17 research outputs found

    Forcing scale invariance in multipolarization SAR change detection

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    This paper considers the problem of coherent (in the sense that both amplitudes and relative phases of the polarimetric returns are used to construct the decision statistic) multi-polarization SAR change detec- tion starting from the availability of image pairs exhibiting possible power mismatches/miscalibrations. The principle of invariance is used to characterize the class of scale-invariant decision rules which are insensitive to power mismatches and ensure the Constant False Alarm Rate (CFAR) property. A maximal invariant statistic is derived together with the induced maximal invariant in the parameter space which significantly compress the data/parameters domain. A Generalized Likelihood Ratio Test (GLRT) is synthesized both for the cases of two- and three-polarimetric channels. Interestingly, for the two-channel case, it is based on the comparison of the condition number of a data-dependent matrix with a suitable threshold. Some additional invariant decision rules are also proposed. The performance of the considered scale-invariant structures is compared to those from two non- invariant counterparts using both simulated and real radar data. The results highlight the robustness of the proposed method and the performance tradeoff involve

    Visualization of and Software for Omnibus Test Based Change Detected in a Time Series of Polarimetric SAR Data

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    Based on an omnibus likelihood ratio test statistic for the equality of several variance-covariance matrices following the complex Wishart distribution and a factorization of this test statistic with associated p-values, change analysis in a time series of multilook polarimetric synthetic aperture radar data in the covariance matrix representation is carried out. The omnibus test statistic and its factorization detect if and when change occurs. Using airborne EMISAR and spaceborne RADARSAT-2 data, this article focuses on change detection based on the p-values, on visualization of change at pixel as well as segment level, and on computer software

    Change Detection for Multi-Polarization SAR

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    Il presente lavoro di tesi si inquadra nel contesto della change detection in immagini SAR. In particolare, la procedura di change detection si pone l'obiettivo di individuare i cambiamenti che avvengono in un area di interesse in un certo intervallo temporale a partire da una coppia coregistrata di immagini SAR rappresentative della scena di interesse nell'intervallo temporale considerato. Presupposto fondamentale delle analisi di change detection è che un cambiamento nella superficie osservata da un sensore corrisponda a un cambiamento di risposta nei dati telerilevati sensibilmente più rilevante rispetto ai cambiamenti dovuti ad altri fattori, quali le condizioni atmosferiche al momento delle acquisizioni, o l'umidità dei suoli o ancora differenze nelle condizioni di acquisizione dei dati telerilevati. Al fine di perseguire tale scopo, in letteratura aperta, vengono considerati due principali approcci noti come change detection incoerente e change detection coerente. A differenza dell'approccio coerente, nella change detection incoerente si cerca di rivelare variazioni del livello di potenza media di una determinata scena sfruttando solo le informazioni di intensità delle immagini disponibili trascurando così le informazioni di fase. L'obiettivo principale che si è inteso perseguire nel lavoro svolto, è stato quello di considerare un nuovo approccio per il problema della change detection basato sulla teoria dell'invarianza nei test di ipotesi considerando un modello di dati polarimetrico, ovvero, supponendo di avere diversità in termini di polarizzazione dei dati relativi alla scena di interesse. In particolare, il principio di invarianza consente, in fase di progetto, di forzare alcune interessanti proprietà della statistica di decisione permettendo di concentrarsi su regole decisionali che mostrano alcune simmetrie naturali implicando importanti proprietà pratiche come il comportamento CFAR (Constant False Alarm Ratio). Inoltre, l'uso del principio di invarianza porta ad una riduzione dei dati, in quanto, tutti i test invarianti possono essere espressi in termini di una statistica, chiamata massimale invariante, che organizza i dati originali in classi di equivalenza. In fase di sviluppo, dopo aver trovato un massimale invariante per il problema in esame si è osservato che il rivelatore invariante ottimo ad esso associato non è UMPI (Uniformly Most Powerful Invariant), quindi, non praticamente realizzabile. Di conseguenza, sono stati determinati alcuni ricevitori invarianti sub-ottimi, le cui prestazioni sono state valutate sia su dati simulati che su immagini SAR reali ad alta risoluzione. Successivamente, si è considerata una particolare struttura diagonale a blocchi per la matrice di covarianza polarimetrica. Imponendo tale vincolo al problema della change detection è stata introdotta una nuova regola di decisione basata sul criterio GLRT (Generalized Likelihood Ratio Test). Inoltre, seguendo un tale approccio, si è dimostrato che il ricevitore sintetizzato garantisce il comportamento CFAR. Tuttavia, nei problemi di change detection, può accadere che le due immagini vengano acquisite con angoli di vista leggermente diversi, o, che le proprietà di propagazione del mezzo cambino tra le due acquisizioni. Tali effetti, possono essere portati in conto in fase di progetto considerando un fattore di scala in termini di intensità. Se il sistema di rilevamento non è stato progettato per tenere conto di tali effetti, il disallineamento in termini di intensità tra le due immagini può introdurre dei falsi allarme con conseguente perdita in termini di capacità rivelazione del sistema di change detection. Per tale motivo, si introduce la possibilità di tenere conto di possibili variazioni di scala al fine di rendere più robusti i ricevitori sintetizzati. Nello specifico, una volta formulato analiticamente il problema considerato, viene sintetizzato il GLRT per i casi in cui si considerino due e tre canali e polarimetrici. Inoltre, utilizzando il principio di invarianza, in primo luogo si dimostra che i ricevitori basati sul GLRT soddisfano la proprietà CFAR, ed, in secondo luogo, vengono proposte alcune ulteriori regole decisionali invarianti. In tutti i casi di studio considerati, le analisi delle prestazioni sono state effettuate utilizzando sia dati simulati che immagini SAR reali ad alta risoluzione. In entrambi i casi, i risultati ottenuti hanno mostrato che alcuni degli algoritmi sviluppati forniscono prestazioni soddisfacenti in termini di capacità di rivelazione dei cambiamenti nell'area di interesse e dunque, rappresentano una buona soluzione per affrontare il problema di change detection

