and the line error hand model of εσ is a basic uncertainty model that can depict the line accuracy and quali...The mathematic theory for uncertainty model of line segment are summed up to achieve a general conception, and the line error hand model of εσ is a basic uncertainty model that can depict the line accuracy and quality efficiently while the model of εm and error entropy can be regarded as the supplement of it. The error band model will reflect and describe the influence of line uncertainty on polygon uncertainty. Therefore, the statistical characteristic of the line error is studied deeply by analyzing the probability that the line error falls into a certain range. Moreover, the theory accordance is achieved in the selecting the error buffer for line feature and the error indicator. The relationship of the accuracy of area for a polygon with the error loop for a polygon boundary is deduced and computed.展开更多
Nowadays, more and more digitalized spatial data are sold and transmitted on the Internet. Thus, there arises an important issue about copyright protection of the digital data. To solve this problem, this paper has de...Nowadays, more and more digitalized spatial data are sold and transmitted on the Internet. Thus, there arises an important issue about copyright protection of the digital data. To solve this problem, this paper has designed and implemented a spatial data watermarking service (SDWS) system which can provide a secure framework for data transaction and transfer via the Internet and protect the rights of both copyright owners and consumers at the same time.展开更多
Spatial data is a key resource for national development. There is a lot of potential locked in spatial data and this potential may be realized by making spatial data readily available for various applications. SD1 (S...Spatial data is a key resource for national development. There is a lot of potential locked in spatial data and this potential may be realized by making spatial data readily available for various applications. SD1 (Spatial Data Infrastructures) provides a platform for the data users, producers and so on to generate and share spatial data effectively. Though efforts to develop spatial data infrastructures started worldwide in the late 1970s, SDIs are still perceived by many institutions as new innovation; as such, they have not penetrated to all institutions to bring about effective management and development changes. This paper is reporting on a study conducted to assess SDI Readiness Index for Tanzania. The study aimed at identifying problems undermining SD1 implementation in Tanzania, despite its potential in bringing fast socio-economic development elsewhere in the world. This paper is based on a research based on views from stakeholders of geospatial technology industry in Municipal Councils, Private Companies and Government Departments in Tanzania. Results indicated that Private Companies are more inspired than Government institutions towards implementation of SDIs. And those problems affecting implementation of SDIs are lack of National SDI Policy, lack of awareness and knowledge about SDIs, limited funding to operationalise SDI, lack of institutional leadership to coordinate SDI development activities, lack of political commitment from the Government. It is recommended that delibate efforts be devised to raise awareness of SDI amongst the Tanzanian community.展开更多
The growth of geo-technologies and the development of methods for spatial data collection have resulted in large spatial data repositories that require techniques for spatial information extraction, in order to transf...The growth of geo-technologies and the development of methods for spatial data collection have resulted in large spatial data repositories that require techniques for spatial information extraction, in order to transform raw data into useful previously unknown information. However, due to the high complexity of spatial data mining, the need for spatial relationship comprehension and its characteristics, efforts have been directed towards improving algorithms in order to provide an increase of performance and quality of results. Likewise, several issues have been addressed to spatial data mining, including environmental management, which is the focus of this paper. The main original contribution of this work is the demonstration of spatial data mining using a novel algorithm with a multi-relational approach that was applied to a database related to water resource from a certain region of S^o Paulo State, Brazil, and the discussion about obtained results. Some characteristics involving the location of water resources and the profile of who is administering the water exploration were discovered and discussed.展开更多
The paper aims to present a concise overview of the current status of the national spatial data infrastructures(SDI)of the European Union(EU)member states combined with specific peculiarities for Bulgaria.Some major c...The paper aims to present a concise overview of the current status of the national spatial data infrastructures(SDI)of the European Union(EU)member states combined with specific peculiarities for Bulgaria.Some major challenges within the progress of the EU SDIs establishing,which is regulated by the European Directive INSPIRE(Infrastructure for spatial information in Europe)toward establishment of a SDI for environmental policies and activities,are marked out.Available comparative analyses of the main indicators for metadata,data-sets,and data services provided by EU member states are briefly discussed as a special attention is given to the Bulgarian progress.Recent achievements on accelerating the process of implementing the recommendations of the INSPIRE Directive in Bulgaria are outlined.展开更多
