138 research outputs found

    JRC - SAR Satellite Small Boat Detection Campaign – Portoroz - Slovenia

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    The European maritime area is one of Europe’s most important assets with regard to resources, security and ultimately prosperity of the Member States. A significant part of Europe’s economy relies directly or indirectly on it. It is not just the shipping or fisheries industries and their related activities. It is also shipbuilding and ports, marine equipment and offshore energy, maritime and coastal tourism, aquaculture, submarine telecommunications, blue biotech and the protection of the marine environment. The European maritime area faces several risks and threats posed by unlawful activities, such as drugs trafficking, smuggling, illegal immigration, organised crime and terrorism. Piracy in international waters also constitutes a threat to Europe since it can disrupt the maritime transport chain. These risks and threats can endanger human lives, marine resources and the environment, as well as significantly disrupt the transport chain and global and local security. It is anticipated that these risks and threats will endure in the mid and long run. In order to keep Europe as a world leader in the global maritime economy, an effective integrated/interoperable, sustainable maritime surveillance system and situational awareness are needed. A significant number of unlawful maritime activities, such as illegal immigration, drugs trafficking, smuggling, piracy and terrorism involve mainly small boats, because small boats are faster and more difficult to detect using conventional means. Hence, it is very important to find out the feasibility of using SAR Satellite images for small boat detection. Since 2008 the EC-JRC has carried out a number of SAR Small Boat detection experiments to assess the feasibility of using Spaceborne SAR for Small Boat detection. This report presents the results and conclusions of the Spaceborne SAR Small Boat detection campaign carried out by the EC-JRC on open sea in Portoroz – Slovenia in May and June 2010.JRC.G.4-Maritime affair

    JRC - Metasensing Coupled Spaceborne & Airborne SAR Campaign in Rotterdam

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    The European maritime area is one of Europe’s most important assets with regard to resources, security and ultimately prosperity of the Member States. A significant part of Europe’s economy relies directly or indirectly on it. It is not just the shipping or fisheries industries and their related activities. It is also shipbuilding and ports, marine equipment and offshore energy, maritime and coastal tourism, aquaculture, submarine telecommunications, blue biotech and the protection of the marine environment. The European maritime area faces several risks and threats posed by unlawful activities, such as drugs trafficking, smuggling, illegal immigration, organised crime and terrorism. Piracy in international waters also constitutes a threat to Europe since it can disrupt the maritime transport chain. These risks and threats can endanger human lives, marine resources and the environment, as well as significantly disrupt the transport chain and global and local security. It is anticipated that these risks and threats will endure in the mid and long run. In order to keep Europe as a world leader in the global maritime economy, an effective integrated/interoperable, sustainable maritime surveillance system and situational awareness are needed. A significant number of unlawful maritime activities, such as illegal immigration, drugs trafficking, smuggling, piracy and terrorism involve mainly small boats, because small boats are faster and more difficult to detect using conventional means. Hence, it is very important to find out the feasibility of using new sensors and platforms, such as SAR or Unmanned Aerial Systems (UAS) for small boat detection, tracking, classification and identification, as well as to study the potential of airborne SAR for maritime surveillance. Since 2010 the EC-JRC has carried out a number of coupled UAS and spaceborne SAR maritime surveillance campaigns to assess the potential of UAS for maritime surveillance, in particular for small boat detection. This report presents the results and conclusions of the JRC – Metasensing Coupled Spaceborne SAR and Airborne SAR campaign carried out in Feb. 2011 in Rotterdam, The Netherlands.JRC.G.4-Maritime affair

    JRC - Alenia Aeronautica Coupled UAS and Spaceborne SAR Campaign in Italy

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    The European maritime area is one of Europe’s most important assets with regard to resources, security and ultimately prosperity of the Member States. A significant part of Europe’s economy relies directly or indirectly on it. It is not just the shipping or fisheries industries and their related activities. It is also shipbuilding and ports, marine equipment and offshore energy, maritime and coastal tourism, aquaculture, submarine telecommunications, blue biotech and the protection of the marine environment. The European maritime area faces several risks and threats posed by unlawful activities, such as drugs trafficking, smuggling, illegal immigration, organised crime and terrorism. Piracy in international waters also constitutes a threat to Europe since it can disrupt the maritime transport chain. These risks and threats can endanger human lives, marine resources and the environment, as well as significantly disrupt the transport chain and global and local security. It is anticipated that these risks and threats will endure in the mid and long run. In order to keep Europe as a world leader in the global maritime economy, an effective integrated/interoperable, sustainable maritime surveillance system and situational awareness are needed. A significant number of unlawful maritime activities, such as illegal immigration, drugs trafficking, smuggling, piracy and terrorism involve mainly small boats, because small boats are faster and more difficult to detect using conventional means. Hence, it is very important to find out the feasibility of using Unmanned Aerial Systems (UAS) for small boat detection, tracking, classification and identification, as well as to study the potential of UAS for maritime surveillance. Since 2010 the EC-JRC has carried out a number of UAS maritime surveillance campaigns to study the potential of UAS for maritime surveillance, in particular for small boat detection. This report presents the results and conclusions of the JRC - Alenia Aeronautica Coupled UAS and Spaceborne SAR campaign carried out in Oct. 2010 in Porto Corallo, Sardinia, Italy.JRC.G.4-Maritime affair

    Deformations of Highway over Undermined Ostrava-Svinov Area Monitored by InSAR Using Limited Set of SAR Images

