953 research outputs found

    Remote sensing of earth terrain

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    Abstracts from 46 refereed journal and conference papers are presented for research on remote sensing of earth terrain. The topics covered related to remote sensing include the following: mathematical models, vegetation cover, sea ice, finite difference theory, electromagnetic waves, polarimetry, neural networks, random media, synthetic aperture radar, electromagnetic bias, and others

    Contributions to GNSS-R earth remote sensing from nano-satellites

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    Premi extraordinari doctorat UPC curs 2015-2016, àmbit de CiènciesGlobal Navigation Satellite Systems Reflectometry (GNSS-R) is a multi-static radar using navigation signals as signals of opportunity. It provides wide-swath and improved spatio-temporal sampling over current space-borne missions. The lack of experimental datasets from space covering signals from multiple constellations (GPS, GLONASS, Galileo, Beidou) at dual-band (L1 and L2) and dual-polarization (Right Hand Left Hand Circular Polarization: RHCP and LHCP), over the ocean, land and cryosphere remains a bottleneck to further develop these techniques. 3Cat-2 is a 6 units (3 x 2 elementary blocks of 10 x 10 x 10 cm3) CubeSat mission ayming to explore fundamentals issues towards an improvement in the understanding of the bistatic scattering properties of different targets. Since geolocalization of specific reflections points is determined by the geometry only, a moderate pointing accuracy is still required to correct for the antena pattern in scatterometry measurements. 3Cat-2 launch is foreseen for the first quarter 2016 into a Sun-Synchronous orbit of 510 km height using a Long March II D rocket. This Ph.D. Thesis represents the main contributions to the development of the 3Cat-2 GNSS-R Earth observation mission (6U CubeSat) including a novel type of GNSS-R technique: the reconstructed one. The desing, development of the platform, and a number of ground-based, airborne and stratospheric balloon experiments to validate the technique and to optimize the instrument. In particular, the main contributions of this Ph.D. thesis are: 1) A novel dual-band Global Navigation Satellite Systems Reflectometer that uses the P(Y) and C/A signals scattered over the sea surface to perform highly precise altimetric measurements (PYCARO). 2) The first proof-of-concept of PYCARO was performed during two different ground-based field experiments over a dam and over the sea under different surface roughness conditions. 3) The scattering of GNSS signals over a water surface has been studied when the receiver is at low height, as for GNSS-R coastal altimetry applications. The precise determination of the local sea level and wave state from the coast can provide useful altimetry and wave information as "dry" tide and wave gauges. In order to test this concept an experiment has been conducted at the Canal d'Investigació i Experimentació Marítima (CIEM) wave channel for two synthetic "sea" states. 4) Two ESA-sponsored airborne experiments were perfomed to test the precision and the relative accuracy of the conventional GNSS-R. 5) The empirical results of a GNSS-R experiment on-board the ESA-sponsored BAXUS 17 stratospheric balloon campaign performed North of Sweden over boreal forests showed that the power of the reflected signals is nearly independent of the platform height for a high coherent integration time. 6) An improved version of the PYCARO payload was tested in Octover 2014 for the second time during the ESA-sposored BEXUS-19,. This work achieved the first ever dual-frequency, multi-constellation GNSS-R observations over boreal forests and lakes using GPS, GLONASS and Galileo signals. 7) The first-ever dual-frequency multi-constellation GNSS-R dual-polarization measurements over boreal forests and lakes were obtained from the stratosphere during the BEXUS 19 using the PYCARO reflectometer operated in closed-loop mode.Global Navigation Satellite Systems Reflectometry (GNSS-R) es una técnica de radar multi-estático que usa señales de radio-navegación como señales de oportunidad. Esta técnica proporciona "wide-swath" y un mejor sampleado espacio-temporal en comparación con las misiones espaciales actuales. La falta de datos desde el espacio proporcionando señales de múltiples constelaciones (GPS, GLONASS, Galileo, Beidou) en doble banda (L1 y L2) y en doble polarización (RHCP y LHCP) sobre océano, tierra y criosfera continua siendo un problema por solucionar. 3Cat-2 es un cubesat de 6 unidades con el objetivo de explorar elementos fundamentales para mejorar el conocimiento sobre el scattering bi-estático sobre diferentes medios dispersores. Dado que la geolocalización de puntos de reflexión específicos está determinada solo por geometría, es necesario un requisito moderado de apuntamiento para corregir el diagrama de antena en aplicaciones de dispersometría. El lanzamiento del 3Cat-2 será en Q2 2016 en una órbitra heliosíncrona usando un cohete Long March II D. Esta tesis representa las contribuciones principales al desarrollo del satélite 3Cat2 para realizar observación de la tierra con GNSS-R incluyendo una nueva técnica: "the reconstructed-code GNSS-R". El diseño, desarrollo de la plataforma y un número de experimentos en tierra, desde avión y desde globo estratosférico para validar la técnica y optimizar el instrumento han sido realizados. En particular, las contribuciones de esta Ph.D. son: 1) un novedoso Global Navigation Satellite Systems Reflectometer que usa las señales P(Y) y C/A después de ser dispersadas sobre la superficie del mar para realizar medidas altimétricas muy precisas. (PYCARO). 2) La primera prueba de concepto de PYCARO se hizo en dos experimentos sobre un pantano y sobre el mar bajo diferentes condiciones de rugosidad. 3) La disperión de las señales GNSS sobre una superfice de agua ha sido estudiada para bajas altitudes para aplicaciones GNSS-R altimétricas de costa. La determinación precisa del nivel local del mar y el estado de las olas desde la costa puede proporcionar información útil de altimetría e información de olas. Para hacer un test de este concepto un experimento en el Canal d'Investigació i Experimentació Marítima (CIEM) fue realizado para dos estados sintéticos de rugosidad. 4) Dos experimentos en avión con esponsor de la ESA se realizaron para estudiar la preción y la exactitud relativa de cGNSS-R. 5) Los resultados empíricos del experimento GNSS-R en BEXUS 17 con esponsor de la ESA realizado en el norte de Suecia sobre bosques boreales mostró que la potencia reflejada de las señales es independiente de la altitud de la plataforma para un tiempo de integración coherente muy alto. 6) Una versión mejorada del PYCARO fue testeada en octubre del 2014 por segunda vez durante el BEXUS 19 que también fue patrocidado por la ESA. Este trabajo proporcionó las primeras medidas GNSS-R sobre bosques boreales en doble frecuencia usando varias constelaciones GNSS. 7) Las primeras medidas polarimétricas (RHCP y LHCP) de GNSS-R sobre bosques boreales también fueron conseguidas durante el experimento BEXUS 19.Award-winningPostprint (published version

