Oil spill and ship detection using high resolution polarimetric X-band SAR data

Among illegal human activities, marine pollution and target detection are the key concern of Maritime Security and Safety. This thesis deals with oil spill and ship detection using high resolution X-band polarimetric SAR (PolSAR). Polarimetry aims at analysing the polarization state of a wave field, in order to obtain physical information from the observed object. In this dissertation PolSAR techniques are suggested as improvement of the current State-of-the-Art of SAR marine pollution and target detection, by examining in depth Near Real Time suitability

Estado da Arte do Sensoriamento Remoto de Radar: Fundamentos, Sensores, Processamento de Imagens e Aplicações.

Este artigo aborda o estado da arte do sensoriamento remoto por radar e foi elaborado para fazer parte da edição especial de comemoração dos 50 anos desta revista. Neste estudo, é apresentada uma breve introdução sobre os fundamentos do sensoriamento remoto por radar, com destaque para os parâmetros mais importantes de imageamento e da superfície terrestre envolvidos no processo de obtenção de imagens de radar. Ênfase é dada para o comprimento de onda, polarização das ondas eletromagnéticas e geometria de obtenção de imagens (parâmetros de imageamento) e para a umidade de solos e da vegetação, rugosidade do terreno e estrutura da vegetação (parâmetros da superfície terrestre). Em seguida, são apresentados os principais sensores orbitais de radar de abertura sintética que estão atualmente em operação e os principais processamentos digitais de imagens de radar, destacando-se a conversão dos valores digitais para coeficientes de retroespalhamento, os filtros espaciais para redução do ruído speckle, as técnicas de decomposição de imagens e o processamento InSAR. Finalmente, é apresentada uma breve discussão sobre algumas aplicações potenciais, com especial atenção para o monitoramento de derrame de óleo em plataformas continentais, estimativa de biomassa aérea, monitoramento de desmatamento em coberturas florestais tropicais, detecção de áreas de plantio de arroz irrigado e estimativa de umidade de solos

Meteo-Marine Parameters from Sentinel-1 SAR Imagery: Towards Near Real-Time Services for the Baltic Sea

A method for estimating meteo-marine parameters from satellite Synthetic Aperture Radar (SAR) data, intended for near-real-time (NRT) service over the Baltic Sea, is presented and validated. Total significant wave height data are retrieved with an empirical function CWAVE_S1-IW, which combines spectral analysis of Sentinel-1A/B Interferometric Wide swath (IW) subscenes with wind data derived with common C-Band Geophysical Model Functions (GMFs). In total, 15 Sentinel-1A/B scenes (116 acquisitions) over the Baltic Sea were processed for comparison with off-shore sea state measurements (52 collocations) and coastal wind measurements (357 colocations). Sentinel-1 wave height was spatially compared with WAM wave model results (Copernicus Marine Environment Monitoring Service (CMEMS). The comparison of SAR-derived wave heights shows good agreement with measured wave heights correlation r of 0.88 and with WAM model (r = 0.85). The wind speed estimated from SAR images yields good agreement with in situ data (r = 0.91). The study demonstrates that the wave retrievals from Sentinel-1 IW data provide valuable information for operational and statistical monitoring of wave conditions in the Baltic Sea. The data is valuable for model validation and interpretation in regions where, and during periods when, in situ measurements are missing. The Sentinel-1 A/B wave retrievals provide more detailed information about spatial variability of the wave field in the coastal zone compared to in situ measurements, altimetry wave products and model forecast. Thus, SAR data enables estimation of storm locations and areal coverage. Methods shown in the study are implemented in NRT service in German Aerospace Center’s (DLR) ground station Neustrelitz

Europe's Space capabilities for the benefit of the Arctic

In recent years, the Arctic region has acquired an increasing environmental, social, economic and strategic importance. The Arctic’s fragile environment is both a direct and key indicator of the climate change and requires specific mitigation and adaptation actions. The EU has a clear strategic interest in playing a key role and is actively responding to the impacts of climate change safeguarding the Arctic’s fragile ecosystem, ensuring a sustainable development, particularly in the European part of the Arctic. The European Commission’s Joint Research Centre has recently completed a study aimed at identifying the capabilities and relevant synergies across the four domains of the EU Space Programme: earth observation, satellite navigation, satellite communications, and space situational awareness (SSA). These synergies are expected to be key enablers of new services that will have a high societal impact in the region, which could be developed in a more cost-efficient and rapid manner. Similarly, synergies will also help exploit to its full extent operational services that are already deployed in the Arctic (e.g., the Copernicus emergency service or the Galileo Search and rescue service could greatly benefit from improved satellite communications connectivity in the region).JRC.E.2-Technology Innovation in Securit

