Spatial Cloud Data Management Framework for Emergency Management

Abstract

Effective management of spatial data is critical for emergency management, and the availability of spatial data through cloud computing demands an efficient framework. This research aims to develop a 
spatial cloud data management framework for emergency management, capable of handling and analyzing large volumes of spatial data. Objectives include exploring spatial data types, designing the framework with key features, and evaluating its performance during emergencies. 
Following a design science approach, the framework comprises four layers: infrastructure, data, application, and client. It leverages cloud storage, PostgreSQL databases, open-source spatial data sources, Apache Spark, PostGIS, and forecasting models. Supporting thick and thin cloud computing clients ensures accessibility for authorized users. 
The significance of this study is evident in its transformative impact on emergency management through the integration of Spatial Big data and advanced analytics. By enhancing preparedness, response, and recovery, it contributes to minimizing the impact of disasters and protecting lives. The evaluation findings underscore its practical effectiveness, rendering it a valuable asset for both practitioners and stakeholders in the field. 
In conclusion, the spatial cloud data management framework offers a viable solution for efficient spatial data management during emergencies. Its multi-layered architecture and support for cloud clients improve emergency management operations, with practical implications for the field and future advancements.