Space-based Global Maritime Surveillance. Part I: Satellite Technologies

Maritime surveillance (MS) is crucial for search and rescue operations, fishery monitoring, pollution control, law enforcement, migration monitoring, and national security policies. Since the early days of seafaring, MS has been a critical task for providing security in human coexistence. Several generations of sensors providing detailed maritime information have become available for large offshore areas in real time: maritime radar sensors in the 1950s and the automatic identification system (AIS) in the 1990s among them. However, ground-based maritime radars and AIS data do not always provide a comprehensive and seamless coverage of the entire maritime space. Therefore, the exploitation of space-based sensor technologies installed on satellites orbiting around the Earth, such as satellite AIS data, synthetic aperture radar, optical sensors, and global navigation satellite systems reflectometry, becomes crucial for MS and to complement the existing terrestrial technologies. In the first part of this work, we provide an overview of the main available space-based sensors technologies and present the advantages and limitations of each technology in the scope of MS. The second part, related to artificial intelligence, signal processing and data fusion techniques, is provided in a companion paper, titled: "Space-based Global Maritime Surveillance. Part II: Artificial Intelligence and Data Fusion Techniques" [1].Comment: This paper has been submitted to IEEE Aerospace and Electronic Systems Magazin

Detection and classification of sea ice from spaceborne multi-frequency synthetic aperture radar imagery and radar altimetry

The sea ice cover in the Arctic is undergoing drastic changes. Since the start of satellite observations by microwave remote sensing in the late 1970\u27s, the maximum summer sea ice extent has been decreasing and thereby causing a generally thinner and younger sea ice cover. Spaceborne radar remote sensing facilitates the determination of sea ice properties in a changing climate with the high spatio-temporal resolution necessary for a better understanding of the ongoing processes as well as safe navigation and operation in ice infested waters.The work presented in this thesis focuses on the one hand on synergies of multi-frequency spaceborne synthetic aperture radar (SAR) imagery for sea ice classification. On the other hand, the fusion of radar altimetry observations with near-coincidental SAR imagery is investigated for its potential to improve 3-dimensional sea ice information retrieval.Investigations of ice/water classification of C- and L-band SAR imagery with a feed-forward neural network demonstrated the capabilities of both frequencies to outline the sea ice edge with good accuracy. Classification results also indicate that a combination of both frequencies can improve the identification of thin ice areas within the ice pack compared to C-band alone. Incidence angle normalisation has proven to increase class separability of different ice types. Analysis of incidence angle dependence between 19-47\ub0 at co- and cross-polarisation from Sentinel-1 C-band images closed a gap in existing slope estimates at cross-polarisation for multiyear sea ice and confirms values obtained in other regions of the Arctic or with different sensors. Furthermore, it demonstrated that insufficient noise correction of the first subswath at cross-polarisation increased the slope estimates by 0.01 dB/1\ub0 for multiyear ice. The incidence angle dependence of the Sentinel-1 noise floor affected smoother first-year sea ice and made the first subswath unusable for reliable incidence angle estimates in those cases.Radar altimetry can complete the 2-dimensional sea ice picture with thickness information. By comparison of SAR imagery with altimeter waveforms from CryoSat-2, it is demonstrated that waveforms respond well to changes of the sea ice surface in the order of a few hundred metres to a few kilometres. Freeboard estimates do however not always correspond to these changes especially when mixtures of different ice types are found within the footprint. Homogeneous ice floes of about 10 km are necessary for robust averaged freeboard estimates. The results demonstrate that multi-frequency and multi-sensor approaches open up for future improvements of sea ice retrievals from radar remote sensing techniques, but access to in-situ data for training and validation will be critical

