Conceptualising the management of climate extreme events through the GIS-based digital twin system

Climate change has been recognised for decades, and environmental risks related to it are expected to become more common over time as the world's population continues to grow. This tendency is compounded by people congregating in areas such as coastal regions, which are becoming increasingly vulnerable due to climate change. It is demonstrated that overpopulated regions need robust early warning systems representing the region's complex systems to allow all stakeholders to receive the correct information and respond appropriately and quickly under extreme climate events to avoid losing lives and property. The concept of a 'digital twin' is proposed as an accurate virtual representation of the effect of climate events on a specific region, which can be used as a tool to achieve better resilience of cities against extreme events. A digital twin can be created by combining data from various IoT sensors and artificial intelligence with a city model to represent a digital replica of the actual world. This paper presents an up-to-date picture of the GIS-based digital twin technology developed in the last decade for the early warning of extreme climate events worldwide and their integration with the smart city management systems. The findings suggest that GIS-based digital twin technology for severe climate hazard early warning is an emerging method. Yet, it has gained prominence in recent years due to developments in technology, software development, and communication technologies. However, much more research on digital twins is necessary to create a more effective early warning system approach. This paper highlights a potential framework for the development, implementation, and application of GIS-Based digital twins in climate resilience management in coastal regions.