ArcticNet - ArcticNet Research

Phase 4 (2015-2018)

Automated Ice and Oil Spill Mapping ? Protecting Arctic Coastal Regions and Communities

Project Leader(s)

Clausi, David

Remote sensing, the science of aerial or satellite data capture of the earth, provides crucial information for monitoring oceans. Vast amounts of data are generated and computer-based algorithms to identify ice and oil slicks are urgently needed. For example, using radar-based images from the Canadian RADARSAT-II satellite, Canadian Ice Service (CIS) personnel manually interpret 4000 scenes annually, providing ice maps over huge (500km by 500km) regions. These maps can be used to infer ice thickness and strength to facilitate decision support systems for shipping and icebreaking. Using finer scale imagery, local ice maps for Arctic communities can be provided to aid hunting and transportation in ice regimes. CIS runs a manually operated system (ISTOP) designed to identify ocean-based oil slicks. To save time and money and to reduce human bias, there is a demand for machine algorithms that can analyze radar-based imagery for ice mapping and detecting oil spill candidates. The challenge involves sensor limitations and environment variability that confuse ice and open water and confuse oil slicks with other natural phenomena. This project?s algorithm design will also support the new Canadian satellites, known as the RADARSAT Constellation Mission (RCM), planned for launch in 2018. Contributes to IRIS: 1, 2, 3, 4