Background A task assigned to space exploration satellites involves detecting the physical environment within a certain space.However,space detection data are complex and abstract.These data are not conducive for rese...Background A task assigned to space exploration satellites involves detecting the physical environment within a certain space.However,space detection data are complex and abstract.These data are not conducive for researchers'visual perceptions of the evolution and interaction of events in the space environment.Methods A time-series dynamic data sampling method for large-scale space was proposed for sample detection data in space and time,and the corresponding relationships between data location features and other attribute features were established.A tone-mapping method based on statistical histogram equalization was proposed and applied to the final attribute feature data.The visualization process is optimized for rendering by merging materials,reducing the number of patches,and performing other operations.Results The results of sampling,feature extraction,and uniform visualization of the detection data of complex types,long duration spans,and uneven spatial distributions were obtained.The real-time visualization of large-scale spatial structures using augmented reality devices,particularly low-performance devices,was also investigated.Conclusions The proposed visualization system can reconstruct the three-dimensional structure of a large-scale space,express the structure and changes in the spatial environment using augmented reality,and assist in intuitively discovering spatial environmental events and evolutionary rules.展开更多
Presented a study on the design and implementation of spatial data modelingand application in the spatial data organization and management of a coalfield geologicalenvironment database.Based on analysis of a number of...Presented a study on the design and implementation of spatial data modelingand application in the spatial data organization and management of a coalfield geologicalenvironment database.Based on analysis of a number of existing data models and takinginto account the unique data structure and characteristic, methodology and key techniquesin the object-oriented spatial data modeling were proposed for the coalfield geological environment.The model building process was developed using object-oriented technologyand the Unified Modeling Language (UML) on the platform of ESRI geodatabase datamodels.A case study of spatial data modeling in UML was presented with successful implementationin the spatial database of the coalfield geological environment.The modelbuilding and implementation provided an effective way of representing the complexity andspecificity of coalfield geological environment spatial data and an integrated managementof spatial and property data.展开更多
The authors designed the spatial data mining system for ore-forming prediction based on the theory and methods of data mining as well as the technique of spatial database,in combination with the characteristics of geo...The authors designed the spatial data mining system for ore-forming prediction based on the theory and methods of data mining as well as the technique of spatial database,in combination with the characteristics of geological information data.The system consists of data management,data mining and knowledge discovery,knowledge representation.It can syncretize multi-source geosciences data effectively,such as geology,geochemistry,geophysics,RS.The system digitized geological information data as data layer files which consist of the two numerical values,to store these files in the system database.According to the combination of the characters of geological information,metallogenic prognosis was realized,as an example from some area in Heilongjiang Province.The prospect area of hydrothermal copper deposit was determined.展开更多
Despite the recent development of many worldwide initiatives, there is still a need for the development of observation frameworks that will provide a comprehensive view of SDI’s use. Amongst the many challenges left,...Despite the recent development of many worldwide initiatives, there is still a need for the development of observation frameworks that will provide a comprehensive view of SDI’s use. Amongst the many challenges left, a thorough analysis of the information flows between existing SDIs as well as their respective uses and the way that those evolve over time is an important issue to explore. The research presented in this paper introduces a methodological framework oriented to the study of the SDIs use from a diachronic perspective. The approach is based on a Social Network Analysis (SNA) and questionnaires collected by online surveys. We develop a structural and diachronic analysis based on a series of graph-based measures identifying the main patterns that appear over time. The methodological framework is applied to a series of French SDIs and users involved in environmental management. The study identifies a series of structural differences in the data flows that emerge between the users and SDIs. Last, the diachronic network analysis provides an overall understanding on how data flows evolve over time at different institutional levels.展开更多
