Thèses sur le sujet « Spaceborne radars »

The thesis concerns the assessment of the performance of the upcoming Earth Cloud Aerosols Radiation Explorer (EarthCARE) Doppler cloud profiling radar in convection. Spaceborne Doppler radar data are simulated starting from high-resolution CRM model data, through forward Monte Carlo simulation from which the voltage signals as sampled by specific radar configuration are generated. Until the launch of Earth- CARE in 2016, simulations are the only means of assessing the impact of EarthCAREs configuration on the accuracy of the Doppler products (reflectivity and mean Doppler velocity). Two of the main contributors to EC-CPR total error budget are the multiple scattering and non-uniform beam filling effect errors, which can be mitigated using methods described in the thesis. However, for Earth- CARE radar using the conventional pulse pair technique, the scientific requirement for accuracy of 1 m/s at 1 km integration of Doppler velocity cannot be met for deep convective systems, even if the correction methods are applied. The thesis then focuses on six polarization diversity radar systems, three for W-band (94 GHz) and three for Ka-band (35 GHz). After the correction methods are applied for MS and NUBF effects, the accuracy of 1 m/s for 500 m integration is possible for all W-band configurations assessed. This includes relatively small antennas of 2.5 m currently being implemented in space. Consequently, two key results for measurements in deep convection can be drawn for future radar concept design. Firstly, the large antenna will help to minimize the effects of non-uniform beam filling and multiple scattering. Secondly, the polarization diversity can solve the problem of aliasing of velocities.

Thesis (M.S. in Physical Oceanography) Naval Postgraduate School, December 2001.
"December 2001". Thesis advisor(s): Durkee, Philip A . ; Paduan, Jeffrey D. Includes bibliographical references (p.53-54). Also available online.

Following success in other areas as a remote sensor, the spaceborne microwave image radars are assuming a notable position in the problem of ship detection for civilian and military purposes. This work will discuss the strong and weak points of Synthetic Aperture Radar (SAR) when used for ship detection. First, the thesis gives a brief description of SAR fundamentals, image processing and the parameters for ship detection. Second, the actual techniques, limitations, errors and some models used for ship detection are described. Finally, using a well-known and reliable ship detection model (Vachon et al. 1997), tested in the Canadian Ocean Monitoring Workstation and in some validation field programs, the new generation of spaceborne SARs, mainly RADARSAT 2, are analyzed for ship detection capabilities. During the analysis parameters like wind velocity, wind direction related to the antenna, satellite incident angle and Number of Looks are changed to study their influence on ship detection.

Les radars à synthèse d'ouverture (SAR) spatioportés ont fait la preuve de leur valeur inestimable dans l'observation des vents et des vagues océaniques mondiaux. Les images SAR acquises par plusieurs capteurs sont utilisées, notamment Sentinel-1 (S-1), Envisat/ASAR, Gaofen-3 et Radarsat-2. Cette thèse passe en revue les paramètres SAR couramment utilisés dans la première partie. Une série d'étapes d'étalonnage sont nécessaires pour obtenir un NRCS approprié et une évaluation du NRCS est effectuée pour le mode d'onde S-1 (WV). Il s'avère que WV est mal calibré et est donc recalibré pour obtenir un NRCS précis. Il a été démontré que la coupure de l'azimut est complémentaire du NRCS et peut expliquer l'impact de l'état de la mer sur l'extraction du vent. D'après les produits SAR entièrement polarimétriques disponibles, la coupure de l'azimut varie considérablement en fonction des polarisations. La transformation actuelle de la cartographie SAR est suffisante pour interpréter la coupure azimutale copolarisée, mais pas pour la polarisation croisée. Compte tenu des limites de l'imagerie SAR, un nouveau paramètre est proposé et défini en fonction du spectre croisé de l'image SAR, appelé MACS. La partie imaginaire de MACS est une quantité signée par rapport à la direction du vent. Compte tenu de cette dépendance, on s'attend à ce qu'un algorithme indépendant de récupération du vent en bénéficie. L'ampleur du MACS peut aider à estimer la fonction de modulation de la cartographie SAR. De plus, la MACS donne également des résultats prometteurs en ce qui concerne les études globales sur les vagues. Les signatures globales du MACS à différentes longueurs d'onde sont bien représentatives de la distribution spatiale et saisonnière des vents. Les MACS des vagues longues montrent des valeurs plus élevées sur les trajectoires des tempêtes alors que les vagues plus courtes sont principalement dans les vents des trader. Ces résultats devraient aider à évaluer les résultats du modèle et compléter les études ultérieures sur le climat spectral global des vagues
Spaceborne synthetic aperture radar (SAR) has been demonstrated invaluable in observing the global ocean winds and waves. SAR images acquired by multiple sensors are employed, including Sentinel-1(S-1), Envisat/ASAR, Gaofen-3 and Radarsat-2. This thesis reviews the commonly used SAR parameters (NRCS and azimuth cutoff) in the first part. A series of calibration steps are required to obtain a proper NRCS and assessment of NRCS is carried out for S-1wave mode (WV). It turns out that WV is poorly calibrated and is thus re-calibrated to obtain accurate NRCS. Azimuth cut off is demonstrated to be complementary to NRCS and can account for the sea state impact on the wind retrieval. Based on the available fully polarimetric SAR products, azimuth cut off is found to vary greatly with polarizations. The present SAR mapping transformation is sufficient to interpret the co-polarized azimuth cut off, while not for the cross-polarization. With the limitations of SAR imaging in mind, a new parameter is proposed and defined based on the SAR image cross-spectra, termed as MACS. The imaginary part of MACS is found to be a signed quantity relative to the wind direction. Given this dependence, an independent wind retrieval algorithm is expected to benefit. The magnitude of MACS is able to aid for estimate of modulation function of SAR mapping. In addition, MACS also gives promising results regarding the global wave studies. The global signatures of MACS at various wave lengths are well representative of the winds distributions, spatially and seasonally. MACS of long waves shows greater values over the storm tracks while the shorter waves are mostly within the trader winds. These results are expected to help evaluate the model outputs and complement further studies of the global wave spectral climate. Data continuity in the coming 10 years shall extend the study towards longer duration

L'observation de la dynamique de l'atmosphère et de la surface de l'océan peut être réalisée par télédétection radar. L'approche habituelle consiste, dans les deux cas, à calculer numériquement le spectre Doppler des échos temporels reçus à l'aide d'une transformée de Fourier discrète. Bien que satisfaisante pour la plupart des applications, cette méthode ne convient pas pour l'observation de phénomènes transitoires, plus courts que le temps d'intégration nécessaire à l'observation radar. Nous utilisons une technique alternative, basée sur une représentation autorégressive des séries temporelles radar et associée à la méthode dite à entropie maximale. Cette approche est appliquée à la mesure de courants de surface par radar côtier dans la bande des hautes fréquences, puis à celle de vent dans la basse atmosphère par radar en bande L. Dans les deux situations, nous montrons à l'aide de simulations numériques, de comparaisons avec d'autres instruments et d'études de cas que l'approche proposée conduit à des estimations fiables des grandeurs géophysiques (courants marins et vitesses de vent) pour des temps d'intégration brefs, là où la méthode conventionnelle échoue
Observations of atmospheric and ocean surface dynamics can be performed via radar remote sensing. The usual approach consists, in both cases, in numerically calculating the Doppler spectrum of the received temporal echoes using a discrete Fourier transform. Although satisfactory for most applications, this method is not suitable for observations of transient phenomena due to being shorter than the integration time required for radar observations. We use an alternative technique based on an autoregressive representation of the radar time series combined with the maximum entropy method. This approach is applied to coastal radar measurements of surface currents in the high frequency band as well as to L-band radar measurements of wind in the lower atmosphere. For both cases, through numerical simulations and case studies, we compare our approach with others that use different instruments. We show that for short integration times, where conventional methods fail, our proposed approach leads to reliable estimates of geophysical quantities (ocean currents and wind speeds)

