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The detection and classification of SAR imaged vessels at sea is a valuable ability for organisations interested in the marine environment or marine vessels. Matching the SAR detected vessels to their AIS messages allows vessels to be identified and context given to their activities. With sparse AIS data, or other identifying geospatial data, an amount of positional uncertainty is introduced that...
Oil spills present a major threat to the sea ecosystem and thus need to be monitored on a regular basis. Synthetic Aperture Radar (SAR) data is well known for ocean monitoring capabilities. SENTINEL 1 (SEN1) extra wide (EW) mode data and RADARSAT-2 (RS2) Maritime Satellite Surveillance Radar (MSSR) modes have been developed to further improve ocean surveillance. This data can monitor large areas (400...
A major task in any discrimination scenario requires the collection and validation of as many examples as possible. Depending on the type of data this can be a time consuming process, especially when dealing with large remote sensing data such as Synthetic Aperture Radar imagery. To aid in the creation of improved machine learning-based ship detection and discrimination methods this paper applies...
Detections and classification of non-AIS-compliant vessels is an important ability for countries or institutions interested in MDA. SAR has been proven to be an effective method but there exists a trade-off between the area that can be imaged and the resolution of each image pixel. Large swath SAR images are a cost effective method of performing maritime surveillance but classification or identification...
The detection of ships at sea is a complex task made more so by adverse weather conditions, lack of night visibility, and large areas of concern. Synthetic aperture radar (SAR) imagery with large swaths can provide the needed coverage at a reduced resolution. The development of ship detection methods that can effectively detect ships despite the reduced image resolution is an important area of research...
An automatic approach to detect bilge dumping in synthetic aperture radar (SAR) images over Southern African oceans is proposed. The approach uses a threshold-based algorithm and a region-based active contour model (ACM) algorithm to achieve an efficient bilge dump detection tool. A threshold method was used to detect areas with a high bilge dump probability while the ACM method is used to get closed...
Efficient and effective ship discrimination across multiple Synthetic Aperture Radar sensors is becoming more important as access to SAR data becomes more widespread. A flexible means of separating ships from sea is ideal and can be accomplished using machine learning. Newer, advanced deep learning techniques offer a unique solution but traditionally require a large dataset to train effectively. Highway...
Monitoring ocean vessels that are not near the coast is difficult and expensive. One way of overcoming this is through the use of SAR satellite platforms. To monitor the largest possible area would require the use of course resolution SAR images which reduce even the largest ships to several pixels. This paper covers the datasets, methods and results used to arrive at a machine learning algorithm...
An important aspect of research in the remote sensing field is to objectively compare different classifiers. This is the foundation of hundreds of research projects and in this paper we will address some raising concerns when evaluating solutions for classification of data sets with skewed class distributions. The quality of assessment is based on the problem specified by the user and the corresponding...
The Maritime Domain Awareness initiative seeks to constantly improve the ways in which maritime information is collected. With the recent release of free Sentinel-1 imagery to the public, monitoring the maritime environment has become a more affordable. Using the basis of a cell-averaging constant false alarm rate prescreening method as input, this paper presents a novel method for detecting ships...
Synthetic Aperture Radar images are able to detect ships that would be hidden to tradition ship tracking methods due to their transponders being turned off. Using a SAR image as input, the CFAR method can highlight these ships given a correctly chosen threshold value. Typically, the threshold value is chosen as a single floating value for all positions creating a flat threshold plane. This study introduces...
Synthetic Aperture Radar images is a proven technology that can be used to detect ships at sea which have no active transponders (commonly referred to as dark targets). Various methods have been proposed that process SAR images to monitor these targets. In this paper, we propose a novel ship detection method for Advanced Synthetic Aperture Radar imagery that combines a Constant False Alarm Rate ship...
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