ESTIMATION OF DATA MEMORY CAPACITY FOR CIRCULARLY POLARIZED SYNTHETIC APERTURE RADAR ONBOARD UNMANNED AERIAL VEHICLE PLATFORM (CP-SAR UAV)

Previously only linear polarization is widely used in the Synthetic Aperture Radar(SAR) system onboard spaceborne and airborne platforms. In such linearly polarized SAR(LP-SAR) systems, Faraday rotation in the ionosphere and platform posture will contribute tothe system noise. Therefore to improve this situation, currently a novel Circularly PolarizedSynthetic Aperture Radar (CP-SAR) sensor is developed in Microwave Remote SensingLaboratory, Chiba University. Moreover, from this research, a new backscattering data basedon circularly polarized wave in the remote sensing field can be obtained. As an early stage ofthe development of this CP-SAR sensor, we built an Unmanned Aerial Vehicle (UAV)platform for testing CP-SAR sensor capabilities. In this paper, we describe the novel CP-SARsensor and the method to design CP-SAR UAV especially in estimating the requirement ofdata memory capacity. Also a smaller antenna is possible to be implemented since the 3-dBaxial ratio on antenna characteristic becomes the main parameter in this new CP-SARtechnique. Hence, a compact CP-SAR sensor onboard a small and low cost spaceborneplatform yielding a high accuracy SAR image data can be realized in the near future

Measuring velocities of a surge type glacier with SAR interferometry using ALOS-2 data

In recent years, in-situ measurements on Kongsvegen, a surge-type glacier located in the Kongsfjorden area, have showed an acceleration in the flow speeds of the glacier. This could indicate the onset of a surging event, which presents the opportunity to study the dynamics of a glacier surge using remote sensing techniques with in-situ data for reference. Synthetic aperture radar (SAR) is well suited for this, as it does not rely on the sun for illumination and is not obstructed by clouds. In addition, SAR can be used to measure displacement with high accuracy and resolution through the use of interferometric SAR (InSAR). This study investigates the acceleration of Kongsvegen using InSAR, MAI and offset tracking. Velocity measurements from the combination DInSAR - MAI are then compared to in-situ data as well as the offset tracking measurements. For image pairs where InSAR measurements are not possible due to phase decorrelation, offset tracking is attempted as a back-up. Data from 2015, 2018 and 2019 was available, and the evolution of flow speeds over time could therefore be evaluated. The image pairs from 2018-2019 were acquired with 14 days separation in time, while the 2015 image pairs were acquired with 28 and 42 days separation. Due to the longer separation in time, the 2015 image pairs decorrelated in time. In addition, a pair acquired in the summer of 2018 decorrelated as a result of surface melting on the glaciers. Therefore only 3 of the total 8 pairs available were suited for interferometric analysis. For the image pairs from 2018-2019, the InSAR measurements were in good agreement with the in-situ data, as they also indicated an acceleration of the flow speeds on Kongsvegen. The offset tracking results on these pairs overestimated the velocity magnitudes, but also showed an increase in time. Similar to the InSAR estimates, the offset tracking failed to produce reasonable results on the 2015 image pairs, likely because of the large temporal baseline and lack of surface features on Kongsvegen. Overall, InSAR could be used to measure flow speeds on Kongsvegen successfully, but more data with a short temporal baseline is needed for an in-depth analysis

