Paris W. Vachon

Validation of ship detection by the RADARSAT synthetic aperture radar and the ocean monitoring workstation

RÉSUMÉ La capacité combinée du radar à synthèse douverture (RSO) de RADARSAT et de la station de travail de surveillance des océans (OMW de langlais Ocean Monitoring Workstation) pour la détection automatique des navires a été évaluée par une validation in situ lors des campagnes de terrain de 1996 et 1997. Notre analyse des données de validation disponibles montre un taux de détection de 97% pour les données à faisceau simple qui sont le plus utile pour la détection des navires (les faisceaux ayant un grand angle dincidence) et un taux de détection global de 84%. Le taux défausses détections est toutefois difficile à expliquer à cause des limites des données de validation. On ne peut non plus évaluer la dépendance du taux de détection avec la vitesse du vent. Les navires détectés ont tendance à être de grande dimension (120 m de longueur en moyenne). Nos résultats indiquent que la performance du système de détection automatique utilisant la combinaison RADARSAT et OMW est fiable.

Airborne SAR observations of ocean surface waves penetrating floating ice

The results are presented for a new and improved procedure for estimating the synthetic-aperture radar (SAR) image spectrum of ocean waves. This procedure, the spectral-sum method, involves summing individual image spectra derived from each of the looks of a multilook set. An automatic registration of the per-look spectral information is achieved, accounting for subimage look misregistration due to the wave propagation between looks. Spectral-sum processing is compared with traditional look-sum processing as a function of the radar slant-range. Spectral-sum processing is applied to SAR imagery of waves penetrating the marginal ice zone. >

Operational ship detection in Canada using RADARSAT

The Polar Epsilon (PE) project has implemented operational ship detection using RADARSAT-2 (R-2) data by constructing new receiving stations and a central data processing facility. R-2 imagery is exploited for ship detection using the OceanSuite tool to generate ship detection reports, usually within ten minutes of data downlink. Two new R-2 ScanSAR modes have been implemented for maritime surveillance, offering improved ship detection over wide swaths. Association of SAR ship detections with Automatic Identification System (AIS) ship reports is being trialed within the PE ground system to aid in the identification of “dark” (i.e., non-emitting) targets. The Polar Epsilon 2 (PE2) project will implement operational ship detection using the RADARSAT Constellation Mission (RCM); RCM will include both SAR and AIS payloads with concurrent collection.

Dual Polarization Detection of Ships and Icebergs - Recent Results with ENVISAT ASAR and Data Simulations of RADARSAT-2

The RADARSAT-2 satellite is an advanced C-band synthetic aperture radar (SAR) with a variety of new modes including options for polarization combinations, resolution, and swath width. This paper examines the potential of multi polarization data for detecting and discriminating ship and iceberg targets Data used in this study consist of well validated airborne Convair-580 SAR and spaceborne ASAR HH/HV and HH/VV. In total, the data set used for evaluating detection and discrimination consists of 901 validated iceberg and ship targets. Optimizing target detection is accomplished using receiver operator curves (ROC) as proposed by [6] and discrimination is conducted using a quadratic discriminant (QD) with feature selection based on sequential forward selection (SFS). In general it was found that detection and discrimination improve with more polarimetric information; however, HH/HV and VV/VH only had nominally less discrimination performance than the quad polarization modes evaluated.

RCM Polarimetric SAR for Enhanced Ship Detection and Classification

Abstract. The RADARSAT Constellation Mission (RCM), which involves three small synthetic aperture radar (SAR) satellites flying in a constellation configuration, will be equipped with fully polarimetric (FP) capabilities in addition to single-polarization (HH, HV, VV), conventional (HH-HV, VV-VH, and HH-VV), and hybrid (i.e., compact) dual polarization. In this article, the added value of polarimetric SAR information for enhanced ship detection is demonstrated using polarimetric RADARSAT-2 (RS2) data collected over vessels (validated with Automatic Identification System (AIS) data) in the Strait of Georgia, near Vancouver, Canada. It is shown that the excursion (Δp) of the degree of polarization (DoP) provides a significant increase in ship–sea contrast in comparison with conventional (i.e., scalar) single-channel polarizations (HH, HV, VV) and compact. Δp, which is a measure of the variation of the DoP with transmit antenna polarization, performs better than compact intensities and degree of depolarization (DoD) promoted recently for ship detection. The unique potential of FP for ship classification is also demonstrated using polarimetric Convair-580 SAR data collected off Cape Race, Newfoundland, Canada. An efficient combination of successive wide-swath ScanSAR and FP, which exploits the RCM rapid-revisit capability at high latitudes, is considered for operational ship detection and classification. Résumé. La mission de la Constellation RADARSAT (MCR), qui est constituée de trois petits satellites SAR évoluant en configuration de constellation, sera équipée avec des capacités de polarisation en quadrature (FP) en plus de la polarisation simple (HH, HV, VV), de la polarisation classique (HH-HV, VV-VH, et HH-VV) et de la bipolarisation hybride (c.-à-d., compacte). Dans cet article, la valeur ajoutée des informations polarimétriques SAR pour améliorer la détection de navires est démontrée en utilisant des données polarimétriques RADARSAT-2 (RS2) recueillies sur des navires (validées avec le système didentification automatique (AIS) de données) dans le détroit de Georgia, près de Vancouver (Canada). Il apparait que la différence (delta p) du degré de polarisation (DOP) fournit une augmentation significative du contraste entre le navire et leau par rapport à des polarisations simples classiques (p.ex., scalaire) (HH, HV, VV) et compactes. Le delta p, qui est une mesure de la variation de la polarisation DoP avec lantenne démission, est plus performant que les intensités compactes et le degré de dépolarisation (DoD) promus récemment pour la détection de navires. Le potentiel unique de la FP pour la classification de navires est également démontré en utilisant les données polarimétriques Convair-580 SAR recueillies au large du cap Race à Terre-Neuve (Canada). Une combinaison efficace de la large fauchée ScanSAR consécutive à la FP, qui exploite la capacité de revisite rapide de la MCR dans les hautes latitudes, est considérée pour la détection et la classification opérationnelles de navires.

