A dimension-independent method for updating topological models of 4D spatio-temporal data based on generalized maps

The three-dimensional (3D) and dynamic development of land use has created a demand for updating topological relations of 4D spatio-temporal data. However, limited by data structures and updating methods, the existing spatio-temporal data updating methods are not efficient at updating complete topological relations of 4D spatio-temporal data. This paper proposes a method for updating topological models of 4D spatio-temporal topological data based on generalized maps. In this method, algorithms are designed for the removal, insert, merge and split operations of 0D-4D spatio-temporal objects. In order to avoid dimension explosion of high-dimensional topological relations, a dimension-independent structure, generalized map, is introduced to represent the topological relations of spatio-temporal objects of different dimensions, which also makes the algorithms for updating operations of different dimensions have a unified logic. Experiments verify each single operation as well as multiple operations. The results show that our proposed method can update 3D and 4D spatio-temporal topological data of different sizes and dimensions efficiently and correctly. In addition, the proposed method has been compared with other three methods based on extended simple feature model (SFM), extended simplified spatial model (SSM), and 4D formal data structure (4D FDS). The comparison results indicate that the proposed method surpasses all other models in both time and space efficiency, with significantly better spatiotemporal query efficiency compared to the other three methods.