Purpose: A geographic information system (GIS) in a combination with health data is very useful for disease monitoring, prevention and control. The new sciences of the combination of GIS and classical health data, nam...Purpose: A geographic information system (GIS) in a combination with health data is very useful for disease monitoring, prevention and control. The new sciences of the combination of GIS and classical health data, namely spatial epidemiology. Methods: Using the secondary health database (including COVID-19 data);data source is the 43 standard data folders of Thailand health statistic collected by Ministry of Public Health Thailand, collected between 2013 and 2022. The data of the Heath Region 6 of Thailand was used as an example. Twodata sets health data with spatial data Combined to new database and developed dashboard to present the information via web base system. Results: The dash board provides new perspective of disease distribution view. For example, the map on our dashboard reports the density of COVID-19 cases in each area. Based on the records, the densest areas shown are the urban area in each province. It can also be used for resource distribution and access time to health center of the area. Conclusion: The project reports the use of GIS and public health data to develop a dashboard for monitoring health resources and disease distributions in the health region 6 of Thailand. The major limitation of spatial epidemiology is the lack of or incomplete raw data input in the system.展开更多
Data is undoubtedly becoming a commodity like oil,land,and labour in the 21st century.Although there have been many successful marketplaces for data trading,the existing data marketplaces lack consideration of the cas...Data is undoubtedly becoming a commodity like oil,land,and labour in the 21st century.Although there have been many successful marketplaces for data trading,the existing data marketplaces lack consideration of the case where buyers want to acquire a collection of datasets(instead of one),and the overall spatial coverage and connectivity matter.In this paper,we make the first attempt to formulate this problem as Budgeted Maximum Coverage with Connectivity Constraint(BMCC),which aims to acquire a dataset collection with the maximum spatial coverage under a limited budget while maintaining spatial connectivity.To solve the problem,we propose two approximate algorithms with detailed theoretical guarantees and time complexity analysis,followed by two acceleration strategies to further improve the efficiency of the algorithm.Experiments are conducted on five real-world spatial dataset collections to verify the efficiency and effectiveness of our algorithms.展开更多
Clustering, in data mining, is a useful technique for discovering interesting data distributions and patterns in the underlying data, and has many application fields, such as statistical data analysis, pattern recogni...Clustering, in data mining, is a useful technique for discovering interesting data distributions and patterns in the underlying data, and has many application fields, such as statistical data analysis, pattern recognition, image processing, and etc. We combine sampling technique with DBSCAN algorithm to cluster large spatial databases, and two sampling based DBSCAN (SDBSCAN) algorithms are developed. One algorithm introduces sampling technique inside DBSCAN, and the other uses sampling procedure outside DBSCAN. Experimental results demonstrate that our algorithms are effective and efficient in clustering large scale spatial databases.展开更多
Recently, attention has been focused on spatial query language which is used to query spatial databases. A design of spatial query language has been presented in this paper by extending the standard relational databas...Recently, attention has been focused on spatial query language which is used to query spatial databases. A design of spatial query language has been presented in this paper by extending the standard relational database query language SQL. It recognizes the significantly different requirements of spatial data handling and overcomes the inherent problems of the application of conventional database query languages. This design is based on an extended spatial data model, including the spatial data types and the spatial operators on them. The processing and optimization of spatial queries have also been discussed in this design. In the end, an implementation of this design is given in a spatial query subsystem.展开更多
Based on the traditional spatial data analysis, a novel mode of spatial data mining and visualization is proposed which integrates the self-organizing map for the actual problem. Simulations for IRIS data show that th...Based on the traditional spatial data analysis, a novel mode of spatial data mining and visualization is proposed which integrates the self-organizing map for the actual problem. Simulations for IRIS data show that this method (computational and visual) can collaboratively discover complex pattems in large spatial datasets, in an effective and efficient way.展开更多