Automated Discrimination of Certain Brightness Fronts in RADARSAT-2 Images of the Ocean Surface

AbstractAutomated classification of the signatures of atmospheric and oceanic processes in synthetic aperture radar (SAR) images of the ocean surface has been a difficult problem, partly because different processes can produce signatures that are very similar in appearance. For example, brightness fronts that are the signatures of horizontal wind shear caused by atmospheric processes that occur independently of properties of the ocean (WIN herein) often appear very similar to brightness fronts that are signatures of sea surface temperature (SST) fronts (SST herein). Using Moderate Resolution Imaging Spectroradiometer (MODIS)-derived SST for validation, 302 SAR SST and 193 SAR WIN signatures were collected from over 250 RADARSAT-2 images of the Gulf Stream region using a Canny edge detector. A vector consisting of textural and contextual features was extracted from each signature and used to train and test logistic regression, maximum likelihood, and binary tree classifiers. Following methods proven effect...

Oil detection in RADARSAT-2 quad-polarization imagery: implications for ScanSAR performance

Environment Canadas Integrated Satellite Tracking of Pollution (ISTOP) program uses RADARSAT-2 data to vector pollution surveillance assets to areas where oil discharges/spills are suspected in support of enforcement and/or cleanup efforts. RADARSAT-2s new imaging capabilities and ground system promises significant improvements in ISTOPs ability to detect and report on oil pollution. Of specific interest is the potential of dual polarization ScanSAR data acquired with VV polarization to improve the detection of oil pollution compared to data acquired with HH polarization, and with VH polarization to concurrently detect ship targets. A series of 101 RADARSAT-2 fine quad images were acquired over Coal Oil Point, near Santa Barbara, California where a seep field naturally releases hydrocarbons. The oil and gas releases in this region are visible on the sea surface and have been well documented allowing for the remote sensing of a constant source of oil at a fixed location. Although the make-up of the oil seep field could be different from that of oil spills, it provides a representative target that can be routinely imaged under a variety of wind conditions. Results derived from the fine quad imagery with a lower noise floor were adjusted to mimic the noise floor limitations of ScanSAR. In this study it was found that VV performed better than HH for oil detection, especially at higher incidence angles.

Ocean Feature Analysis Using Automated Detection and Classification of Sea-Surface Temperature Front Signatures in RADARSAT-2 Images

The Royal Canadian Navy produces a semiweekly map of major water mass boundaries in the Western North Atlantic using temperature measurements from several data sources, including satellite sea surface temperature (SST) images from the Advanced Very High Resolution Radiometer (AVHRR). Temporal–spatial detail that can be provided by AVHRR of the location of important SST boundaries such as the Gulf Stream North Wall is limited due to pervasive cloud cover. The ability of satellite-borne synthetic aperture radar (SAR) to image SST front signatures unrestrained by cloud cover makes it a potentially significant additional data source. The Spaceborne Ocean Intelligence Network project has developed an automated procedure to detect candidate SST front signatures in RADARSAT-2 SAR images of the ocean surface and classify them with greater than 80% accuracy.

Airborne SAR observations of mesoscale ocean features

RESUMELe present article donne un apercu des donnees et des resultats obtenus avec le radar aeroporte a antenne synthetique (RAS), en bande C, du Centre canadien de teledetection, lors dune mission effectuee en juin 1990, au large de la cote ouest de lile de Vancouver, en Colombie-Britannique. Le navire scientifique “CSS Parizeau” a egalement pris part a cette mission dont lobjectif principal etait dobserver des caracteristiques oceanographiques a lechelle intermediaire (de 10 a 100 km) a laide dune serie chronologique de donnees-images RAS. La serie chronologique etait destinee a echantillonner des systemes meteorologiques des images RAS produites par les phenomenes atmospheriques de celles produites par les phenomenes oceanographiques. Les caracteristiques relatives aux courants marins observees sur les images RAS alors que les vents etaient legers (moins de 5 m/s) ont ete validees a laide des observations tirees du programme oceanogrpahique sur le terrain.

The Utility of Sentinel-1 Data for Ocean Surface Feature Analysis in the Vicinity of the Gulf Stream

ABSTRACT European Space Agency Sentinel-1 (S1) synthetic aperture radar (SAR) datasets are used to assess their suitability for ocean surface feature extraction in the vicinity of the Gulf Stream. A SAR ocean feature detection tool originally developed to extract and classify brightness fronts in RADARSAT-2 (R2) SAR imagery has been updated to extract and classify brightness fronts from S1 ground range-detected products. Results indicate that the features extracted from S1 datasets are largely consistent with those derived from R2. However, more features are extracted from S1 data and, in limited examples, there are differences in how features are classified. In addition, S1 radial velocity (RVL) products were compared with simulated RVL products created from modeled ocean current data. This comparison shows that the orientation and magnitude of the Gulf Stream in S1 RVL products is generally consistent with modeled results, but does indicate that some regions of the Gulf Stream (meanders and ocean eddies) are likely to present challenges for automatic extraction algorithms. Taken together, this research shows that S1 data have utility for ocean surface feature extraction and provide an additional dataset that can be exploited to expand ocean feature analysis over Canadian waters.