Ocean Remote Sensing with Synthetic Aperture Radar

The ocean covers approximately 71% of the Earth’s surface, 90% of the biosphere and contains 97% of Earth’s water. The Synthetic Aperture Radar (SAR) can image the ocean surface in all weather conditions and day or night. SAR remote sensing on ocean and coastal monitoring has become a research hotspot in geoscience and remote sensing. This book—Progress in SAR Oceanography—provides an update of the current state of the science on ocean remote sensing with SAR. Overall, the book presents a variety of marine applications, such as, oceanic surface and internal waves, wind, bathymetry, oil spill, coastline and intertidal zone classification, ship and other man-made objects’ detection, as well as remotely sensed data assimilation. The book is aimed at a wide audience, ranging from graduate students, university teachers and working scientists to policy makers and managers. Efforts have been made to highlight general principles as well as the state-of-the-art technologies in the field of SAR Oceanography

Quad polarimetric synthetic aperture radar analysis of icebergs in Greenland and Svalbard

Polarimetric synthetic aperture radar (PolSAR) has been widely used in ocean and cryospheric applications. This is because, PolSAR can be used in all-day operations and in areas of cloud cover, and therefore can provide valuable large-scale monitoring in polar regions, which is very helpful to shipping and offshore maritime operations. In the last decades, attention has turned to the potential of PolSAR to detect icebergs in the Arctic since they are a major hazard to vessels. However, there is a substantial lack of literature exploring the potentialities of PolSAR and the understanding of iceberg scattering mechanisms. Additionally, it is not known if high resolution PolSAR can be used to detect icebergs smaller than 120 metres. This thesis aims to improve the knowledge of the use of PolSAR scattering mechanisms of icebergs, and detection of small icebergs. First, an introduction to PolSAR is outlined in chapter two, and monitoring of icebergs is presented in chapter three. The first data chapter (Chapter 4) is focused on developing a multi-scale analysis of icebergs using parameters from the Cloude-Pottier and the Yamaguchi decompositions, the polarimetric span and the Pauli scattering vector. This method is carried out using ALOS-2 PALSAR quad polarimetric L-band SAR on icebergs in Greenland. This approach outlines the good potential for using PolSAR for future iceberg classification. One of the main important outcomes is that icebergs are composed by a combination of single targets, which therefore may require a more complex way of processing SAR data to properly extract physical information. In chapter five, the problem of detecting icebergs is addressed by introducing six state-of-the-art detectors previously applied to vessel monitoring. These detectors are the Dual Intensity Polarisation Ratio Anomaly Detector (iDPolRAD), Polarimetric Notch Filter (PNF), Polarimetric Matched Filter (PMF), reflection symmetry (sym), Optimal Polarimetric Detector (OPD) and the Polarimetric Whitening Filter (PWF). Cloude-Pottier entropy, and first and third eigenvalues (eig1 and eig3) of the coherency matrix are also utilised as parameters for comparison. This approach uses the same ALOS-2 dataset, but also evaluates detection performance in two scenarios: icebergs in open ocean, and in sea ice. Polarimetric modes (quad-pol, dual-pol, and single intensities) are also considered for comparison. Currently it is very difficult to detect icebergs less than 120 metres in length using this approach, due to the scattering mechanisms of icebergs and sea ice being very similar. However, it was possible to obtain detection performances of the OPD and PWF, which both showed a Probability of Detection (PF) of 0.99 when the Probability of False Alarms (PF) was set to 10-5 in open ocean. Similarly, in dual pol images, the PWF gave the best performance with a PD of 0.90. Results in sea ice found eig3 to be the best detector with a PD of 0.90 while in dual-pol mode, iDPolRAD gave a PD of 0.978. Single intensity detector performance found the HV channel gave the best detection with a PD of 0.99 in open ocean and 0.87 in sea ice. In the previous two approaches, only satellite data is used. However, in chapter six, data from a ground-based Ku-band Gamma Portable Radio Interferometer (GPRI) instrument is introduced, providing images that are synchronised with the satellite acquisitions. In this approach, the same six detectors are applied to three multitemporal RADARSAT-2 quad pol C-band SAR images on icebergs in Kongsfjorden, Svalbard to evaluate the detection performance within a changing fjord environment. As before, we also make use of Cloude-Pottier entropy, eig1 and eig3. Finally, we evaluate the target-to-clutter ratio (TCR) of the icebergs and check for correlation between the backscattering coefficients and the iceberg dimension. The results obtained from this thesis present original additions to the literature that contributes to the understanding of PolSAR in cryospheric applications. Although these methods are applied to PolSAR and ground-based radar on vessels, they have been applied for the first time on icebergs in this thesis. To summarise, the main findings are that icebergs cannot be represented as single or partial targets, but they do exhibit a collection of single targets clustered together. This result leads to the fact that entropy is not sufficient as a parameter to detect icebergs. Detection results show that the OPD and PWF detectors perform best in an open ocean setting and using quad-pol mode. These results are degraded in dual-pol mode, while single intensity detection is best in the HV cross polarisation channel. When these detectors are applied to the RADARSAT-2 in Svalbard, the OPD and PWF detectors also perform best with PD values ranging between 0.5-0.75 for a PF of 0.01-0.05. However, the sea ice present in the fjord degrades performance across all detectors. Correlation plots with iceberg size show that a regression is not straightforward and Computer Vision methodologies may work best for this