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

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    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

    Electromagnetic Wave Theory and Applications

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    Contains table of contents for Section 3, research summary and reports on six research projects.Joint Services Electronics Program (Contract DAAL 03-86-K-0002)Joint Services Electronics Program (Contract DAAL 03-89-C-0001)U.S. Navy - Office of Naval Research (Contract N00014-86-K-0533)National Science Foundation (Contract ECS 86-20029)U.S. Army Research Office (Contract DAAL03 88-K-0057)International Business Machine CorporationSchlumberger-Doll ResearchNational Aeronautics and Space Administration (Contract NAG 5-270)U.S. Navy - Office of Naval Research (Contract N00014-83-K-0258)National Aeronautics and Space Administration (Contract NAG 5-769)U.S. Army Corps of Engineers - Waterways Experimental Station (Contract DACA39-87-K-0022)Simulation TechnologiesU.S. Air Force - Rome Air Development Center (Contract F19628-88-K-0013)U.S. Navy - Office of Naval Research (Contract N00014-89-J-1107)Digital Equipment Corporatio

    Statistical Modeling of SAR Images: A Survey

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    Statistical modeling is essential to SAR (Synthetic Aperture Radar) image interpretation. It aims to describe SAR images through statistical methods and reveal the characteristics of these images. Moreover, statistical modeling can provide a technical support for a comprehensive understanding of terrain scattering mechanism, which helps to develop algorithms for effective image interpretation and creditable image simulation. Numerous statistical models have been developed to describe SAR image data, and the purpose of this paper is to categorize and evaluate these models. We first summarize the development history and the current researching state of statistical modeling, then different SAR image models developed from the product model are mainly discussed in detail. Relevant issues are also discussed. Several promising directions for future research are concluded at last

    On the use of rigorous microwave interaction models to support remote sensing of natural surfaces

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    A study has been undertaken which objective is to contribute to the investigation of the validity of microwave surface scattering models used in remote sensing applications, particularly when applied to realistic representations of natural surfaces. These investigations are based on recent implementations of rigorous methods (MoM and FDTD) and cover a wide range of configurations of observation (mono- and bi-static). Both land (bare soils) and sea surfaces are being investigated

    Integrating Incidence Angle Dependencies Into the Clustering-Based Segmentation of SAR Images

