Complicated Geospatial Flow Processing with Scientific Workflow

By combining geo-computing tasks and spatial-temporal data resources with specific business logic, users can deal with complex geographic problems in specific domains. Traditional geo-computing processes require manual participation if complex iterations are built. Scientific workflows support automated process to assist researchers in geo-computing and knowledge discovery. A method for complicated geospatial flow processing based on scientific workflow is proposed. Firstly, exist open source scientific workflow management systems are compared. Subsequently, the core problems of geo-computing processes are analyzed: Heterogeneous multi-source data access, the description of complex computing, the scalability of computing, and the interaction and sharing of data analysis processes. The complex geo-computing flow processing method supported by scientific workflow is put forward, which can combine the data dependencies between complicated applications. Based on Swift's excellent capabilities in process structure, dispatchable resource types, and fault tolerance levels, geospatial flow can control the sequence of different parts to be completed under the constraints of time, storage and resources. Therefore, spatial-temporal data can be searched, moved, analyzed, processed and visualized. Finally, a housing site selection case based on this method is presented to show the feasibility.