A bistatic radar has a physically separated transmitter and receiver. This research pro gramme investigates a bistatic radar system which uses a spaceborne synthetic aperture radar transmitter on board the European Space Agency's Envisat satellite and a station ary, ground based receiver. The advantages of this variant of the bistatic configuration includes the passive and therefore covert nature of the receiver, its relatively low cost, in addition to the possibility of using a non-cooperative transmitter. The theory behind bistatic SAR systems is covered, including the specific case investi gated. The design, construction and testing of the bistatic receiver, which uses two separate channels, for the direct signal from the satellite (for synchronisation purposes) and the re flected signals from the imaged scene is also described. A SAR processing scheme using an adapted chirp scaling algorithm is presented and demonstrated through simulations to produce focused images for the scenario. The results of several bistatic imaging experiments are analysed through comparisons with theoretical impulse responses, and comparisons with satellite photographs, the corresponding monostatic image produced by Envisat, and the bistatic ambiguity function. It is demonstrated that focused images may be produced with such a system, although the performance achievable is dependent upon the imaging geometry. Different look direc tions of the receiver produce widely differing resolution values. The optimum choice of look direction must be weighed against possible direct signal interference in the reflected signal channel. Other effects, such as azimuth ambiguities caused by the sampling of the mov ing transmitter beam by the pulse repetition frequency may also have an effect, depending upon the combined transmit/receive beam pattern. Aspects of the system that could be investigated in the future are identified, for example the addition of an extra channel to the receiver in order to perform bistatic displaced phase centre antenna or interferometry experiments.

International Telemetering Conference Proceedings / October 25-28, 1993 / Riviera Hotel and Convention Center, Las Vegas, Nevada
Spaceborne wind scatterometers are designed principally to measure radar backscatter from the ocean's surface for the determination of the near-surface wind direction and speed. Although measurements of the radar backscatter are made over land, application of these measurements has been limited primarily to the calibration of the instrument due to their low resolution (typically 50 km). However, a recently developed resolution enhancement technique can be applied to the measurements to produced medium-scale radar backscatter images of the earth's surface. Such images have proven useful in the study of tropical vegetation3 as well as glacial5 and sea6 ice. The technique has been successfully applied2 to Seasat scatterometer (SASS) data to achieve image resolution as fine as 3-4 km. The method can also be applied to ERS-l scatterometer data. Unfortunately, the instrument processing method employed by SASS limits the ultimate resolution which can be obtained with the method. To achieve the desired measurement overlap, multiple satellite passes are required. However, with minor modifications to future Doppler scatterometer systems (such as the NASA scatterometer [NSCAT] and its follow-on EoS-era scatterometer NEXSCAT) imaging resolutions down to 1-2 km for land/ice and 5-10 km for wind measurement may be achieved on a single pass with a moderate increase in downlink bandwidth (from 3.1 kbps to 750 kbps). This paper describes these modifications and briefly describes some of the applications of this medium-scale Ku-band imagery for vegetation studies, hydrology, sea ice mapping, and the study of mesoscale winds.

This work examines the effectiveness of spaceborne synthetic aperture radar (SAR) for investigating seasonally variable glaciological parameters, in particular its ability to discriminate glacier surface facies in order to estimate glacier mass balance. A multitemporal C-band SAR dataset of Nordenskiold Land, Spitsbergen, acquired by the ERS-1 satellite, is used for the analysis, which focuses on mountain glaciers rather than ice sheets. Validating field measurements of ice and snowpack parameters were obtained contemporaneously with two SAR images, prior to and during the ablation season. A general model for the annual backscatter cycle from a sub-polar glacier is derived from SAR data of three glacierised areas. This model reveals two seasonal reversals in the relative magnitude of backscatter from the ice and wet-snow facies, principally through a 10 dB change in the latter; these reversals mark the start and end of the ablation season. It is shown that a combination of winter and summer SAR imagery is necessary to estimate the equilibriumline altitude of a sub-polar glacier. Topographic distortion is the major limiting factor regarding the utilisation of SAR data for studying mountainous glaciers. Existing theoretical models of radar backscatter from snow and ice are validated for three scenarios: glacier ice, dry snow overlying glacier ice, and wet snow, using the in situ measurements. In addition, temporal variations of ice and snowpack parameters observed during the field campaigns are used to predict short-term seasonal changes in backscatter, and to corroborate the model of annual backscatter. ERS-1 SAR data are compared to NIR Landsat TM data in separate analyses of data information content and temporal resolution; the optical data are found to be better for both facies discrimination and obtaining synoptic glaciological information in mountainous regions. However, the Spitsbergen cloud cover is such that useful TM data may not necessarily be acquired in a given year; consequently SAR is the better sensor for obtaining guaranteed synoptic mass balance data for use in climate change studies, or for studying short-term events like glacier surges. These conclusions are shown to apply to the entire European Arctic sector except East Greenland, where the two sensors have similar temporal resolutions. Data from both sensors were integrated to provide an estimation of the synoptic mass balance of Nordenskiold Land for 1991/92; the results, which indicate an overall slightly negative mass balance, demonstrate that elevation is the principal factor governing glacier net mass balance in the region.

International Telemetering Conference Proceedings / October 30-November 02, 1995 / Riviera Hotel, Las Vegas, Nevada
A radar scatterometer transmits a series of RF pulses and measures the total-power (energy) of the backscattered signal. Measurements of the backscattered energy from the ocean's surface can be used to infer the near-surface wind vector [7]. Accurate backscatter energy measurements are required to insure accurate wind estimates. Unfortunately, the signal measurement is noisy so a separate measurement of the noise-only total-power is subtracted from the signal measurement to estimate the echo signal energy. A common metric for evaluating the accuracy of the scatterometer energy measurement is the normalized signal variance, termed K(p). In designing a scatterometer tradeoffs in design parameters are made to minimize K(p). Spaceborne scatterometers have traditionally been based on fan-beam antennas and CW modulation for which expressions for K(p) exist. Advanced pencil-beam scatterometers, such as SeaWinds currently being developed by NASA use modulated Signals so that new K(p) expressions are required. This paper outlines the derivation of the generalized K(p) expression. While very complicated in its exact form, with a simplified geometry the K(p) expression can be related to the radar ambiguity function. The resulting analysis yields insights into the tradeoffs inherent in a scatterometer design and permits analytic tradeoffs in system performance.

Spaceborne radar sounders are an important class of remote sensing instruments which operate by recording backscattered electromagnetic waves in the vicinity of a solid planetary body. The incoming waves are generally transmitted by the radar itself (active sounding), although external signals of opportunity can also be used (passive sounding). There are currently two major planetary radar sounders under development, both headed to the Jovian icy moons (Europa, Ganymede and Callisto). Designing a radar sounder is a very challenging process involving careful leveraging of heritage and predictive tools, and in which backscattering simulators play a central role. This is especially true for coherent simulators, due to their higher accuracy and the possibility they offer to apply advanced processing techniques on the resulting simulated data, such as synthetic aperture radar focusing, or any other operation which requires field amplitude, phase and polarisation. For this reason, designing computationally-efficient coherent simulators is an important and active research area. The first contribution of this thesis is a novel multilayer coherent simulator based on the Stratton-Chu equation and the linear phase approximation, which can generate realistic simulated radar data on a wide range of surface and subsurface digital elevation models (DEM), using only a fraction of the computational resources that a finite-difference time-domain method would need. Thorough validation was conducted against both theoretical formulations and real data, which confirmed the accuracy of the method. The method was then generalised to noisy active and passive sounding, which is an important capability in the context of the proposed use of passive sounding on the Jovian icy moons. Provided that representative information about the surface and this external field exists, the simulator could compare the relative scientific value of active and passive sounding of a given target under given conditions. However, quality DEMs of the Jovian icy moons are scarce. For this reason we also present a comparative study of the fractal roughness of Europa and Mars (a much better studied body), where we derive fractal analogue maps of twelve types of Europan terrains on Mars. These maps could be used to guide the choice of Martian DEMs on which to perform representative backscattering simulations for future radar missions on Europa. Finally, we explore the possibility of entirely new radar architectures with the novel concept of the distributed radar. In a distributed sounder, very large across-track antennas can be synthesised from smallsats flying on selected orbits, providing a way to obtain a highly-directive antenna without the need to deploy large and complex structures in space. We develop an analytical formulation to treat the problem of beamforming with an array affected by perturbations on the positions of its array elements, and propose a set of Keplerian parameters that enable the concept.