    A Sensitivity Study of L-Band Synthetic Aperture Radar Measurements to the Internal Variations and Evolving Nature of Oil Slicks

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    This thesis focuses on the use of multi-polarization synthetic aperture radar (SAR) for characterization of marine oil spills. In particular, the potential of detecting internal zones within oil slicks in SAR scenes are investigated by a direct within-slick segmentation scheme, along with a sensitivity study of SAR measurements to the evolving nature of oil slicks. A simple, k-means clustering algorithm, along with a Gaussian Mixture Model are separately applied, giving rise to a comparative study of the internal class structures obtained by both strategies. As no optical imagery is available for verification, the within-slick segmentations are evaluated with respect to the behavior of a set of selected polarimetric features, the prevailing wind conditions and weathering processes. In addition, a fake zone detection scheme is established to help determine if the class structures obtained potentially reflect actual internal variations within the slicks. Further, the evolving nature of oil slicks is studied based on the temporal development of a set of selected geometric region descriptors. Two data sets are available for the investigation presented in this thesis, both captured by a full-polarization L-band airborne SAR system with high spatial- and temporal resolution. The results obtained with respect to the zone detection scheme developed supports the hypothesis of the existence of detectable zones within oil spills in SAR scenes. Additionally, the method established for studying the evolving nature of oil slicks is found convenient for accessing the general behavior of the slicks, and simplifies interpretation

    Innovative solutions based on the EM-algorithm for covariance structure detection and classification in polarimetric SAR images

