Service Component Architecture for Geographic Information System in Cloud Computing Infrastructure

This paper proposes a service integration model of service component architecture (SCA) that follows Service Oriented Architecture principles applied in services of Geographic Information Systems (GIS). GIS integrates the different types of data to bring a broader, more comprehensive view to decision makers. We have successfully integrated SCA in the domain of vending machines in the past. Readily, we focus on using this architecture to integrate related services of GIS, substantially reduce the duplication of development, publish service of disaster reduction quickly, and provide users with a completely new experiential usage in GIS domain. Meanwhile, we also address many components that can be integrated with system scaling up in GIS, such as environmental monitoring, remote-sensing image´s processing, Map services, location-based services, and so on. Therefore, we use cloud computing to solve these discussed issues. Finally, this paper implements a SCA-based Rainfall Information Application that composes web service from third party, employs GIS interpolation computation by IDW, and runs the cloud-based service by MapReduce programming model easily. The results of this study can increase development speed, reduce unnecessary work and time consuming, and make the system more stable and scalable in GIS.