Spaceborne radar sounders are an important class of remote sensing instruments which operate by recording backscattered electromagnetic waves in the vicinity of a solid planetary body. The incoming waves are generally transmitted by the radar itself (active sounding), although external signals of opportunity can also be used (passive sounding). There are currently two major planetary radar sounders under development, both headed to the Jovian icy moons (Europa, Ganymede and Callisto). Designing a radar sounder is a very challenging process involving careful leveraging of heritage and predictive tools, and in which backscattering simulators play a central role. This is especially true for coherent simulators, due to their higher accuracy and the possibility they offer to apply advanced processing techniques on the resulting simulated data, such as synthetic aperture radar focusing, or any other operation which requires field amplitude, phase and polarisation. For this reason, designing computationally-efficient coherent simulators is an important and active research area. The first contribution of this thesis is a novel multilayer coherent simulator based on the Stratton-Chu equation and the linear phase approximation, which can generate realistic simulated radar data on a wide range of surface and subsurface digital elevation models (DEM), using only a fraction of the computational resources that a finite-difference time-domain method would need. Thorough validation was conducted against both theoretical formulations and real data, which confirmed the accuracy of the method. The method was then generalised to noisy active and passive sounding, which is an important capability in the context of the proposed use of passive sounding on the Jovian icy moons. Provided that representative information about the surface and this external field exists, the simulator could compare the relative scientific value of active and passive sounding of a given target under given conditions. However, quality DEMs of the Jovian icy moons are scarce. For this reason we also present a comparative study of the fractal roughness of Europa and Mars (a much better studied body), where we derive fractal analogue maps of twelve types of Europan terrains on Mars. These maps could be used to guide the choice of Martian DEMs on which to perform representative backscattering simulations for future radar missions on Europa. Finally, we explore the possibility of entirely new radar architectures with the novel concept of the distributed radar. In a distributed sounder, very large across-track antennas can be synthesised from smallsats flying on selected orbits, providing a way to obtain a highly-directive antenna without the need to deploy large and complex structures in space. We develop an analytical formulation to treat the problem of beamforming with an array affected by perturbations on the positions of its array elements, and propose a set of Keplerian parameters that enable the concept.

Forests are considered important reservoirs of organic carbon and have been identified as essential in moderating climate change. Measuring the amount of carbon stored in forests helps improve our understanding of the carbon budget and help with climate change adaptation strategies. Therefore, effective and accurate methods in characterizing changing forest cover and biomass densities are needed. Both LiDAR (light detection and ranging) and radar (radio detection and ranging) technologies can contribute towards the study of forest biomass but one sensor alone cannot provide all the information necessary to monitor forests. Understanding and investigating synergies between different remotely sensed data sets provides new and innovative opportunities to monitor forests. The overall objective reported in this thesis is to demonstrate novel methods to integrate two remotely sensed data sets (i.e., radar and LiDAR) for the application of biomass estimation. This research was divided into two main questions: (1) can shorter wavelength radar variables provide improved biomass estimates when combined with LiDAR data; and (2) can the use of space-borne radar extend aboveground biomass estimates over a larger area using spatial modeling methods. In the first study, relationships between biomass and biomass components with LiDAR and radar data were examined through regression analyses to determine the best combined parameters to estimate biomass. Results indicated that integrating radar variables to a LiDAR-derived model of aboveground biomass helped explain an additional 17.9% of the variability in crown biomass. This corresponded in an improvement in crown biomass estimates of 10% RMSE. Furthermore, InSAR coherence magnitudes from C-band and L-band radars provided the best estimate of aboveground biomass using radar alone. In the second study, aboveground biomass transects derived from plot-based field data and LiDAR, and wall-to-wall radar were spatially integrated using three kriging techniques. The results indicated the importance of correlation between primary and secondary variables when using these kriging approaches. Also a 1000 m distance between biomass transects, was found to provide reasonable compromise between ease of use, accuracy, and cost of obtaining LiDAR data for the study area. Insights into other opportunities for further development in spatial modeling techniques are discussed.

The NASA Scatterometer (NSCAT) was launched August 20, 1996 aboard the National Space Development Agency of Japan's Advanced Earth Observing Spacecraft (ADEOS). NSCAT's primary mission was to measure radar backscatter over the world's oceans. These measurements are used to generate estimates of ocean wind speed and direction. Scatterometers must be calibrated before their measurements are scientifically useful. However, the calibration of NSCAT must be done in orbit. A new methodology for selecting land regions for use in extended target spaceborne scatterometer calibration is first developed. Next, a summary of the calibration technique used in this thesis is presented. While the foundation of this technique was previously developed theoretically, the work in this thesis is its first application for calibration/validation of an on-line spaceborne radar system. The technique is extended to estimate simultaneously NSCAT's calibration and the host spacecraft's attitude error. The attitude references reported by the attitude control system on-board ADEOS are deemed erroneous. Results of this expanded technique, applied under varying assumptions, are presented for consideration. A summary and suggestions for future research conclude this work.

Urban areas around the world are changing constantly and therefore it is necessary to update urban land cover maps regularly. Remote sensing techniques have been used to monitor changes and update land-use/land-cover information in urban areas for decades. Optical imaging systems have received most of the attention in urban studies. The development of SAR applications in urban monitoring has been accelerated with more and more advanced SAR systems operating in space.   This research investigated object-based and rule-based classification methodologies for extracting urban land-cover information from high resolution SAR data. The study area is located in the north and northwest part of the Greater Toronto Area (GTA), Ontario, Canada, which has been undergoing rapid urban growth during the past decades. Five-date RADARSAT-1 fine-beam C-HH SAR images with a spatial resolution of 10 meters were acquired during May to August in 2002. Three-date RADARSAT-2 ultra-fine-beam C-HH SAR images with a spatial resolution of 3 meters were acquired during June to September in 2008.   SAR images were pre-processed and then segmented using multi-resolution segmentation algorithm. Specific features such as geometric and texture features were selected and calculated for image objects derived from the segmentation of SAR images. Both neural network (NN) and support vector machines (SVM) were investigated for the supervised classification of image objects of RADARSAT-1 SAR images, while SVM was employed to classify image objects of RADARSAT-2 SAR images. Knowledge-based rules were developed and applied to resolve the confusion among some classes in the object-based classification results.   The classification of both RADARSAT-1 and RADARSAT-2 SAR images yielded relatively high accuracies (over 80%). SVM classifier generated better result than NN classifier for the object-based supervised classification of RADARSAT-1 SAR images. Well-designed knowledge-based rules could increase the accuracies of some classes after the object-based supervised classification. The comparison of the classification results of RADARSAT-1 and RADARSAT-2 SAR images showed that SAR images with higher resolution could reveal more details, but might produce lower classification accuracies for certain land cover classes due to the increasing complexity of the images. Overall, the classification results indicate that the proposed object-based and rule-based approaches have potential for operational urban land cover mapping from high-resolution space borne SAR images.
QC 20101209