Efficient SAR MTI simulator of marine scenes

Tècniques de detecció de moviment amb radars d'apertura sintètica multicanals sobre escenaris marítims.[ANGLÈS] Multichannel spaceborne and airborne synthetic aperture radars (SAR) offer the opportunity to monitor maritime traffic through specially designed instruments and applying a suitable signal processing in order to reject sea surface clutter. These processing techniques are known as Moving Target Indication techniques (MTI) and the choice of the most adequate method depends on the radar system and operating environment. In maritime scenes the seas presents a complicated clutter whose temporal/spatial coherence models and background reflectivity depends on a large number of factors and are still subject of research. Moreover the targets kinematics are influenced by the sea conditions, producing in some situations high alterations in the imaged target. These aspects make difficult the detectability analysis of vessels in maritime scenarios, requiring both theoretical models and numerical simulations. This thesis looks into the few available MTI techniques and deals experimentally with them in a developed simulator for maritime SAR images. The results are also presented in a image format, giving the sequence for one trial simulation and the asymptotic probability of detection for the simulated conditions.[CASTELLÀ] Los radares de apertura sintética (SAR) multicanal a bordo de satélites o plataformas aerotransportadas ofrecen la oportunidad de monitorizar el tráfico marítimo a través de instrumentos especialmente diseñados y procesando los datos recibidos de forma adecuada para rechazar la señal provocada por la reflexión del mar. A estas técnicas se las conoce como Moving Target Indication techniques (MTI) y la elección de la más adecuada depende del sistema y del entorno de aplicación. En escenarios marinos, el mar presenta un clutter complicado de modelar, cuya coherencia espacio-temporal y reflectividad radar dependen de un gran número de factores que hoy en día todavía siguen siendo investigados. Por otra parte los parámetros dinámicos del target estan influenciados por las condiciones del mar, produciendo en algunas situaciones graves alteraciones en la formación de la imagen. Estos aspectos dificultan el análisis de la detección de las embarcaciones, requiriendo modelos teóricos y simulaciones numéricas. Este Proyecto Final de Carrera investiga las técnicas MTI disponibles, aplicándolas sobre las imágenes marítimas generadas por un simulador SAR. Los resultados son la generación de los productos MTI en formato imagen y el cálculo de la probabilidad de detección para cada target.[CATALÀ] Els radars d'obertura sintètica (SAR) multicanal embarcats en satèl·lits o plataformes aerotransportades ofereixen l'oportunitat de monitoritzar el tràfic marítim a través d'instruments especialment dissenyats i processant les dades rebudes de forma adequada per rebutjar la senyal provocada per la reflexió del mar. A aquestes tècniques se les coneix com Moving Target indication techniques (MTI) i l'elecció de la més adequada depèn del sistema i de l'entorn d'aplicació. En escenaris marins, el mar presenta un clutter complicat de modelar, la coherència espai-temporal i reflectivitat radar depenen d'un gran nombre de factors que avui dia encara segueixen sent investigats. D'altra banda els paràmetres dinàmics del target estan influenciats per les condicions de la mar, produint en algunes situacions greus alteracions en la formació de la imatge. Aquests aspectes dificulten l'anàlisi de la detecció de les embarcacions, requerint models teòrics i simulacions numèriques. Aquest Projecte Final de Carrera investiga les tècniques MTI disponibles, aplicant-les sobre les imatges marítimes generades per un simulador SAR. Els resultats són la generació dels productes MTI en format imatge i el càlcul de la probabilitat asimptòtica de detecció per a cada target

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

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

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

Offshore oil spill detection using synthetic aperture radar

Among the different types of marine pollution, oil spill has been considered as a major threat to the sea ecosystems. The source of the oil pollution can be located on the mainland or directly at sea. The sources of oil pollution at sea are discharges coming from ships, offshore platforms or natural seepage from sea bed. Oil pollution from sea-based sources can be accidental or deliberate. Different sensors to detect and monitor oil spills could be onboard vessels, aircraft, or satellites. Vessels equipped with specialised radars, can detect oil at sea but they can cover a very limited area. One of the established ways to monitor sea-based oil pollution is the use of satellites equipped with Synthetic Aperture Radar (SAR).The aim of the work presented in this thesis is to identify optimum set of feature extracted parameters and implement methods at various stages for oil spill detection from Synthetic Aperture Radar (SAR) imagery. More than 200 images of ERS-2, ENVSAT and RADARSAT 2 SAR sensor have been used to assess proposed feature vector for oil spill detection methodology, which involves three stages: segmentation for dark spot detection, feature extraction and classification of feature vector. Unfortunately oil spill is not only the phenomenon that can create a dark spot in SAR imagery. There are several others meteorological and oceanographic and wind induced phenomena which may lead to a dark spot in SAR imagery. Therefore, these dark objects also appear similar to the dark spot due to oil spill and are called as look-alikes. These look-alikes thus cause difficulty in detecting oil spill spots as their primary characteristic similar to oil spill spots. To get over this difficulty, feature extraction becomes important; a stage which may involve selection of appropriate feature extraction parameters. The main objective of this dissertation is to identify the optimum feature vector in order to segregate oil spill and ‘look-alike’ spots. A total of 44 Feature extracted parameters have been studied. For segmentation, four methods; based on edge detection, adaptive theresholding, artificial neural network (ANN) segmentation and the other on contrast split segmentation have been implemented. Spot features are extracted from both the dark spots themselves and their surroundings. Classification stage was performed using two different classification techniques, first one is based on ANN and the other based on a two-stage processing that combines classification tree analysis and fuzzy logic. A modified feature vector, including both new and improved features, is suggested for better description of different types of dark spots. An ANN classifier using full spectrum of feature parameters has also been developed and evaluated. The implemented methodology appears promising in detecting dark spots and discriminating oil spills from look-alikes and processing time is well below any operational service requirements

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