Cloud parallel spatial‐temporal data model with intelligent parameter adaptation for spatial‐temporal big data

Summary With the fast development of earth observation technology and internet of things technology, the spatial‐temporal data can be obtained with higher speed and lower cost, and spatial‐temporal big data management with existing spatial‐temporal data model has become one of the bottlenecks of spatial‐temporal applications such as e‐government construction, digital city, and smart city. Cloud parallel spatial‐temporal data model with intelligent parameter adaptation for spatial‐temporal big data provided in this paper is able to divide a spatial‐temporal problem into a lot of subdivided spatial‐temporal problems and to map the subdivided problems onto different cloud parallel computing nodes to process. This paper includes the concept, division methods, and mathematical formulas of cloud parallel spatial‐temporal data model and provides the method to intelligently find the best parameter of cloud parallel spatial‐temporal data model for solving the problem with highest parallel speedup or highest parallel efficiency in cloud parallel computing environment.