The Internet technology has already changed the Information Society in profound ways, and will continue to do so. Nowadays many people foresee that there is a similar trajectory for the next generation of Internet - G...The Internet technology has already changed the Information Society in profound ways, and will continue to do so. Nowadays many people foresee that there is a similar trajectory for the next generation of Internet - Grid Technology. As an emerging computational and networking infrastructure, Grid Computing is designed to provide pervasive, uniform and reliable access to data, computational and human resources distributed in a dynamic, heterogeneous environment. On the other hand, the development of Geographic Information System (GIS) has been highly influenced by the evolution of information technology such as the Internet, telecommunications, software and various types of computing technology. In particular, in the distributed GIS domain, the development However, due to the closed and centralized has made significant impact in the past decade. legacy of the architecture and the lack of interoperability, modularity, and flexibility, current distributed GIS still cannot fully accommodate the distributed, dynamic, heterogeneous and speedy development in network and computing environments. Hence, the development of a high performance distributed GIS system is still a challenging task. So, the development of Grid computing technology undoubtedly provides a unique opportunity for distributed GIS, and a Grid Computing based GIS paradigm becomes inevitable. This paper proposes a new computing platform based distributed GIS framework - the Grid Geographic Information System (G^2IS).展开更多
摘要Effective spatial data maintenance during the operation and maintenance phase of airports is imperative for the infrastructure safety,operational effectiveness,and compliance with regulations.However,airports encounter serious challenges such as lack of management support,insufficient funding,and poor-quality data sources.Despite the recognised potential of emerging technologies such as digital twins,digital threads,ontologies,scalable data architectures,and governance frameworks,their integrated application for airport spatial data management remains unexplored.The existing literature focuses on analysing these technologies individually,leaving a large gap for their combined application for end-to-end comprehensive spatial data maintenance.To bridge this gap,this research proposes a comprehensive,literature-based framework using qualitative research as the underlying approach with the inclusion of a comprehensive literature review,and semi-structured interviews with experts for practical significance and theoretical richness.By employing inductive thematic analysis,we identified critical drivers and challenges in the practice of spatial data maintenance.The proposed framework brings together digital twins for realistic infrastructure simulation,digital threads for end-to-end data traceability,ontologies for semantic interoperability,data lakehouses for cost-optimisation,and a governance layer for compliance and data integrity.The integrated ecosystem addresses the identified challenges by leveraging the identified drivers and technological synergies,enhancing data-driven decision-making capabilities across diversified airport settings.Although the proposed framework is theoretically validated,it must be tested on real airports,representing a critical limitation.Additionally,the scope of the research is constrained by stakeholder insights primarily from medium-sized U.S.airports,which may limit applicability for large airports or other regulatory frameworks.Future research will involve piloting the framework for empirical testing of performance and adaptability,enhancing stakeholder engagement across the world,examining the strategies for mainstreaming with existing airport systems,and addressing ethical and cybersecurity issues.
基金Funded by the National 863 Program of China(No.2005AA113150)the National Natural Science Foundation of China(No.40701158).
摘要A novel Hilbert-curve is introduced for parallel spatial data partitioning,with consideration of the huge-amount property of spatial information and the variable-length characteristic of vector data items.Based on the improved Hilbert curve,the algorithm can be designed to achieve almost-uniform spatial data partitioning among multiple disks in parallel spatial databases.Thus,the phenomenon of data imbalance can be significantly avoided and search and query efficiency can be enhanced.
基金Supported by the Research Fund of Key GIS Lab of the Education Ministry(No.200610)
摘要In this paper we propose a service-oriented architecture for spatial data integration(SOA-SDI)in the context of a large number of available spatial data sources that are physically sitting at different places,and develop web-based GIS systems based on SOA-SDI,allowing client applications to pull in,analyze and present spatial data from those available spatial data sources.The proposed architecture logically includes 4 layers or components;they are layer of multiple data provider services,layer of data in-tegration,layer of backend services,and front-end graphical user interface(GUI)for spatial data presentation.On the basis of the 4-layered SOA-SDI framework,WebGIS applications can be quickly deployed,which proves that SOA-SDI has the potential to reduce the input of software development and shorten the development period.
基金Supported by the 863 High Technology Program of China(No.2007AA12Z214)the National Natural Science Foundation of China(No.40601083)the National Key Basic Research and Development Program of China(No.2004CB318206).
摘要In order to provide a provincial spatial database,this paper presents a scheme for spatial database construction to meet the needs of China.The objective and overall technical route of spatial database construction are described.The logical and physical database models are designed.Key issues are addressed,such as integration of multi-scale heterogeneous spatial databases,spatial data version management based on metadata and integrative management of map cartography and spatial database.
