Study On Seamless Temporal-space Oriented Multi-domain Integrated Spatio-temporal Data Model

A spatio-temporal data model is the critical basis of the abilities to effectively represent, manage and analyze massive spatio-temporal data,which is essential to next generation GIS. None of the existing spatio-temporal data models has been widely accepted caused by the complexity of spatio-temporal change semantics,the extraordinarity of the representation of time dimension,the complexities in the technical implementation of dynamic multi-dimensional extension and overwhelming mass data generated from adding time dimension to the massive spatial data.The ongoing researches and development of GIS base platform and applications may still employ traditional spatial data models and modeling methods,which can no longer satisfy the requirement of spatio-temporal applications in GIS, especially for the management and analysis of massive spatio-temporal data.Based on spatio-temporal semantic modeling,logical modeling and physical modeling methodology,this paper presents the theory,techniques and application of seamless temporal-space oriented multi-domain integrated spatio-temporal data model(SMDI-STDM), which is oriented to integrative description for entity changes and processes-the principles of seamless temporal-space,and uses the multi-representation approach integrating feature domain,spatio-temporal field domain,event domain and relation domain.The spatio-temporal changes of many geography entities and phenomenon are summarized and a corresponding data structure is designed to achieve a more complete and effective representation for spatio-temporal change semantics.The model also develops a new method for efficiently organizing and storing massive spatio-temporal data.The main content includes as follows:(1) Literature review.Typical spatio-temporal data models are reviewed and examined which is guided by a general conceptual framework of spatio-temporal representation constructed based on spatial semantics,attribute semantics,temporal semantics and spatio-temporal semantics.(2) SMDI-STDM semantic model.The seamless temporal-space concept mainly consists of the three-level-description of the spatio-temporal changes oriented to a integrative description for the entity changes and the spatio-temporal processes.Guided by the seamless temporal-space concept,basic objects for the representation of the spatio-temporal semantics are examined,which includeds feature and spatio-temporal field,spaito-temporal chain and spatio-temporal graph,event and event chain.Then, by utilizing relation domain integrating feature domain,spatio-temporal field domain and event domain,the SMDI-STDM model based on the multi-representation approach is presented.Using the multi-domain integrated representation method,the feature-field modeling and modeling for three-levels-description of spatio-temporal changes are further discussed.(3) SMDI-STDM logic model.To implement seamless temporal-space oriented multi-domain integrated representation,a logic organization model with two layers structure is designed.â‘ On the lowest,object-relational database level, spaito-temporal extension is constructed.Spatial data types and operations,temporal data types and operations,spatio-temporal data types and operations,spatio-temporal relation and spafio-temporal algebra operations are formally defined as well as for spatio-temporal relationship.Features having spatio-temporal 5-domain structure, spatio-temporal fields in 4D spatio-temporal block structure,multi-domain relation structure,feature-field structure and spatio-temporal lib-dataset structure oriented to massive spatio-temporal data are examined.â‘¡On the middle layer,unified organization of logical data is implemented using an object oriented approach. Classes for spatio-temporal object,spatio-temporal dataset,spatio-temporal change organizer and spatio-temporal entity relationship and rule are designed.(4) SMDI-STDM physical model.In order to tackle the current difficulties of massive spatio-temporal data management,a new mode to organize and store massive spatio-temporal data based on spatio-temporal partition and spatio-temporal cluster are developed by the integration of GIS spatio-temporal data feature with current database technology.The spatio-temporal partition allows spatio-temporal unclustering entities to be stored in parallel structure at different blocks or disks. Further the spatio-temporal clustering presents the capacity of mapping entities neighboring in temporal space to their positions neighboring in physical storage.(5) Prototypes,tests and applications.A basic framework,function modules and the development strategy of Prototype GeoST are described.Series prototypes of multi-domain integrated representation are introduced.The efficiency of spatio-temporal partition and clustering method on single table from 2GB to 60 GB is tested.Finally,applications are presented.The experiments and applications show that the design of SMDI-STDM is effective, efficient,logical and practical.The modeling method based on integrative description of entity change and process could more realistically capture the essential features of geography entities and phenomenon,and may also be more acceptable.To solve the complexity of spatio-temporal change semantics,the multi-representation approach might be necessary and prototypes further show the practicability of the theory.The experiments with massive spatio-temporal data reveal that spatio-temporal partition and clustering method are efficient and logical,based on which a practical solution to effectively manage the massive spatio-temporal data could be marketed to users.