Research On Theory And Applications Of Spatio-temporal Data Model

Traditional GIS can only handle static spatial data and keep a transient state of the real world. Generally, historical data is replaced with fresh one to form another transient state, and we can not deal with dynamic change of spatial objects. An application oriented spatio-temporal data model is strongly needed to realize organic organization, efficient management and flexible usage of spatio-temporal data for tracking dynamic change of spatial data and meeting different application requirement of realistic world.Nowadays, spatio-temporal data has already extensively applied in different fields and corresponding spatio-temporal data model has also successively been put forward, which gradually becomes a hot research point with important theoretical value and application worth. This paper proposed a novel Markov-based spatio-temporal data model in terms of application based on the existing research results. We have verified the validity, practicability and universality of the model with the application in floating car spatio-temporal data and geographic spatio-temporal data. The main contribution of the dissertation is listed as follows:⑴The basic principle of existing spatio-temporal data model was systematically studied in the thesis. The merits and shortcomings of each spatio-temporal data model were listed out, and the universal problems of existing spatio-temporal data models were pointed out by analyzing spatial semantics, temporal semantics and spatio-temporal semantics. All these work provided a basic experience for the further spatio-temporal data model research.⑵The geography spatio-temporal objects and their space movement characteristic were analyzed. On the foundation of existing spatio-temporal data models, a noval spatio-temporal data model based on Markov chain was proposed. The data model absorbed the state transfer thought and spatio-temporal grain based on the object-oriented technique. Data model and data compression were efficiently gathered for the integral whole, and the sequence snap shot model, the ground state correction models and spatio-temporal cube model were integrated together. Thus the usability and applicability of spatio-temporal data model was significantly raised. The statistics analysis model was established for real application, which described the spatio-temporal evolvement of geography object effectively and provided a new technique means for spatio-temporal data modeling.⑶Combined with the characteristics of floating car spatio-temporal data in intelligence transportation system, a spatio-temporal data model of dynamic object was established utilizing spatio-temporal data model based on Markov chain thought. And a urban real time traffic information releases prototype system was designed to verify the usability and usefulness of the spatio-temporal data model based on Markov chain. Meanwhile, a series of new algorithms were put forward, which include the floating car adaptive sampling method oriented to actual road network, the on-line map matching algorithm based on the short-term prediction, the off-line map matching algorithm based on the similarity measure of Hausdorff distance and the floating car traffic congested status distinguishing method oriented towards dynamic navigation. The simulation and experimental results demonstrated the efficiency and superiority of these novel algorithms aimed in data collecting, data processing and information extraction of prototype system.⑷According to the multisource, multiresolution, multitemporal and isomerous properties of the geographic spatio-temporal data as remote sensing image, vector digital map and DEM, the spatio-temporal data model based on Markov chain was taken to realize the seamless link up, efficient organization, unify management, rapid search and synthesis application for the graphic spatio-temporal data. This work further provided a technical support for the geographic spatio-temporal data application and verified the usability, usefulness and adaptability of the spatio-temporal data model based on Markov chain at the same time.