摘要To improve the performance of the traditional map matching algorithms in freeway traffic state monitoring systems using the low logging frequency GPS (global positioning system) probe data, a map matching algorithm based on the Oracle spatial data model is proposed. The algorithm uses the Oracle road network data model to analyze the spatial relationships between massive GPS positioning points and freeway networks, builds an N-shortest path algorithm to find reasonable candidate routes between GPS positioning points efficiently, and uses the fuzzy logic inference system to determine the final matched traveling route. According to the implementation with field data from Los Angeles, the computation speed of the algorithm is about 135 GPS positioning points per second and the accuracy is 98.9%. The results demonstrate the effectiveness and accuracy of the proposed algorithm for mapping massive GPS positioning data onto freeway networks with complex geometric characteristics.
基金Project supported by the National Natural Science Foundation of China (No.40301043) .
摘要The mathematic theory for uncertainty model of line segment are summed up to achieve a general conception, and the line error hand model of εσ is a basic uncertainty model that can depict the line accuracy and quality efficiently while the model of εm and error entropy can be regarded as the supplement of it. The error band model will reflect and describe the influence of line uncertainty on polygon uncertainty. Therefore, the statistical characteristic of the line error is studied deeply by analyzing the probability that the line error falls into a certain range. Moreover, the theory accordance is achieved in the selecting the error buffer for line feature and the error indicator. The relationship of the accuracy of area for a polygon with the error loop for a polygon boundary is deduced and computed.
基金Supported by the National High Technology Research and Development Program of China(No.2006AA12Z210)
摘要Nowadays, more and more digitalized spatial data are sold and transmitted on the Internet. Thus, there arises an important issue about copyright protection of the digital data. To solve this problem, this paper has designed and implemented a spatial data watermarking service (SDWS) system which can provide a secure framework for data transaction and transfer via the Internet and protect the rights of both copyright owners and consumers at the same time.
摘要Spatial data is a key resource for national development. There is a lot of potential locked in spatial data and this potential may be realized by making spatial data readily available for various applications. SD1 (Spatial Data Infrastructures) provides a platform for the data users, producers and so on to generate and share spatial data effectively. Though efforts to develop spatial data infrastructures started worldwide in the late 1970s, SDIs are still perceived by many institutions as new innovation; as such, they have not penetrated to all institutions to bring about effective management and development changes. This paper is reporting on a study conducted to assess SDI Readiness Index for Tanzania. The study aimed at identifying problems undermining SD1 implementation in Tanzania, despite its potential in bringing fast socio-economic development elsewhere in the world. This paper is based on a research based on views from stakeholders of geospatial technology industry in Municipal Councils, Private Companies and Government Departments in Tanzania. Results indicated that Private Companies are more inspired than Government institutions towards implementation of SDIs. And those problems affecting implementation of SDIs are lack of National SDI Policy, lack of awareness and knowledge about SDIs, limited funding to operationalise SDI, lack of institutional leadership to coordinate SDI development activities, lack of political commitment from the Government. It is recommended that delibate efforts be devised to raise awareness of SDI amongst the Tanzanian community.
摘要The growth of geo-technologies and the development of methods for spatial data collection have resulted in large spatial data repositories that require techniques for spatial information extraction, in order to transform raw data into useful previously unknown information. However, due to the high complexity of spatial data mining, the need for spatial relationship comprehension and its characteristics, efforts have been directed towards improving algorithms in order to provide an increase of performance and quality of results. Likewise, several issues have been addressed to spatial data mining, including environmental management, which is the focus of this paper. The main original contribution of this work is the demonstration of spatial data mining using a novel algorithm with a multi-relational approach that was applied to a database related to water resource from a certain region of S^o Paulo State, Brazil, and the discussion about obtained results. Some characteristics involving the location of water resources and the profile of who is administering the water exploration were discovered and discussed.