The Compact Polarimetry Alternative for Spaceborne SAR at Low Frequency

International audienceIn spaceborne synthetic aperture radar (SAR), a single-polarization on-transmit offers twice the swath width compared to full polarization. This is linked to SAR system design issues, and, without getting into the technical details deserving by themselves a full paper, we can just mention the swath characteristics of ALOS PALSAR (the Advanced Land Observing Satellite, Phased Array L-Band Synthetic Aperture Radar), reducing from 70 km for the dual-pol mode to 30 km for the full polarization mode. The reduced coverage in the full polarization mode has a harmful impact on the revisit time, which is always a major drive for the Earth-observing community. The options chosen up to now for dual-pol system designs (or single-polarization on-transmit) rely on a linear polarization on-transmit [either horizontal (H) or vertical (V)], with two orthogonal polarizations on-receive. Souyris and Raney in earlier papers proposed more pertinent alternatives for the selection of the transmit polarization leading to a better characterization of the scattering mechanisms. In this paper, the analysis is pursued in more depth by including the effect of the ionosphere on the wave propagation and extending the applications to polarimetric interferometry SAR (PolInSAR). A compact mode is developed where the transmit polarization is circular, whereas the only constraint on the two receiving polarizations is independence. Indeed, the choice of the polarizations of the two receive channels does not matter, as any polarization on-receive can be synthesized from these two measurements. This is, however, not the case for the unique transmit polarization. At a low frequency, where the ionosphere has a significant effect, the circular transmit polarization is the only sensible option, as it provides an effective constant polarization as seen by the scattering surface. This is an essential condition for a meaningful multitemporal analysis. Both the polarimetric SAR applications and the PolInSAR applications in the context of this compact polarimetry (CP) mode are explored. A pseudocovariance matrix can be reconstructed following Souyris' proposed approach for distributed targets and is shown to be very similar to the full polarimetric (FP) covariance matrix. The reconstruction of the cross-polarized Sigma0 is shown to be reliable and to have very low sensitivity to Faraday rotation. A PolInSAR vegetation height inversion for P-band is presented and applied to the CP data with a level of performance that is similar to the one derived from FP (a 1.2-m root-mean-square height error on the ONERA Airborne radar (RAMSES) data over the Landes Forest). A procedure is developed to correct for the ionospheric effects for the PolInSAR acquisition in the FP or CP mode and is assessed on the data simulated from an airborne acquisition. The results demonstrate that the technique is efficient and robust. The calibration of CP data is identified as an important challenge to be solved, and some clues are provided to address the problem

Advanced machine learning algorithms for Canadian wetland mapping using polarimetric synthetic aperture radar (PolSAR) and optical imagery

Wetlands are complex land cover ecosystems that represent a wide range of biophysical conditions. They are one of the most productive ecosystems and provide several important environmental functionalities. As such, wetland mapping and monitoring using cost- and time-efficient approaches are of great interest for sustainable management and resource assessment. In this regard, satellite remote sensing data are greatly beneficial, as they capture a synoptic and multi-temporal view of landscapes. The ability to extract useful information from satellite imagery greatly affects the accuracy and reliability of the final products. This is of particular concern for mapping complex land cover ecosystems, such as wetlands, where complex, heterogeneous, and fragmented landscape results in similar backscatter/spectral signatures of land cover classes in satellite images. Accordingly, the overarching purpose of this thesis is to contribute to existing methodologies of wetland classification by proposing and developing several new techniques based on advanced remote sensing tools and optical and Synthetic Aperture Radar (SAR) imagery. Specifically, the importance of employing an efficient speckle reduction method for polarimetric SAR (PolSAR) image processing is discussed and a new speckle reduction technique is proposed. Two novel techniques are also introduced for improving the accuracy of wetland classification. In particular, a new hierarchical classification algorithm using multi-frequency SAR data is proposed that discriminates wetland classes in three steps depending on their complexity and similarity. The experimental results reveal that the proposed method is advantageous for mapping complex land cover ecosystems compared to single stream classification approaches, which have been extensively used in the literature. Furthermore, a new feature weighting approach is proposed based on the statistical and physical characteristics of PolSAR data to improve the discrimination capability of input features prior to incorporating them into the classification scheme. This study also demonstrates the transferability of existing classification algorithms, which have been developed based on RADARSAT-2 imagery, to compact polarimetry SAR data that will be collected by the upcoming RADARSAT Constellation Mission (RCM). The capability of several well-known deep Convolutional Neural Network (CNN) architectures currently employed in computer vision is first introduced in this thesis for classification of wetland complexes using multispectral remote sensing data. Finally, this research results in the first provincial-scale wetland inventory maps of Newfoundland and Labrador using the Google Earth Engine (GEE) cloud computing resources and open access Earth Observation (EO) collected by the Copernicus Sentinel missions. Overall, the methodologies proposed in this thesis address fundamental limitations/challenges of wetland mapping using remote sensing data, which have been ignored in the literature. These challenges include the backscattering/spectrally similar signature of wetland classes, insufficient classification accuracy of wetland classes, and limitations of wetland mapping on large scales. In addition to the capabilities of the proposed methods for mapping wetland complexes, the use of these developed techniques for classifying other complex land cover types beyond wetlands, such as sea ice and crop ecosystems, offers a potential avenue for further research