Urban represents one of the most dynamic areas in the global change context. To support rational policies for sustainable urban development, remote sensing technologies such as Synthetic Aperture Radar (SAR) enjoy increasing popularity for collecting up-to-date and reliable information such as urban land cover/land-use. With the launch of advanced spaceborne SAR sensors such as RADARSAT-2, multitemporal fully polarimetric SAR data in high-resolution become increasingly available. Therefore, development of new methodologies to analyze such data for detailed and accurate urban mapping is in demand.   This research investigated multitemporal fine resolution spaceborne polarimetric SAR (PolSAR) data for detailed urban land cover mapping. To this end, the north and northwest parts of the Greater Toronto Area (GTA), Ontario, Canada were selected as the study area. Six-date C-band RADARSAT-2 fine-beam full polarimetric SAR data were acquired during June to September in 2008. Detailed urban land covers and various natural classes were focused in this study.   Both object-based and pixel-based classification schemes were investigated for detailed urban land cover mapping. For the object-based approaches, Support Vector Machine (SVM) and rule-based classification method were combined to evaluate the classification capacities of various polarimetric features. Classification efficiencies of various multitemporal data combination forms were assessed. For the pixel-based approach, a temporal-spatial Stochastic Expectation-Maximization (SEM) algorithm was proposed. With an adaptive Markov Random Field (MRF) analysis and multitemporal mixture models, contextual information was explored in the classification process. Moreover, the fitness of alternative data distribution assumptions of multi-look PolSAR data were compared for detailed urban mapping by this algorithm.   Both the object-based and pixel-based classifications could produce the finer urban structures with high accuracy. The superiority of SVM was demonstrated by comparison with the Nearest Neighbor (NN) classifier in object-based cases. Efficient polarimetric parameters such as Pauli parameters and processing approaches such as logarithmically scaling of the data were found to be useful to improve the classification results. Combination of both the ascending and descending data with appropriate temporal span are suitable for urban land cover mapping. The SEM algorithm could preserve the detailed urban features with high classification accuracy while simultaneously overcoming the speckles. Additionally the fitness of the G0p and Kp distribution assumptions were demonstrated better than the Wishart one.