摘要The paper aims to present a concise overview of the current status of the national spatial data infrastructures(SDI)of the European Union(EU)member states combined with specific peculiarities for Bulgaria.Some major challenges within the progress of the EU SDIs establishing,which is regulated by the European Directive INSPIRE(Infrastructure for spatial information in Europe)toward establishment of a SDI for environmental policies and activities,are marked out.Available comparative analyses of the main indicators for metadata,data-sets,and data services provided by EU member states are briefly discussed as a special attention is given to the Bulgarian progress.Recent achievements on accelerating the process of implementing the recommendations of the INSPIRE Directive in Bulgaria are outlined.
摘要Background A task assigned to space exploration satellites involves detecting the physical environment within a certain space.However,space detection data are complex and abstract.These data are not conducive for researchers'visual perceptions of the evolution and interaction of events in the space environment.Methods A time-series dynamic data sampling method for large-scale space was proposed for sample detection data in space and time,and the corresponding relationships between data location features and other attribute features were established.A tone-mapping method based on statistical histogram equalization was proposed and applied to the final attribute feature data.The visualization process is optimized for rendering by merging materials,reducing the number of patches,and performing other operations.Results The results of sampling,feature extraction,and uniform visualization of the detection data of complex types,long duration spans,and uneven spatial distributions were obtained.The real-time visualization of large-scale spatial structures using augmented reality devices,particularly low-performance devices,was also investigated.Conclusions The proposed visualization system can reconstruct the three-dimensional structure of a large-scale space,express the structure and changes in the spatial environment using augmented reality,and assist in intuitively discovering spatial environmental events and evolutionary rules.
基金Supported by the Natural Science Foundation of Shanxi Province(2008011028-2)
摘要Presented a study on the design and implementation of spatial data modelingand application in the spatial data organization and management of a coalfield geologicalenvironment database.Based on analysis of a number of existing data models and takinginto account the unique data structure and characteristic, methodology and key techniquesin the object-oriented spatial data modeling were proposed for the coalfield geological environment.The model building process was developed using object-oriented technologyand the Unified Modeling Language (UML) on the platform of ESRI geodatabase datamodels.A case study of spatial data modeling in UML was presented with successful implementationin the spatial database of the coalfield geological environment.The modelbuilding and implementation provided an effective way of representing the complexity andspecificity of coalfield geological environment spatial data and an integrated managementof spatial and property data.
摘要The authors designed the spatial data mining system for ore-forming prediction based on the theory and methods of data mining as well as the technique of spatial database,in combination with the characteristics of geological information data.The system consists of data management,data mining and knowledge discovery,knowledge representation.It can syncretize multi-source geosciences data effectively,such as geology,geochemistry,geophysics,RS.The system digitized geological information data as data layer files which consist of the two numerical values,to store these files in the system database.According to the combination of the characters of geological information,metallogenic prognosis was realized,as an example from some area in Heilongjiang Province.The prospect area of hydrothermal copper deposit was determined.
摘要Despite the recent development of many worldwide initiatives, there is still a need for the development of observation frameworks that will provide a comprehensive view of SDI’s use. Amongst the many challenges left, a thorough analysis of the information flows between existing SDIs as well as their respective uses and the way that those evolve over time is an important issue to explore. The research presented in this paper introduces a methodological framework oriented to the study of the SDIs use from a diachronic perspective. The approach is based on a Social Network Analysis (SNA) and questionnaires collected by online surveys. We develop a structural and diachronic analysis based on a series of graph-based measures identifying the main patterns that appear over time. The methodological framework is applied to a series of French SDIs and users involved in environmental management. The study identifies a series of structural differences in the data flows that emerge between the users and SDIs. Last, the diachronic network analysis provides an overall understanding on how data flows evolve over time at different institutional levels.
摘要Purpose: A geographic information system (GIS) in a combination with health data is very useful for disease monitoring, prevention and control. The new sciences of the combination of GIS and classical health data, namely spatial epidemiology. Methods: Using the secondary health database (including COVID-19 data);data source is the 43 standard data folders of Thailand health statistic collected by Ministry of Public Health Thailand, collected between 2013 and 2022. The data of the Heath Region 6 of Thailand was used as an example. Twodata sets health data with spatial data Combined to new database and developed dashboard to present the information via web base system. Results: The dash board provides new perspective of disease distribution view. For example, the map on our dashboard reports the density of COVID-19 cases in each area. Based on the records, the densest areas shown are the urban area in each province. It can also be used for resource distribution and access time to health center of the area. Conclusion: The project reports the use of GIS and public health data to develop a dashboard for monitoring health resources and disease distributions in the health region 6 of Thailand. The major limitation of spatial epidemiology is the lack of or incomplete raw data input in the system.