L’utilisation de la polarimétrie radar et de la décomposition de Touzi pour la caractérisation et la classification des physionomies végétales des milieux humides : le cas du Lac Saint-Pierre

Les milieux humides remplissent plusieurs fonctions écologiques d’importance et contribuent à la biodiversité de la faune et de la flore. Même s’il existe une reconnaissance croissante sur l’importante de protéger ces milieux, il n’en demeure pas moins que leur intégrité est encore menacée par la pression des activités humaines. L’inventaire et le suivi systématique des milieux humides constituent une nécessité et la télédétection est le seul moyen réaliste d’atteindre ce but. L’objectif de cette thèse consiste à contribuer et à améliorer la caractérisation des milieux humides en utilisant des données satellites acquises par des radars polarimétriques en bande L (ALOS-PALSAR) et C (RADARSAT-2). Cette thèse se fonde sur deux hypothèses (chap. 1). La première hypothèse stipule que les classes de physionomies végétales, basées sur la structure des végétaux, sont plus appropriées que les classes d’espèces végétales car mieux adaptées au contenu informationnel des images radar polarimétriques. La seconde hypothèse stipule que les algorithmes de décompositions polarimétriques permettent une extraction optimale de l’information polarimétrique comparativement à une approche multipolarisée basée sur les canaux de polarisation HH, HV et VV (chap. 3). En particulier, l’apport de la décomposition incohérente de Touzi pour l’inventaire et le suivi de milieux humides est examiné en détail. Cette décomposition permet de caractériser le type de diffusion, la phase, l’orientation, la symétrie, le degré de polarisation et la puissance rétrodiffusée d’une cible à l’aide d’une série de paramètres extraits d’une analyse des vecteurs et des valeurs propres de la matrice de cohérence. La région du lac Saint-Pierre a été sélectionnée comme site d’étude étant donné la grande diversité de ses milieux humides qui y couvrent plus de 20 000 ha. L’un des défis posés par cette thèse consiste au fait qu’il n’existe pas de système standard énumérant l’ensemble possible des classes physionomiques ni d’indications précises quant à leurs caractéristiques et dimensions. Une grande attention a donc été portée à la création de ces classes par recoupement de sources de données diverses et plus de 50 espèces végétales ont été regroupées en 9 classes physionomiques (chap. 7, 8 et 9). Plusieurs analyses sont proposées pour valider les hypothèses de cette thèse (chap. 9). Des analyses de sensibilité par diffusiogramme sont utilisées pour étudier les caractéristiques et la dispersion des physionomies végétales dans différents espaces constitués de paramètres polarimétriques ou canaux de polarisation (chap. 10 et 12). Des séries temporelles d’images RADARSAT-2 sont utilisées pour approfondir la compréhension de l’évolution saisonnière des physionomies végétales (chap. 12). L’algorithme de la divergence transformée est utilisé pour quantifier la séparabilité entre les classes physionomiques et pour identifier le ou les paramètres ayant le plus contribué(s) à leur séparabilité (chap. 11 et 13). Des classifications sont aussi proposées et les résultats comparés à une carte existante des milieux humide du lac Saint-Pierre (14). Finalement, une analyse du potentiel des paramètres polarimétrique en bande C et L est proposé pour le suivi de l’hydrologie des tourbières (chap. 15 et 16). Les analyses de sensibilité montrent que les paramètres de la 1re composante, relatifs à la portion dominante (polarisée) du signal, sont suffisants pour une caractérisation générale des physionomies végétales. Les paramètres des 2e et 3e composantes sont cependant nécessaires pour obtenir de meilleures séparabilités entre les classes (chap. 11 et 13) et une meilleure discrimination entre milieux humides et milieux secs (chap. 14). Cette thèse montre qu’il est préférable de considérer individuellement les paramètres des 1re, 2e et 3e composantes plutôt que leur somme pondérée par leurs valeurs propres respectives (chap. 10 et 12). Cette