QC 20110315

Le tecniche Multi-temporali SAR interferometriche (Mt-InSAR) rappresentano oggigiorno strumenti consolidati per mappare l’evoluzione temporale dei fenomeni di deformazione del suolo Terrestre. Queste tecniche utilizzano congiuntamente sets di interferogrammi SAR differenziali al fine di estrarre la componente legata alla deformazione e produrre così serie storiche di deformazione dei bersagli osservati dal sensore. L'affidabilità delle misure prodotte utilizzando algoritmi Mt-InSAR è strettamente legata alla capacità degli stessi algoritmi nell’isolare esclusivamente i segnali legati alla deformazione dal segnale complessivo interferometrico, e questa operazione diventa sempre più complessa all’aumentare dei livelli di rumore in ciascun interferogramma SAR coinvolto. Le tecniche Mt-InSAR canoniche sono altamente affidabili nel monitorare l'evoluzione dello spostamento dei target che risultano essere ampiamente stabili o coerenti per tutto il periodo di analisi. Diversamente, quando i bersagli sono particolarmente affetti da problemi di decorrelazione, le stime di deformazione ottenute risultano corrotte e inaffidabili. Questo pone le basi per lo sviluppo di processori Mt-InSAR avanzati che possano fornire stime accurate della deformazione del suolo anche in scenari con problemi di decorrelazione più o meno severi. In questo lavoro di tesi affronta dapprima lo studio dello stato dell’arte delle tecniche Mt-InSAR canoniche applicabili sia nel caso di piattaforme satellitare che terrestri, e dopodiché si propongono delle nuove tecniche Mt-InSAR per superare alcune delle criticità riscontrante. In particolare si studiano le tecniche convenzionali Mt-InSAR multigriglia per l'analisi dei target alla griglia di risoluzione spaziale più risoluta, evidenziandone le loro criticità in aree a media e bassa coerenza, e proprio in questo ambito è proposta una tecnica innovativa per meglio operare in ambienti decorrelati. Il metodo proposto si basa su efficienti operazioni con cui viene srotolata la fase (PhU) interferometrica eseguite alle scale spaziali native, ed in particolare, si srotolano dapprima gli interferogrammi alla scala di soluzione mediata (ML) attraverso algoritmi di PhU convenzionali (o avanzati). Successivamente, gli interferogrammi ML srotolati vengono utilizzati per facilitare le operazioni di PhU eseguite alla scala più fine (single-look). In dettaglio, gli interferogrammi multi-look srotolati vengono ricampionati alla griglia single-look e sottratti a modulo modulo-2π agli interferogrammi single-look. Gli interferogrammi epurati dai contributi a bassa frequenza vengono poi srotolati e aggiunti nuovamente agli interferogrammi multilook ricampionati alla griglia di risoluzione più fine. Per realizzare queste operazioni, a differenza dei metodi multigriglia canonici, non si utilizza alcun modello (lineare/non lineare) per recuperare le componenti di deformazione in alta frequenza. Infine, gli interferogrammi single-look srotolati sono opportunamente invertiti al fine di calcolare le serie storiche di deformazione del suolo attraverso un qualsiasi algoritmo a piccola baseline (SB) InSAR multi-temporale. I risultati sperimentali sono stati ottenuti elaborando una serie di dati SAR acquisiti dal sensore COSMO-SkyMed (banda X) sulla zona costiera di Shanghai, in Cina. La tesi prosegue analizzando le tecniche ai minimi quadrati pesate (WLS) e su come sono sfruttate nell’ambito InSAR al fine di migliorare l’operazione con cui si srotola la fase interferometrica e la generazione di serie storiche di deformazione. Proprio in questo contesto, utilizzando gli approcci WLS, si estende l'utilizzabilità dell'algoritmo Mt-InSAR Small BAseline Subset (SBAS) in aree caratterizzate da una coerenza spaziale medio-bassa. In particolare, pixel per pixel, si invertono esclusivamente le fasi interferometriche coerenti utilizzando una metrica a minimi quadrati pesati. Per cui attraverso una selezione adattiva, per ogni pixel si utilizzano ed invertono soltanto le fasi interferometriche coerenti, e tale caratterista può portare a diversi sottoinsiemi disgiunti di dati SAR, che sono poi invertiti sfruttando la Decomposizione a Valori Singolari Pesata (WSVD). Tuttavia, per taluni pixel, l’utilizzo esclusivo delle fasi interferometriche coerenti può portare in alcuni casi allo scarto di acquisizioni SAR particolarmente rumorose, il che si traduce in serie storiche di deformazione affidabili ma con campionamento temporale variabile. I risultati sperimentali sono stati condotti applicando la tecnica sviluppata ad un set di dati SAR acquisiti dai sensori COSMO-SkyMed (CSK) sulla regione Basilicata, nel sud Italia. Il lavoro di tesi continua analizzando le proprietà che ledono alla irrotazionalità delle triplette di fase di interferogrammi SAR multi-look. In particolare, si studiano le conseguenze delle incongruenze temporali di fase dei multi-look sulla generazione delle serie storiche di deformazione del suolo attraverso metodi SB Mt-InSAR. La ricerca condotta mostra come queste incongruenze di fase si possono propagare attraverso una rete temporale ridondante di interferogrammi SB, ed insieme agli errori di PhU, pregiudicano la qualità dei prodotti InSAR generati. In letteratura questo effetto va sotto il nome di bias di fase, il quale può pregiudicare l’affidabilità dei metodi SB quando si impostano delle soglie sulla massima baseline temporale troppo stringenti (nell’ordine di 30 giorni o meno). Proponiamo così, due nuovi metodi per la compensazione di tali fenomeni di bias, i quali metodi sono stati testati utilizzando dati SAR simulati e reali. I dati reali sono stati acquisiti dai sensori Sentinel-1A/B (banda C) sulle aree del Nevada (U.S.), e sulla zona del monte Etna in Sicilia, nel sud Italia. Dopo lo sviluppo di algoritmi per la parte satellitare, il lavoro si sposta sui sensori SAR terrestri (GB-SAR). In questo ambito proponiamo un metodo per stimare e compensare i disturbi introdotti dallo strato atmosferico (APS) in interferogrammi GB-SAR. Un’ambia analisi fisica, statistica e matematica dell'approccio presentato è fornita, discutendo inoltre le potenzialità e i limiti del metodo che a differenza di altri algoritmi, che stimano l'APS dai segnali di fase srotolati, nella metodologia proposta la compensazione avviene direttamente sul dato arrotolato, in modo tale che la stima non è affetta da nessun potenziale errore di PhU. Gli esperimenti eseguiti su dati InSAR GB-SAR simulati e reali confermano la validità della tecnica proposta, confermando inoltre che il metodo è vantaggioso nelle zone caratterizzate da una forte escursione di quota (come ad esempio nelle regioni Alpine e montuose). Infine, viene presentata un'applicazione SAR interferometrica per la stima delle deformazioni della superficie investigata in tre dimensioni (3-D) attraverso l'uso congiunto ed integrato di dati SAR acquisiti da piattaforme satellitari e terrestri. Più precisamente, la catena di combinazione interferometrica sviluppata si compone anche degli innovativi algoritmi Mt-InSAR sviluppati in questo lavoro di tesi, al fine di ottenere mappe di velocità media di deformazione 3-D direttamente alla griglia spaziale più risoluta possibile. Inoltre, in conclusione, vengono menzionate anche alcune interessanti applicazioni SAR satellitari in ambito di prevenzione ed analisi di particolari fenomeni naturali e indotti dall'uomo.
Multi-temporal SAR interferometric (Mt-InSAR) techniques are nowadays mature tools to measure the temporal evolution of the Earth’s surface with millimetric accuracy. The reliability of crustal measurements is closely related to the goodness of the used Mt-InSAR algorithms in isolating the deformation-related signal from the overall signal, and this becomes increasingly complex as the noise levels of each interferogram increase. Canonical techniques are highly reliable in monitoring the displacement evolution of targets that are found to be largely stable or coherent over the entire period of analysis. Otherwise, when the scatterers are particularly affected by decorrelation problems, the obtained deformation estimates turn out to be corrupted and unreliable. Thus, there is a strong demand for new advanced Mt-InSAR processors that can provide accurate estimates of crustal deformation even in scenarios with more or less severe decorrelation problems. This thesis work focuses on the study of multi-temporal InSAR techniques applicable in both satellite and terrestrial case. Specifically, the canonical Mt-InSAR multigrid techniques for analyzing targets at the finest resolution grid will be discussed extensively highlighting their criticality in medium to low coherence areas, and in this context an innovative technique is proposed to better operate in decorrelated environments. The new method relies on efficient phase-unwrapping (PhU) operations performed at the native spatial scales. In particular, a set of multi-look (ML) interferograms is first unwrapped using conventional (or advanced) PhU algorithms at the regional scale. Subsequently, ML unwrapped interferograms are used to facilitate the PhU operations performed at the local scale (single-look). Specifically, the unwrapped multi-look interferograms are resampled to the single-look grid and modulo-2π subtracted to the single-look interferograms. These phase residuals are then unwrapped and added back to the multi-look resampled interferograms. To accomplish these operations, at variance with alternative multiscale methods, no (linear/nonlinear) models are used to fit the spatial high-pass phase residuals. Finally, the unwrapped single-look interferograms are properly inverted to retrieve the ground displacement time series using any small baseline (SB)-oriented multitemporal InSAR tool. Experimental results are performed by processing a set of SAR data acquired by the X-band COSMO-SkyMed sensor over the coastal area of Shanghai, China. Then, the focusing moves on the Weighted Least-squares (WLS) techniques applied within the InSAR framework for improving the performance of the phase unwrapping operations as well as for better conveying the inversion of sequences of unwrapped interferograms to generate ground displacement maps. In both cases, the identification of low-coherent areas, where the standard deviation of the phase is high, is requested. Therefore, a WLS method that extends the usability of the Mt-InSAR Small BAseline Subset (SBAS) algorithm in regions with medium-to-low coherence is presented. In particular, the proposed method relies on the adaptive selection and exploitation, pixel-by-pixel, of the medium-to-high coherent interferograms, only, so as to discard the noisy phase measurements. The selected interferometric phase values are then inverted by solving a WLS optimization problem. Noteworthy, the adopted, pixel-dependent selection of the “good” interferograms to be inverted may lead the available SAR data to be grouped into several disjointed subsets, which are then connected, exploiting the Weighted Singular Value Decomposition (WSVD) method. However, in some critical noisy regions, it may also happen that discarding of the incoherent interferograms may lead to rejecting some SAR acquisitions from the generated ground displacement time-series, at the cost of the reduced temporal sampling of the data measurements. Thus, variable-length ground displacement time-series are generated. The presented experiments have been carried out by applying the developed technique to a SAR dataset acquired by the COSMO-SkyMed (CSK) sensors over the Basilicata region, Southern Italy. In the continuation of the thesis work, the properties characterizing the phase non-closure of multi-look SAR interferograms are explored. Precisely, we study the implications of multi-look phase time incongruences on the generation of ground displacement time-series through SB Mt-InSAR methods. Our research clarifies how these phase inconsistencies can propagate through a time-redundant network of SB interferograms and contribute, along with PhU errors, to the quality of the generated ground displacement products. Moreover, we analyze the effects of short-lived phase bias signals that could happen in sequences of short baseline interferograms and propose a strategy for their mitigation. The developed methods have been tested using both simulated and real SAR data. The latter were collected by the Sentinel-1A/B (C-band) sensors over the study areas of Nevada state, U.S., and Sicily Island, Italy. After the development of algorithms for the satellite part, the work veers to ground-based SAR (GB-SAR) sensors. In this field, we propose a method for estimating and compensating the atmospheric phase screen (APS) in sets of SAR interferograms generated with a GB-SAR instrument. We address the presented approach’s physical, statistical, and mathematical framework by discussing its potential and limitations. In contrast with other existing algorithms that estimate the APS from the unwrapped phase signals, our methodology is based on the straightforward analysis of the wrapped phases, directly. Therefore, the method is not affected by any potential phase unwrapping mistake, and it is suitable for Mt-InSAR applications. The effects of the local topography, the decorrelation noise, and the ground deformation on the APS estimates are deeply studied. Experiments performed on simulated and real GB-SAR InSAR data corroborate the validity of the theory. In particular, the simulated results show that the method is beneficial in zones with medium-to-high topographic slopes (e.g., for Alpine and mountainous regions). Further, an interferometric SAR application for the study of three-dimensional (3-D) deformation through the joint and integrated use of satellite and ground SAR data is presented. More precisely, the interferometric data-combining technique exploits the innovative Mt-InSAR algorithms mentioned above, and allows obtaining 3-D mean displacement velocity maps at the finest spatial grid among the available data. In conclusion, also some interested satellite SAR applications in prevention and analysis of particular natural and human-induced disasters are given.

