Towards operational near real time oil spill detection service using polarimetric TerraSAR-X Images

Abstract

Exploitation of polarimetric features for oil spill detection is relatively new and until recently those properties were not exploited for operational services. This paper describes the development of a Near Real Time (NRT) oil spill detection processing chain using coherent dual-polarimetric (co-polarized channels, i.e. HH-VV) TerraSAR-X images. Proposed methodology introduces for the first time a combination of traditional and polarimetric features for object-based oil spill and look-alike (algae, weather induced phenomenon etc.) discrimination. A total number of 35 feature parameters were extracted from 225 oil spill and 26 look-alikes. Extracted features are then used for training and validation of a decision tree classifier. Initial performance estimation was carried out for the proposed methodology on a large dataset acquired over well-known platform location in order to evaluate its suitability for NRT operational service.