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    Synthetic aperture radar systems perform signal acquisition under varying incidence angles and register an implicit intensity decay from near to far range. Owing to the geometrical interaction between microwaves and the imaged targets, the rates at which intensities decay depend on the nature of the targets, thus rendering single-rate image correction approaches only partially successful. The decay, also known as the incidence angle effect, impacts the segmentation of wide-swath images performed on absolute intensity values. We propose to integrate the target-specific intensity decay rates into a nonstationary statistical model, for use in a fully automatic and unsupervised segmentation algorithm. We demonstrate this concept by assuming Gaussian distributed log-intensities and linear decay rates, a fitting approximation for the smooth systematic decay observed for extended flat targets. The segmentation is performed on Sentinel-1, Radarsat-2, and UAVSAR wide-swath scenes containing open water, sea ice, and oil slicks. As a result, we obtain segments connected throughout the entire incidence angle range, thus overcoming the limitations of modeling that does not account for different per-target decays. The model simplicity also allows for short execution times and presents the segmentation approach as a potential operational algorithm. In addition, we estimate the log-linear decay rates and examine their potential for a physical interpretation of the segments

    Monitoring Snow Cover and Snowmelt Dynamics and Assessing their Influences on Inland Water Resources

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    Snow is one of the most vital cryospheric components owing to its wide coverage as well as its unique physical characteristics. It not only affects the balance of numerous natural systems but also influences various socio-economic activities of human beings. Notably, the importance of snowmelt water to global water resources is outstanding, as millions of populations rely on snowmelt water for daily consumption and agricultural use. Nevertheless, due to the unprecedented temperature rise resulting from the deterioration of climate change, global snow cover extent (SCE) has been shrinking significantly, which endangers the sustainability and availability of inland water resources. Therefore, in order to understand cryo-hydrosphere interactions under a warming climate, (1) monitoring SCE dynamics and snowmelt conditions, (2) tracking the dynamics of snowmelt-influenced waterbodies, and (3) assessing the causal effect of snowmelt conditions on inland water resources are indispensable. However, for each point, there exist many research questions that need to be answered. Consequently, in this thesis, five objectives are proposed accordingly. Objective 1: Reviewing the characteristics of SAR and its interactions with snow, and exploring the trends, difficulties, and opportunities of existing SAR-based SCE mapping studies; Objective 2: Proposing a novel total and wet SCE mapping strategy based on freely accessible SAR imagery with all land cover classes applicability and global transferability; Objective 3: Enhancing total SCE mapping accuracy by fusing SAR- and multi-spectral sensor-based information, and providing total SCE mapping reliability map information; Objective 4: Proposing a cloud-free and illumination-independent inland waterbody dynamics tracking strategy using freely accessible datasets and services; Objective 5: Assessing the influence of snowmelt conditions on inland water resources

    CFAR Ship Detection in Polarimetric Synthetic Aperture Radar Images Based on Whitening Filter

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    Polarimetric whitening filter (PWF) can be used to filter polarimetric synthetic aperture radar (PolSAR) images to improve the contrast between ships and sea clutter background. For this reason, the output of the filter can be used to detect ships. This paper deals with the setting of the threshold over PolSAR images filtered by the PWF. Two parameter-constant false alarm rate (2P-CFAR) is a common detection method used on whitened polarimetric images. It assumes that the probability density function (PDF) of the filtered image intensity is characterized by a log-normal distribution. However, this assumption does not always hold. In this paper, we propose a systemic analytical framework for CFAR algorithms based on PWF or multi-look PWF (MPWF). The framework covers the entire log-cumulants space in terms of the textural distributions in the product model, including the constant, gamma, inverse gamma, Fisher, beta, inverse beta, and generalized gamma distributions (GΓDs). We derive the analytical forms of the PDF for each of the textural distributions and the probability of false alarm (PFA). Finally, the threshold is derived by fixing the false alarm rate (FAR). Experimental results using both the simulated and real data demonstrate that the derived expressions and CFAR algorithms are valid and robust

    Remote Sensing of the Oceans

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    This book covers different topics in the framework of remote sensing of the oceans. Latest research advancements and brand-new studies are presented that address the exploitation of remote sensing instruments and simulation tools to improve the understanding of ocean processes and enable cutting-edge applications with the aim of preserving the ocean environment and supporting the blue economy. Hence, this book provides a reference framework for state-of-the-art remote sensing methods that deal with the generation of added-value products and the geophysical information retrieval in related fields, including: Oil spill detection and discrimination; Analysis of tropical cyclones and sea echoes; Shoreline and aquaculture area extraction; Monitoring coastal marine litter and moving vessels; Processing of SAR, HF radar and UAV measurements
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