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    AbstractPart of Czech highway D1 connecting Ostrava city with Prague and Poland, is built over an undermined area of Ostrava-Svinov, with mines closed since 1991 in the area. Soon after its opening ceremony in 2008, the highway began to exhibit various significant deformations. An attempt of InSAR monitoring using ERS, Envisat and several TerraSAR-X Spotlight acquisitions was done in order to monitor progress of deformations, to consider suitability of satellite InSAR for such purposes and to search for footprints whether the deformations were caused by fading subsidence due to undermining or by another, local, reason. Only shallow subsidence was found in the area from Envisat data ranging 2005-2010. Highway deformations in late 2011 are observable from processing of limited set of 5 TerraSAR-X images using different methods. Detected deformations are very probably due to longitudinal thermal expansion of the observed highway bridge. This publication contains issues to be taken into consideration for appropriate interpretation and processing if the available input dataset is limited and not optimal

    Effective SAR image despeckling based on bandlet and SRAD

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    Despeckling of a SAR image without losing features of the image is a daring task as it is intrinsically affected by multiplicative noise called speckle. This thesis proposes a novel technique to efficiently despeckle SAR images. Using an SRAD filter, a Bandlet transform based filter and a Guided filter, the speckle noise in SAR images is removed without losing the features in it. Here a SAR image input is given parallel to both SRAD and Bandlet transform based filters. The SRAD filter despeckles the SAR image and the despeckled output image is used as a reference image for the guided filter. In the Bandlet transform based despeckling scheme, the input SAR image is first decomposed using the bandlet transform. Then the coefficients obtained are thresholded using a soft thresholding rule. All coefficients other than the low-frequency ones are so adjusted. The generalized cross-validation (GCV) technique is employed here to find the most favorable threshold for each subband. The bandlet transform is able to extract edges and fine features in the image because it finds the direction where the function gives maximum value and in the same direction it builds extended orthogonal vectors. Simple soft thresholding using an optimum threshold despeckles the input SAR image. The guided filter with the help of a reference image removes the remaining speckle from the bandlet transform output. In terms of numerical and visual quality, the proposed filtering scheme surpasses the available despeckling schemes

    SAR image classification with non-stationary multinomial logistic mixture of amplitude and texture densities

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    We combine both amplitude and texture statistics of the Synthetic Aperture Radar (SAR) images using Products of Experts (PoE) approach for classification purpose. We use Nakagami density to model the class amplitudes. To model the textures of the classes, we exploit a non-Gaussian Markov Random Field (MRF) texture model with t-distributed regression error. Non-stationary Multinomial Logistic (MnL) latent class label model is used as a mixture density to obtain spatially smooth class segments. We perform the Classification Expectation-Maximization (CEM) algorithm to estimate the class parameters and classify the pixels. We obtained some classification results of water, land and urban areas in both supervised and semi-supervised cases on TerraSAR-X data

    Classification accuracy increase using multisensor data fusion

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    The practical use of very high resolution visible and near-infrared (VNIR) data is still growing (IKONOS, Quickbird, GeoEye-1, etc.) but for classification purposes the number of bands is limited in comparison to full spectral imaging. These limitations may lead to the confusion of materials such as different roofs, pavements, roads, etc. and therefore may provide wrong interpretation and use of classification products. Employment of hyperspectral data is another solution, but their low spatial resolution (comparing to multispectral data) restrict their usage for many applications. Another improvement can be achieved by fusion approaches of multisensory data since this may increase the quality of scene classification. Integration of Synthetic Aperture Radar (SAR) and optical data is widely performed for automatic classification, interpretation, and change detection. In this paper we present an approach for very high resolution SAR and multispectral data fusion for automatic classification in urban areas. Single polarization TerraSAR-X (SpotLight mode) and multispectral data are integrated using the INFOFUSE framework, consisting of feature extraction (information fission), unsupervised clustering (data representation on a finite domain and dimensionality reduction), and data aggregation (Bayesian or neural network). This framework allows a relevant way of multisource data combination following consensus theory. The classification is not influenced by the limitations of dimensionality, and the calculation complexity primarily depends on the step of dimensionality reduction. Fusion of single polarization TerraSAR-X, WorldView-2 (VNIR or full set), and Digital Surface Model (DSM) data allow for different types of urban objects to be classified into predefined classes of interest with increased accuracy. The comparison to classification results of WorldView-2 multispectral data (8 spectral bands) is provided and the numerical evaluation of the method in comparison to other established methods illustrates the advantage in the classification accuracy for many classes such as buildings, low vegetation, sport objects, forest, roads, rail roads, etc

    The TerraSAR-X Mission and System Design

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    This paper describes the TerraSAR-X Mission Concept within the context of a public-private-partnership (PPP) agreement between the German Aerospace Center DLR and industry. It briefly describes the PPP-concept as well as the overall project organization. The paper then gives an overview of the satellite design, the corresponding Ground Segment as well as the main mission parameters. After a short introduction to the scientific and commercial exploitation scheme, the paper finally focuses on the mission accomplishments achieved so far during the ongoing mission

    An Efficient Polyphase Filter Based Resampling Method for Unifying the PRFs in SAR Data

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    Variable and higher pulse repetition frequencies (PRFs) are increasingly being used to meet the stricter requirements and complexities of current airborne and spaceborne synthetic aperture radar (SAR) systems associated with higher resolution and wider area products. POLYPHASE, the proposed resampling scheme, downsamples and unifies variable PRFs within a single look complex (SLC) SAR acquisition and across a repeat pass sequence of acquisitions down to an effective lower PRF. A sparsity condition of the received SAR data ensures that the uniformly resampled data approximates the spectral properties of a decimated densely sampled version of the received SAR data. While experiments conducted with both synthetically generated and real airborne SAR data show that POLYPHASE retains comparable performance to the state-of-the-art BLUI scheme in image quality, a polyphase filter-based implementation of POLYPHASE offers significant computational savings for arbitrary (not necessarily periodic) input PRF variations, thus allowing fully on-board, in-place, and real-time implementation
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