Oil spill contingency planning using Laser Fluorosensors and web-based GIS

Abstract

The oil spill contingency planning is important for protecting the oceanic environment and reducing economic losses due to oil spill disaster. A real-time GIS based oil spill detection and decision support system can be very efficient in preventing, monitoring and mitigating oil spills. The use of event-driven GIS is proposed to provide a real time application. Oil spill surveillance constitutes an important component of oil spill disaster management. Advances in remote sensing technologies can help to identify parties potentially responsible for pollution and to identify minor spills before they cause widespread damage. Laser Fluorosensors, such as the Scanning Laser Environmental Airborne Fluorosensor (SLEAF) sensor operated by Environment Canada, are among the most appropriate sensors for oil spill surveillance in light of their ability to detect oil against a variety of backgrounds, including ice and snow. Laser fluorosensor data can be processed in real time and can reliably detect oil and hence can be the most useful remote sensing data as an input for real time Decision Support Systems. A reliable and robust classification scheme is proposed for oil spill detection and classification. The oil spill trajectory will be modeled based on the available metrological and oceanic current and tidal data. This research aims to provide various oil spill disaster products such as Oil Spill Location Map, Oil Spill Risk Map, Oil Spill Affected Area Map and Oil Spill Emergency Response Map to the oil spill responders. Various disaster products can be prepared to understand the impact of oil spill. The emergency response system is designed to be Internet based so that users or emergency responders can access all the valuable information from anywhere in the world.