基金supported by the National Key R&D Program of China(Grant No.2023YFB4503600)the National Natural Science Foundation of China(Grant Nos.62202338 and 62372337)the Key R&D Program of Hubei Province(Grant No.2023BAB081).
摘要Data is undoubtedly becoming a commodity like oil,land,and labour in the 21st century.Although there have been many successful marketplaces for data trading,the existing data marketplaces lack consideration of the case where buyers want to acquire a collection of datasets(instead of one),and the overall spatial coverage and connectivity matter.In this paper,we make the first attempt to formulate this problem as Budgeted Maximum Coverage with Connectivity Constraint(BMCC),which aims to acquire a dataset collection with the maximum spatial coverage under a limited budget while maintaining spatial connectivity.To solve the problem,we propose two approximate algorithms with detailed theoretical guarantees and time complexity analysis,followed by two acceleration strategies to further improve the efficiency of the algorithm.Experiments are conducted on five real-world spatial dataset collections to verify the efficiency and effectiveness of our algorithms.
基金Supported by the Open Researches Fund Program of L IESMARS(WKL(0 0 ) 0 30 2 )
摘要Clustering, in data mining, is a useful technique for discovering interesting data distributions and patterns in the underlying data, and has many application fields, such as statistical data analysis, pattern recognition, image processing, and etc. We combine sampling technique with DBSCAN algorithm to cluster large spatial databases, and two sampling based DBSCAN (SDBSCAN) algorithms are developed. One algorithm introduces sampling technique inside DBSCAN, and the other uses sampling procedure outside DBSCAN. Experimental results demonstrate that our algorithms are effective and efficient in clustering large scale spatial databases.
基金This work is supported by the National High Technology Research and Development Program ofChina(2 0 0 2 AA135 2 30 ) and the Major Project of National Natural Science Foundation of Beijing(4 0 110 0 2 ) .
摘要Recently, attention has been focused on spatial query language which is used to query spatial databases. A design of spatial query language has been presented in this paper by extending the standard relational database query language SQL. It recognizes the significantly different requirements of spatial data handling and overcomes the inherent problems of the application of conventional database query languages. This design is based on an extended spatial data model, including the spatial data types and the spatial operators on them. The processing and optimization of spatial queries have also been discussed in this design. In the end, an implementation of this design is given in a spatial query subsystem.
摘要Based on the traditional spatial data analysis, a novel mode of spatial data mining and visualization is proposed which integrates the self-organizing map for the actual problem. Simulations for IRIS data show that this method (computational and visual) can collaboratively discover complex pattems in large spatial datasets, in an effective and efficient way.
摘要The Internet technology has already changed the Information Society in profound ways, and will continue to do so. Nowadays many people foresee that there is a similar trajectory for the next generation of Internet - Grid Technology. As an emerging computational and networking infrastructure, Grid Computing is designed to provide pervasive, uniform and reliable access to data, computational and human resources distributed in a dynamic, heterogeneous environment. On the other hand, the development of Geographic Information System (GIS) has been highly influenced by the evolution of information technology such as the Internet, telecommunications, software and various types of computing technology. In particular, in the distributed GIS domain, the development However, due to the closed and centralized has made significant impact in the past decade. legacy of the architecture and the lack of interoperability, modularity, and flexibility, current distributed GIS still cannot fully accommodate the distributed, dynamic, heterogeneous and speedy development in network and computing environments. Hence, the development of a high performance distributed GIS system is still a challenging task. So, the development of Grid computing technology undoubtedly provides a unique opportunity for distributed GIS, and a Grid Computing based GIS paradigm becomes inevitable. This paper proposes a new computing platform based distributed GIS framework - the Grid Geographic Information System (G^2IS).