thèse examine également la complémentarité entre les paramètres de structure et ceux relatifs à la puissance rétrodiffusée, souvent ignorée et normalisée par la plupart des décompositions polarimétriques. La dimension temporelle (saisonnière) est essentielle pour la caractérisation et la classification des physionomies végétales (chap. 12, 13 et 14). Des images acquises au printemps (avril et mai) sont nécessaires pour discriminer les milieux secs des milieux humides alors que des images acquises en été (juillet et août) sont nécessaires pour raffiner la classification des physionomies végétales. Un arbre hiérarchique de classification développé dans cette thèse constitue une synthèse des connaissances acquises (chap. 14). À l’aide d’un nombre relativement réduit de paramètres polarimétriques et de règles de décisions simples, il est possible d’identifier, entre autres, trois classes de bas marais et de discriminer avec succès les hauts marais herbacés des autres classes physionomiques sans avoir recours à des sources de données auxiliaires. Les résultats obtenus sont comparables à ceux provenant d’une classification supervisée utilisant deux images Landsat-5 avec une exactitude globale de 77.3% et 79.0% respectivement. Diverses classifications utilisant la machine à vecteurs de support (SVM) permettent de reproduire les résultats obtenus avec l’arbre hiérarchique de classification. L’exploitation d’une plus forte dimensionalitée par le SVM, avec une précision globale maximale de 79.1%, ne permet cependant pas d’obtenir des résultats significativement meilleurs. Finalement, la phase de la décomposition de Touzi apparaît être le seul paramètre (en bande L) sensible aux variations du niveau d’eau sous la surface des tourbières ouvertes (chap. 16). Ce paramètre offre donc un grand potentiel pour le suivi de l’hydrologie des tourbières comparativement à la différence de phase entre les canaux HH et VV. Cette thèse démontre que les paramètres de la décomposition de Touzi permettent une meilleure caractérisation, de meilleures séparabilités et de meilleures classifications des physionomies végétales des milieux humides que les canaux de polarisation HH, HV et VV. Le regroupement des espèces végétales en classes physionomiques est un concept valable. Mais certaines espèces végétales partageant une physionomie similaire, mais occupant un milieu différent (haut vs bas marais), ont cependant présenté des différences significatives quant aux propriétés de leur rétrodiffusion.Wetlands fill many important ecological functions and contribute to the biodiversity of fauna and flora. Although there is a growing recognition of the importance to protect these areas, it remains that their integrity is still threatened by the pressure of human activities. The inventory and the systematic monitoring of wetlands are a necessity and remote sensing is the only realistic way to achieve this goal. The primary objective of this thesis is to contribute and improve the wetland characterization using satellite polarimetric data acquired in L (ALOS-PALSAR) and C (RADARSAT-2) band. This thesis is based on two hypotheses (Ch. 1). The first hypothesis stipulate that classes of plant physiognomies, based on plant structure, are more appropriate than classes of plant species because they are best adapted to the information content of polarimetric radar data. The second hypothesis states that polarimetric decomposition algorithms allow an optimal extraction of polarimetric information compared to a multi-polarized approach based on the HH, HV and VV channels (Ch. 3). In particular, the contribution of the incoherent Touzi decomposition for the inventory and monitoring of wetlands is examined in detail. This decomposition allows the characterization of the scattering type, its phase, orientation, symmetry, degree of polarization and the backscattered power of a target with a series of parameters extracted from an analysis of the coherency matrix eigenvectors and eigenvalues. The lake Saint-Pierre region was chosen as the study site because of the great diversity of its wetlands that