Interferometric synthetic aperture radar (InSAR) has been increasingly used to extract information about the earth‟s surface by exploiting the phase difference between two complex radar signals. Some significant application fields that utilize InSAR techniques are digital elevation model (DEM) generation, land use classification and land subsidence. In this thesis, by using ERS-1/2 tandem SAR images pairs, the potential implementations of SAR interferometry in tropical peatland forests in Central Kalimantan, Indonesia are described. Coherence was found to be a good tool for rapid assessment for burned and deforested areas. The coherence of burned forest area was increased by 0.2; whilst the minimum coherence was found to be than 0.35. However, many critical factors affect the quality of InSAR data and limit its applications, such as methods of InSAR data processing. This study emphasizes the impact of different processing and phase unwrapping techniques on DEM accuracy. Analyses of InSAR DEM accuracy indicate that DEMs with relative errors of less than 3 m root mean square error (RMSE) are possible in some regions in the former Mega Rice Project (Ex-MRP) area and could meet many objectives of a global mapping mission. Applying adaptive filtering many times with a decreasing window size has a strong impact to reduce the number of residues, which can increase the phase unwrapping efficiency and the final DEM accuracy. Furthermore, the differential SAR Interferometry (DInSAR) was examined to see if it can detect peatland subsidence accurately from October 1997 to January 2000 using 4-pass and complex interferogram combination methods. The subsidence rate of 2 cm per year is considered to be the best possible prediction for subsidence in the project area and between 53 and 83 Mt of peat carbon was lost for the same period of the study. The contribution of the maximum subsidence to the emission of CO2 was estimated to be 52 tonnes per hectare per year. These results are not reliable enough for detailed planning purposes, but they provide a basis for further work by highlighting where methodological development is needed.

Urban land cover mapping represents one of the most important remote sensing applications in the context of rapid global urbanization. In recent years, high resolution spaceborne Polarimetric Synthetic Aperture Radar (PolSAR) has been increasingly used for urban land cover/land-use mapping, since more information could be obtained in multiple polarizations and the collection of such data is less influenced by solar illumination and weather conditions.  The overall objective of this research is to develop effective methods to extract accurate and detailed urban land cover information from spaceborne PolSAR data. Six RADARSAT-2 fine-beam polarimetric SAR and three RADARSAT-2 ultra-fine beam SAR images were used. These data were acquired from June to September 2008 over the north urban-rural fringe of the Greater Toronto Area, Canada. The major landuse/land-cover classes in this area include high-density residential areas, low-density residential areas, industrial and commercial areas, construction sites, roads, streets, parks, golf courses, forests, pasture, water and two types of agricultural crops. In this research, various polarimetric SAR parameters were evaluated for urban land cover mapping. They include the parameters from Pauli, Freeman and Cloude-Pottier decompositions, coherency matrix, intensities of each polarization and their logarithms.  Both object-based and pixel-based classification approaches were investigated. Through an object-based Support Vector Machine (SVM) and a rule-based approach, efficiencies of various PolSAR features and the multitemporal data combinations were evaluated. For the pixel-based approach, a contextual Stochastic Expectation-Maximization (SEM) algorithm was proposed. With an adaptive Markov Random Field (MRF) and a modified Multiscale Pappas Adaptive Clustering (MPAC), contextual information was explored to improve the mapping results. To take full advantages of alternative PolSAR distribution models, a rule-based model selection approach was put forward in comparison with a dictionary-based approach.  Moreover, the capability of multitemporal fine-beam PolSAR data was compared with multitemporal ultra-fine beam C-HH SAR data. Texture analysis and a rule-based approach which explores the object features and the spatial relationships were applied for further improvement. Using the proposed approaches, detailed urban land-cover classes and finer urban structures could be mapped with high accuracy in contrast to most of the previous studies which have only focused on the extraction of urban extent or the mapping of very few urban classes. It is also one of the first comparisons of various PolSAR parameters for detailed urban mapping using an object-based approach. Unlike other multitemporal studies, the significance of complementary information from both ascending and descending SAR data and the temporal relationships in the data were the focus in the multitemporal analysis. Further, the proposed novel contextual analyses could effectively improve the pixel-based classification accuracy and present homogenous results with preserved shape details avoiding over-averaging. The proposed contextual SEM algorithm, which is one of the first to combine the adaptive MRF and the modified MPAC, was able to mitigate the degenerative problem in the traditional EM algorithms with fast convergence speed when dealing with many classes. This contextual SEM outperformed the contextual SVM in certain situations with regard to both accuracy and computation time. By using such a contextual algorithm, the common PolSAR data distribution models namely Wishart, G0p, Kp and KummerU were compared for detailed urban mapping in terms of both mapping accuracy and time efficiency. In the comparisons, G0p, Kp and KummerU demonstrated better performances with higher overall accuracies than Wishart. Nevertheless, the advantages of Wishart and the other models could also be effectively integrated by the proposed rule-based adaptive model selection, while limited improvement could be observed by the dictionary-based selection, which has been applied in previous studies. The use of polarimetric SAR data for identifying various urban classes was then compared with the ultra-fine-beam C-HH SAR data. The grey level co-occurrence matrix textures generated from the ultra-fine-beam C-HH SAR data were found to be more efficient than the corresponding PolSAR textures for identifying urban areas from rural areas. An object-based and pixel-based fusion approach that uses ultra-fine-beam C-HH SAR texture data with PolSAR data was developed. In contrast to many other fusion approaches that have explored pixel-based classification results to improve object-based classifications, the proposed rule-based fusion approach using the object features and contextual information was able to extract several low backscatter classes such as roads, streets and parks with reasonable accuracy.

QC 20121112

Satellite altimetry has been traditionally used in the past few decades to measure elevation of land ice, quantify changes in ice topography and infer the mass balance of large and remote areas such as the Greenland and Antarctic ice sheets. Radar altimetry is particularly well suited to this task due to its all-weather year-round capability of observing the ice surface. However, monitoring of ice caps and ice fields - bodies of ice with areas typically smaller than ~ 10,000 km2 - has proven more challenging. The large footprint of a conventional radar altimeter and coarse ground track coverage are less suited to observing comparatively small regions with complex topography. Since 2010, the European Space Agency’s CryoSat-2 satellite has been collecting ice elevation measurements over ice caps and ice fields with its novel radar altimeter. CryoSat-2’s smaller inter-track spacing provides higher density of observations compared to previous satellite altimeters. Additionally, it generates more accurate measurements because (i) the footprint size is reduced in the along-track direction by means of synthetic aperture radar processing and (ii) interferometry allows to precisely locate the the across-track angle of arrival of a reflection from the surface. Furthermore, the interferometric capabilities of CryoSat-2 allow for the processing of the delayed surface reflections after the first echo. When applied over a sloping surface, this procedure generates a swath of elevations a few km wide compared to the conventional approach returning a single elevation. In this thesis, swath processing of CryoSat-2 interferometric data is exploited to generate topographic data over ice caps and ice fields. The dense elevation field is then used to compute maps of elevation change rates at sub-kilometer resolution with the aim of quantifying ice volume change and mass balance. A number of algorithms have been developed in this work, partly or entirely, to form a complete processing chain from generating the elevation field to calculating volume and mass change. These algorithms are discussed in detail before presenting the results obtained in two selected regions: Iceland and Patagonia. Over Icelandic ice caps, the high-resolution mapping reveals complex surface elevation changes, related to climate, ice dynamics and sub-glacial, geothermal and magmatic processes. The mass balance of each of the six largest ice caps (90% of Iceland’s permanent ice cover) is calculated independently for the first time using spaceborne radar altimetry data. Between October 2010 and September 2015 Icelandic ice caps have lost a total of 5.8± 0.7 Gt a ̄1, contributing 0.016± 0.002 mm a ̄1 to eustatic sea level rise. This estimate indicates that over this period the mass balance was 40% less negative than the preceding 15 years, a fact which partly reflects the anomalous positive balance year across the Vatnaj ̈okull ice cap (~ 70% of the glaciated area) in 2014/15. Furthermore, it is demonstrated how swath processing of CryoSat-2 interferometric data allows the monitoring of glaciological processes at the catchment scale. Comparison of the geodetic estimates of mass balance against those based on in situ data shows good agreement. The thesis then investigates surface elevation change on the Northern and Southern Patagonian Ice Fields to quantify their mass balance. This area is characterized by some of the fastest flowing glaciers in the world, displaying complex interactions with the proglacial environments (including marine fjords and freshwater lakes) they often drain into. Field observations are sparse due to the inaccessibility of these ice fields and even remotely sensed data are limited, often tied to comparisons to the topography in 2000 as measured by the Shuttle Radar Topography Mission. Despite gaps in the spatial coverage, in particular due to the complex topography, CryoSat-2 swath radar altimetry provides insight into the patterns of change on the ice fields in the most recent period (2011 to 2017) and allows to independently calculate the mass balance of glaciers or catchments as small as 300 km2. The northern part of the Southern Patagonian ice field displays the strongest losses due to a combination between ice dynamics and warming temperatures. In contrast Pio XI, the largest glacier on this ice field and in South America, is advancing and gaining mass. Between April 2011 and march 2017, the two ice fields combined have lost an average of 21.29± 1.98 Gt a ̄1 (equivalent to 0.059± 0.005 mm a ̄1 eustatic sea level rise), 24% and 42% more negative when compared to the periods 2000-2012/14 and 1975-2000. In particular the Northern Patagonian ice field, responsible for one third of the mass loss, is losing mass 70% faster compared to the first decade of the 21st century. These results confirm the overall strong mass loss of the Patagonian ice fields, second only to glaciers and ice caps in Alaska and the Canadian Arctic, and higher than High Mountain Asia, which all extend over areas ~ 5-8 times larger (excluding glaciers at the periphery of the Greenland and Antarctic ice sheets).

