This research addresses the use of dual-polarimetric descriptors for automatic large-scale ship detection and characterization from synthetic aperture radar (SAR) data. Ship detection is usually performed independently on each polarization channel and the detection results are merged subsequently. In this study, we propose to make use of the complex coherence between the two polarization channels of Sentinel-1 and to perform vessel detection in this domain. Therefore, an automatic algorithm, based on the dual-polarization coherence, and applicable to entire large scale SAR scenes in a timely manner, is developed. Automatic identification system (AIS) data are used for an extensive and also large scale cross-comparison with the SAR-based detections. The comparative assessment allows us to evaluate the added-value of the dual-polarization complex coherence, with respect to SAR intensity images in ship detection, as well as the SAR detection performances depending on a vessel’s size. The proposed methodology is justified statistically and tested on Sentinel-1 data acquired over two different and contrasting, in terms of traffic conditions, areas: the English Channel the and Pacific coastline of Mexico. The results indicate a very high SAR detection rate, i.e., >80%, for vessels larger than 60 m and a decrease of detection rate up to 40 % for smaller size vessels. In addition, the analysis highlights many SAR detections without corresponding AIS positions, indicating the complementarity of SAR with respect to cooperative sources for detecting dark vessels.
The paper presents a proposal for a framework for the identification, assessment and selection of open data sources based on certain quality criteria, such as accessibility, relevance, accuracy & reliability, clarity, timeliness & punctuality, and coherence & comparability. The framework concerns mainly open data sources and focuses on their quality. The open data are used to enhance existing internal data and to fuse them with data from other sources. The framework consists of few steps starting from definition of quality criteria based on review of relevant literature and user requirements, then identification of potential sources, sources assessment and selection, and finally data retrieval process. For each step, a specific approach is described, how it may be conducted in practice. The proposed framework is evaluated using a real use case scenario from the maritime domain. The main approach utilized in this use-case is the Delphi method with some characteristics of Analytic Hierarchy Process.
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