are covering more than 20 000 ha. One of the challenges posed by this thesis is that there is neither a standard system enumerating all the possible physiognomic classes nor an accurate description of their characteristics and dimensions. Special attention was given to the creation of these classes by combining several data sources and more than 50 plant species were grouped into nine physiognomic classes (Ch. 7, 8 and 9). Several analyzes are proposed to validate the hypotheses of this thesis (Ch. 9). Sensitivity analysis using scatter plots are performs to study the characteristics and dispersion of plant physiognomic classes in various features space consisting of polarimetric parameters or polarization channels (Ch. 10 and 12). Time series of made of RADARSAT-2 images are used to deepen the understanding of the seasonal evolution of plant physiognomies (Ch. 12). The transformed divergence algorithm is used to quantify the separability between physiognomic classes and to identify the parameters (s) that contribute the most to their separability (Ch. 11 and 13). Classifications are also proposed and the results compared to an existing map of the lake Saint-Pierre wetlands (Ch. 14). Finally, an analysis of the potential of polarimetric parameters in C and L-band is proposed for the monitoring of peatlands hydrology (Ch. 15 and 16). Sensitivity analyses show that the parameters of the 1st component, relative to the dominant (polarized) part of the signal, are sufficient for a general characterization of plant physiognomies. The parameters of the second and third components are, however, needed for better class separability (Ch. 11 and 13) and a better discrimination between wetlands and uplands (Ch. 14). This thesis shows that it is preferable to consider individually the parameters of the 1st, 2nd and 3rd components rather than their weighted sum by their respective eigenvalues (Ch. 10 and 12). This thesis also examines the complementarity between the structural parameters and those related to the backscattered power, often ignored and normalized by most polarimetric decomposition. The temporal (seasonal) dimension is essential for the characterization and classification of plant physiognomies (Ch. 12, 13 and 14). Images acquired in spring (April and May) are needed to discriminate between upland and wetlands while images acquired in summer (July and August) are needed to refine the classifications of plant physiognomies. A hierarchical classification tree developed in this thesis represents a synthesis of the acquired knowledge (Chapter 14). Using a relatively small number of polarimetric parameters and simple decision rules, it is possible to identify, among other, three low marshes classes and to discriminate with success herbaceous high marshes from other physiognomic classes without using ancillary data source. The results obtained are comparable to those from a supervised classification using two Landsat-5 images with an overall accuracy of 77.3% and 79.0% respectively. Various classifications using the support vector machine (SVM) can reproduce the results obtained with the hierarchical classification tree. But the possible exploitation by the SVM of a higher dimensionality, with a maximum overall accuracy of 79.1%, does not allow however to achieve significantly better results. Finally, the phase of the Touzi decomposition appears to be the only parameter (in L-band) sensitive to changes in water level beneath the peat surface (Ch. 16). Therefore, this parameter offer a great potential for peatlands hydrology monitoring compared to the HH-VV phase difference. This thesis demonstrates that the Touzi decomposition parameters allow a better characterization, better separability and better classifications of wetlands plant physiognomic classes than HH, HV and VV polarization channels. The grouping of plant species into physiognomic classes is a valid concept. However, some plant species sharing a similar physiognomy, but occupying a different environment (high vs. low marshes), have presented significant differences in their scattering properties