With the advent of the first satellites for Earth Observation: Landsat-1 in July 1972 and ERS-1 in May 1991, the discipline of environmental remote sensing has become, over time, increasingly fundamental for the study of phenomena characterizing the planet Earth. The goal of environmental remote sensing is to perform detailed analyses and to monitor the temporal evolution of different physical phenomena, exploiting the mechanisms of interaction between the objects that are present in an observed scene and the electromagnetic radiation detected by sensors, placed at a distance from the scene, operating at different frequencies. The analyzed physical phenomena are those related to climate change, weather forecasts, global ocean circulation, greenhouse gas profiling, earthquakes, volcanic eruptions, soil subsidence, and the effects of rapid urbanization processes. Generally, remote sensing sensors are of two primary types: active and passive. Active sensors use their own source of electromagnetic radiation to illuminate and analyze an area of interest. An active sensor emits radiation in the direction of the area to be investigated and then detects and measures the radiation that is backscattered from the objects contained in that area. Passive sensors, on the other hand, detect natural electromagnetic radiation (e.g., from the Sun in the visible band and the Earth in the infrared and microwave bands) emitted or reflected by the object contained in the observed scene. The scientific community has dedicated many resources to developing techniques to estimate, study and analyze Earth’s geophysical parameters. These techniques differ for active and passive sensors because they depend strictly on the type of the measured physical quantity. In my P.h.D. work, inversion techniques for estimating Earth’s surface and atmosphere geophysical parameters will be addressed, emphasizing methods based on machine learning (ML). In particular, the study of cloud microphysics and the characterization of Earth’s surface changes phenomenon are the critical points of this work.

Persistent Scatterer Interferometric techniques are very powerful geodetic tools for land deformation monitoring that offer the typical advantages of the satellite remote sensing SAR (Synthetic Aperture Radar) systems : a wide coverage at a relatively high resolution. Those techniques are based on the analysis of a set of SAR images acquired over a given area. They overcome the decorrelation problem by identifying elements (in resolution cells) with a high quality returned SAR signal which remains stable in a series of interferograms. These techniques have been useful for the analysis of urban areas, where man-made objects produce good reflections that dominate over the background scattering, as well as in field areas where the density of infrastructures is more limited. Typically, PSI technique requires an approximate a priori temporal model for the detection of the deformation, even though characterizing the temporal evolution of a deformation is commonly one of the objectives of any study.This work is focused on a particular PSI technique, which is named Stable Point Network (SPN) and that it has been completely developed by Altamira Information in 2003. The work concisely outlines the main characteristics of this technique, and describes its main products: average deformation maps, deformation time series of the measured points, and the so-called maps of the residual topographic error, which are used to precisely geocode the PSI products. The main objectives of this PhD are the identification and analysis of the drawbacks of this processing chain, and the development of new tools and methodologies in order to overcome them. First, the performances of the SPN technique are examined and illustrated by means of practical cases (based on real test sites made with data coming from different sensors) and simulated scenarios.Thus, the main drawbacks of the technique are identified and discussed, such as the lack of automatic quality control parameters, the evaluation of the input data quality, the selection of good points for the measurements and the use of a functional model to unwrap the phases based on a linear deformation trend in time. Then, different enhancements are proposed. In particular, the automatic quality control of the coregistration procedure has been introduced through the analysis of the inter-pixel position of some natural point targets-like pixels identified within the images. The enhancements in the selection of the final points of measurements (the final PSI map) come by means of the analysis of the SAR signal signature of the strong targets presented within the image, in order to select only the center of the main lobe as point of measurement. The introduction of robustness within some critical steps of the technique is done by means of the analysis of the rotational of the estimates in close loops within a network of relative measurements, and by means of the implementation of a different integration methodology, which can be ran in parallel in order to compare it with the classical one. Finally, the main drawback of the technique, the use of a linear model for the detection of ground deformations, is addressed with the development of a new fitting methodology which allows possible change of trends within the analyzed time span. All those enhancements are evaluated with the use of real examples of applications and with simulated data. In particular, the new methodology for detecting non-linear ground deformations has been tested in the city of Paris, where a large stacking of ERS1/2 and ENVISAT SAR images are available. Those images are covering a very large time period of analysis at where some known non-linear ground deformations where occurring

Several studies suggest that deep convection that penetrates the tropical tropopause layer may influence the long-term trends in lower stratospheric water vapor. This thesis investigates the relationship between penetrating deep convection and lower stratospheric water vapor variability using historical infrared (IR) observations. However, since infrared observations do not directly resolve cloud vertical structure and cloud top height, and there has been some debate on their usefulness to characterize penetrating deep convective clouds, CloudSat/Calipso and Aqua MODIS observations are first combined to understand how to best interpret IR observations of penetrating tops. The major findings of the combined CloudSat/Calipso and Aqua MODIS analysis show that penetrating deep convection predominantly occur in the western tropical Pacific Ocean. This finding is consistent with IR studies but is in contrast to previous radar studies where penetrating deep convective clouds predominantly occur over land regions such as equatorial Africa. Estimates on the areal extent of penetrating deep convection show that when using IR observations with a horizontal resolution of 10 km, about two thirds of the events are large enough to be detected. Evaluation of two different IR detection schemes, which includes cold cloud features/pixels and positive brightness temperature differences (+BTD), show that neither schemes completely separate between penetrating deep convection and other types of high clouds. However, the predominant fraction of +BTD distributions and cold cloud features/pixels ≤ 210 K is due to the coldest and highest penetrating tops as inferred from collocated IR and radar/lidar observations. This result is in contrast to previous studies that suggest the majority of cold cloud features/pixels ≤ 210 K are cirrus/anvil cloud fractions that coexist with deep convective clouds. Observations also show that a sufficient fraction of penetrating deep convective cloud tops occur in the extratropics. This provides evidence that penetrating deep convection should be documented as a pathway of stratospheric-tropospheric exchange within the extratropical region. Since the cold cloud feature/pixel ≤ 210 K approach was found to be a sufficient method to detect penetrating deep convection it was used to develop a climatology of the coldest penetrating deep convective clouds from GridSat observations covering years 1998-2008. The highest frequencies of the coldest penetrating deep convective clouds consistently occur in the western-central Pacific and Indian Ocean. Monthly frequency anomalies in penetrating deep convection were evaluated against monthly anomalies in lower stratospheric water vapor at 82 mb and show higher correlations for the western-central Pacific regions in comparison to the tropics. At a lag of 3 months, the combined western-central Pacific had a small but significant anticorrelation, where the largest amount of variance explained by the combined western-central Pacific region was 8.25%. In conjunction with anomalies in the 82 mb water vapor mixing ratios, decreasing trends for the 1998-2008 period were also observed for tropics, the western Pacific and Indian Ocean. Although none of these trends were significant at the 95% confidence level, decreases in the frequency of penetrating deep convection over the 1998-2008 shows evidence that could explain in part some of the 82 mb lower stratospheric water vapor variability.