Study of the speckle noise effects over the eigen decomposition of polarimetric SAR data: a review

This paper is focused on considering the effects of speckle noise on the eigen decomposition of the co- herency matrix. Based on a perturbation analysis of the matrix, it is possible to obtain an analytical expression for the mean value of the eigenvalues and the eigenvectors, as well as for the Entropy, the Anisotroopy and the dif- ferent a angles. The analytical expressions are compared against simulated polarimetric SAR data, demonstrating the correctness of the different expressions.Peer ReviewedPostprint (published version

A comparative study of operational vessel detectors for maritime surveillance using satellite-borne synthetic aperture radar

This paper presents a comparative study among four operational detectors that work by automatically post-processing synthetic aperture radar (SAR) images acquired from the satellite platforms RADARSAT-2 and COSMO-SkyMed. Challenging maritime scenarios have been chosen to assess the detectors' performance against features such as ambiguities, significant sea clutter, or irregular shorelines. The SAR images which form the test data are complemented with ground truth to define the reference detection configuration, which permits quantifying the probability of detection, the false alarm rate, and the accuracy of estimating ship dimensions. Although the results show that all the detectors perform well, there is no perfect detector, and a better detection system could be developed that combines the best elements from each of the single detectors. In addition to the comparison exercise, the study has facilitated the improvement of the detectors by highlighting weaknesses and providing means for fixing them.Peer ReviewedPostprint (published version

Applications of Satellite Earth Observations section - NEODAAS: Providing satellite data for efficient research

The NERC Earth Observation Data Acquisition and Analysis Service (NEODAAS) provides a central point of Earth Observation (EO) satellite data access and expertise for UK researchers. The service is tailored to individual users’ requirements to ensure that researchers can focus effort on their science, rather than struggling with correct use of unfamiliar satellite data

Polarimetric Synthetic Aperture Radar

This open access book focuses on the practical application of electromagnetic polarimetry principles in Earth remote sensing with an educational purpose. In the last decade, the operations from fully polarimetric synthetic aperture radar such as the Japanese ALOS/PalSAR, the Canadian Radarsat-2 and the German TerraSAR-X and their easy data access for scientific use have developed further the research and data applications at L,C and X band. As a consequence, the wider distribution of polarimetric data sets across the remote sensing community boosted activity and development in polarimetric SAR applications, also in view of future missions. Numerous experiments with real data from spaceborne platforms are shown, with the aim of giving an up-to-date and complete treatment of the unique benefits of fully polarimetric synthetic aperture radar data in five different domains: forest, agriculture, cryosphere, urban and oceans

Satellite monitoring of harmful algal blooms (HABs) to protect the aquaculture industry

Harmful algal blooms (HABs) can cause sudden and considerable losses to fish farms, for example 500,000 salmon during one bloom in Shetland, and also present a threat to human health. Early warning allows the industry to take protective measures. PML's satellite monitoring of HABs is now funded by the Scottish aquaculture industry. The service involves processing EO ocean colour data from NASA and ESA in near-real time, and applying novel techniques for discriminating certain harmful blooms from harmless algae. Within the AQUA-USERS project we are extending this capability to further HAB species within several European countries