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    This paper addresses the challenge of identifying the polarimetric covariance matrix (PCM) structures associated with a polarimetric SAR image. Interestingly, such information can be used, for instance, to improve the scene interpretation or to enhance the performance of (possibly PCM-based) segmentation algorithms as well as other kinds of methods. To this end, a general framework to solve a multiple hypothesis test is introduced with the aim to detect and classify contextual spatial variations in polarimetric SAR images. Specifically, under the null hypothesis, only one unknown structure is assumed for data belonging to a 2-dimensional spatial sliding window, whereas under each alternative hypothesis, data are partitioned into subsets sharing different PCM structures. The problem of partition estimation is solved by resorting to hidden random variables representative of covariance structure classes and the expectation maximization (EM) algorithm. The effectiveness of the proposed detection strategies is demonstrated on both simulated and real polarimetric SAR data also in comparison with existing classification algorithms

    Ecohydrological Footprints:Quantitative Response of Ecosystems to Changes in their Hydrological Drivers

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    Ecohydrological footprints are defined as the response of ecosystem functions or services to changes in their hydrologic drivers. In this thesis, several diverse footprints are addressed: noise-driven effects on storage-discharge relations and catchment streamflow distributions, that are important drivers of biodiversity; soil salinization and its ecohydrological implications; topological effects of the ecological interaction networks on living communities (e.g. on their species persistence); and form and function of the global virtual water trade network. The coherence of the conceptual framework is provided by the study of drivers and controls of ecohydrological variability using methodological approaches based on statistical mechanics. In fact, this thesis work outlines a significant portion of environmental statistical mechanics, an overarching discipline that is emerging in recent years, which applies mathematical tools from statistical mechanics to model several ecohydrological processes. The proposed relevance of this thesis lies in the major effects of hydrologic drivers on ecological process. The view that emerges from current research in ecohydrology, that this thesis supports, is that there exists a definite need for an integrated understanding of ecological and hydrological processes. Because stochasticity is intrinsic to environmental and ecohydrological variability, noise plays an important and constructive role in ecohydrological processes. In this thesis, a stochastic approach is applied to analyze different ecohydrological processes, ranging from green and blue water flows in river basins (part I), ecosystem dynamics affected by the directional dispersal provided by river networks (part II) to water footprints of human society (part III).Methods range from novel exact solutions to stochastic differential equations to random graph theory applications, and imply the analysis of suitable field data. An analytical framework for quantitative analysis is laid out to tackle complex problems and to estimate the effects of environmental change on the interaction of the hydrologic processes with the biota. The main results of this thesis are: i) the achievement of exact solutions for the probability distribution of catchment streamflow, that takes in account stochastic fluctuations in the storage-discharge relation and for the condition of a noise induced phenomena to the streamflows regimes; ii) the stationary solutions of soil salinity under stochastic hydrologic forcing; iii) a novel solution of the Ito-Stratonovich problem in multiplicative Poisson processes; iv) the proper framework for species' persistence time distributions, as a function of topological constraints on the ecosystem, and its connection with other important macroecological laws. A related length-bias sampling problem is also solved. v) A statistical analysis of the global virtual trade network and a semi-analytical model that is able to describe most of the observed properties

    The 1990 Reference Handbook: Earth Observing System

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    An overview of the Earth Observing System (EOS) including goals and requirements is given. Its role in the U.S. Global Change Research Program and the International--Biosphere Program is addressed. The EOS mission requirements, science, fellowship program, data and information systems architecture, data policy, space measurement, and mission elements are presented along with the management of EOS. Descriptions of the facility instruments, instrument investigations, and interdisciplinary investigations are also present. The role of the National Oceanic and Atmospheric Administration in the mission is mentioned

    Earth resources: A continuing bibliography with indexes (issue 61)

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    This bibliography lists 606 reports, articles, and other documents introduced into the NASA scientific and technical information system between January 1 and March 31, 1989. Emphasis is placed on the use of remote sensing and geophysical instrumentation in spacecraft and aircraft to survey and inventory natural resources and urban areas. Subject matter is grouped according to agriculture and forestry, environmental changes and cultural resources, geodesy and cartography, geology and mineral resources, oceanography and marine resources, hydrology and water management, data processing and distribution systems, and instrumentation and sensors, and economic analysis
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