博士
國立中央大學
太空科學研究所
98
The new generation spaceborne SAR are more complicated within radar interferometry application due to more flexible operation as multi-beam and multi-polarization like as ENVISAT、ALOS/PALSAR、Radarsat-2 and TerraSAR-X etc. The prevailing complex geological condition of Taiwan have drawn considerable attention from various geological communities to produce various natural hazards at different scales. Located in the tropical/subtropical zone of the Pacific Rim, its ecological and rugged mountainous properties are environmentally sensitive making monitoring and observations especially difficult because of the high population density. The main limitation of 3D deformation measurements made with interferometry is that interferogram gives only give the line-of-sight direction is measured. In this study proposes a new approach using the cost function to integrate of multi-modal spaceborne radar interferograms within multi-beam or both ascending and descending. Minimized the cost function and extracted the subsidence deformation map. In the meantime, we considered the deformation type and proposed the temporal deformation models with minimized cost function for long-term interferometric observation. The study case used the period of observations dated from Dec. 2006 to Jan. 2009 with pairs from C-band ASAR/ENVISAT and L-band PALSAR/ALOS data sets were used to detect and track the deformations. With both ascending and descending orbits, the manner further improved the subsidence mapping. That result is better comparisons with the precision leveling survey in 2005. Both ascending and descending mapping results indicate that the maximum subsidence rates were about 7 cm/yr (around epicenter) in that period. Another topic within deformation model within the long-term observation to find the temporal deformation profile such as Yuanlin subsidence event before ChiChi earthquake and Tainan tableland uplift.

Thesis (M.S.)--University of Wisconsin--Madison, 1998.
Typescript. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 91-94).

L’ambito scientifico dell’attività di ricerca svolta riguarda lo sviluppo e l’analisi di tecniche innovative per l’elaborazione di segnali a banda larga, utilizzando le potenzialità che sistemi multo-canale e/o multi - sensore forniscono. Nello specifico l’obiettivo è rappresentato dallo studio di funzionalità avanzate per radar aviotrasportati e spaziali di nuova generazione, tra cui la cancellazione di interferenze elettromagnetiche (e.m.) a banda larga e la capacità di imaging di target ad alta risoluzione. Il primo argomento trattato riguarda l’elaborazione di dati radar ad apertura sintetica multicanale (M-SAR), allo scopo di difendere il sistema da interferenze elettromagnetiche a larga banda (SAR-ECCM) preservando le normali capacità di imaging. I SAR sono sensori attivi in grado di produrre, attraverso tecniche di scansione, “mappe” di parametri radiativi ad alta risoluzione, grazie all’utilizzo di bande elevate; a tal fine sfruttano il backscattering dalla superficie, che subisce un’attenuazione a due vie, quindi è di estrema importanza che sistemi di questo tipo siano in grado di proteggersi dalle interferenze elettromagnetiche (intenzionali, dovute al Jamming, oppure dovute alle spurie di altri sistemi a radiofrequenza, in altre parole Radio Frequency Interference - RFI), che subiscono attenuazioni a una via e possono essere caratterizzate da potenze molto più elevate di quelle del segnale utile, anche se ricevute dai lobi laterali del pattern di antenna. L’utilizzo di tecniche di nulling di antenna ottimizzate per lavorare a banda stretta non può garantire la protezione da interferenze di tipo Noise-Like a banda larga, quindi sembra di grande interesse lo sviluppo e lo studio di prestazioni di tecniche apposite, che prevedano l’aumento di gradi di libertà a disposizione, sia spaziali, nel senso di un numero maggiore di canali riceventi ed eventualmente introducendo vincoli aggiuntivi, sia temporali, in altre parole considerando la possibilità di elaborare più campioni di segnale per ciascun canale ricevente. Il secondo argomento affrontato riguarda l’elaborazione di dati radar ad apertura sintetica inversa (ISAR) al fine di aumentare la risoluzione cross-range dell’immagine quando siano disponibili le acquisizioni, monostatiche o bistatiche, di una molteplicità di sensori aviotrasportati. Come è noto l’ISAR fornisce immagini di target ad alta risoluzione sfruttando le caratteristiche del moto dei bersagli rispetto a un sensore, posto su di una piattaforma quasi stazionaria. Il principale svantaggio di questo tipo di processing risiede nel fatto che le prestazioni raggiungibili in termini di risoluzione cross-range dipendono dalle caratteristiche intrinseche del moto del bersaglio, piuttosto che da parametri di sistema; mentre la risoluzione in slant-range è determinata una volta che la banda e la forma d’onda trasmessa sono state decise, non c’è nessun modo di assegnare un valore desiderato di risoluzione cross-range. In casi particolari di bersagli con piccole componenti di movimento il valore di risoluzione di cross-range ottenuto può essere insufficiente, se si pensa che le immagini ISAR generalmente sono usate nelle procedure di Non Cooperative Target Recognition (NCTR). Per contrastare questo effetto è possibile derivare delle procedure per combinare in modo coerente le acquisizioni di un insieme di sensori trasportati da piattaforme che volano in formazione; in questo modo è possibile sintetizzare un’apertura equivalente maggiore, quindi un valore di risoluzione migliore che se si considerasse un unico sensore.

The Microwave Remote Sensing Laboratory (MIRSL) at the University of Massachusetts, in collaboration with The Jet Propulsion Laboratory, has developed a new radar designed to facilitate measurements of the radiative properties of clouds. Details of this new design are described with particular emphasis on improvements from previous systems. This radar system was used to collect cloud data during three experiment campaigns. During these experiments, reflectivity data from all prevalent cloud types were collected over a wide range of geographical locations. The observations were then used to examine the reflectivity vs. altitude and temperature characteristics and layer structure for various types of cloud complexes. To increase the representation of tropical cirrus clouds in the composite data set, the airborne data was supplemented with data from MCTEX collected by the UMass CPRS radar. All observations were classified into four classes of clouds and histograms of altitude and temperature vs. reflectivity were used to demonstrate the reflectivity characteristics of various clouds types. Statistics of layer base and top altitudes, thickness and number of layers were also computed. Also, the relationship between cirrus cloud thickness, reflectivity and ice water path (IWP) is examined. The data sets from the four experiments were then used to address performance issues for a spaceborne radar. The problem of cloud detectability is discussed and an analysis of the ice water content (IWC) estimation error resulting from spatial inhomogeneity is presented. The fraction of clouds thinner than one range gate of the CloudSat radar was found to be 14% for all data sets combined. The data sets are used to simulate satellite radar pixels and the distributions of errors in IWC estimates due to inhomogeneity are calculated. On average, 40% of the pixels were partially filled and the relative IWC error was 24%. The distribution of the relative errors vs. IWC values indicated that the largest relative error occurred at vary small values of IWC and the mean error for all experiments was only 15% for IWC values larger than 10 –3 gm3.

Thesis (M.S.)--University of Wisconsin--Madison, 1996.
Typescript. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 127-137).