Polarimetric Response of Rice Fields at C-Band: Analysis and Phenology Retrieval

A set of ten RADARSAT-2 images acquired in fully polarimetric mode over a test site with rice fields in Seville, Spain, has been analyzed to extract the main features of the C-band radar backscatter as a function of rice phenology. After observing the evolutions versus phenology of different polarimetric observables and explaining their behavior in terms of scattering mechanisms present in the scene, a simple retrieval approach has been proposed. This algorithm is based on three polarimetric observables and provides estimates from a set of four relevant intervals of phenological stages. The validation against ground data, carried out at parcel level for a set of six stands and up to nine dates per stand, provides a 96% rate of coincidence. Moreover, an equivalent compact-pol retrieval algorithm has been also proposed and validated, providing the same performance at parcel level. In all cases, the inversion is carried out by exploiting a single satellite acquisition, without any other auxiliary information.This work was supported by the Spanish Ministry of Economy and Competitiveness (MINECO) and European Union FEDER under Project TEC2011-28201-C02-02

Polarimetric Synthetic Aperture Radar

This open access book focuses on the practical application of electromagnetic polarimetry principles in Earth remote sensing with an educational purpose. In the last decade, the operations from fully polarimetric synthetic aperture radar such as the Japanese ALOS/PalSAR, the Canadian Radarsat-2 and the German TerraSAR-X and their easy data access for scientific use have developed further the research and data applications at L,C and X band. As a consequence, the wider distribution of polarimetric data sets across the remote sensing community boosted activity and development in polarimetric SAR applications, also in view of future missions. Numerous experiments with real data from spaceborne platforms are shown, with the aim of giving an up-to-date and complete treatment of the unique benefits of fully polarimetric synthetic aperture radar data in five different domains: forest, agriculture, cryosphere, urban and oceans

Spatial Modeling of Compact Polarimetric Synthetic Aperture Radar Imagery

The RADARSAT Constellation Mission (RCM) utilizes compact polarimetric (CP) mode to provide data with varying resolutions, supporting a wide range of applications including oil spill detection, sea ice mapping, and land cover analysis. However, the complexity and variability of CP data, influenced by factors such as weather conditions and satellite infrastructure, introduce signature ambiguity. This ambiguity poses challenges in accurate object classification, reducing discriminability and increasing uncertainty. To address these challenges, this thesis introduces tailored spatial models in CP SAR imagery through the utilization of machine learning techniques. Firstly, to enhance oil spill monitoring, a novel conditional random field (CRF) is introduced. The CRF model leverages the statistical properties of CP SAR data and exploits similarities in labels and features among neighboring pixels to effectively model spatial interactions. By mitigating the impact of speckle noise and accurately distinguishing oil spill candidates from oil-free water, the CRF model achieves successful results even in scenarios where the availability of labeled samples is limited. This highlights the capability of CRF in handling situations with a scarcity of training data. Secondly, to improve the accuracy of sea ice mapping, a region-based automated classification methodology is developed. This methodology incorporates learned features, spatial context, and statistical properties from various SAR modes, resulting in enhanced classification accuracy and improved algorithmic efficiency. Thirdly, the presence of a high degree of heterogeneity in target distribution presents an additional challenge in land cover mapping tasks, further compounded by signature ambiguity. To address this, a novel transformer model is proposed. The transformer model incorporates both fine- and coarse-grained spatial dependencies between pixels and leverages different levels of features to enhance the accuracy of land cover type detection. The proposed approaches have undergone extensive experimentation in various remote sensing tasks, validating their effectiveness. By introducing tailored spatial models and innovative algorithms, this thesis successfully addresses the inherent complexity and variability of CP data, thereby ensuring the accuracy and reliability of diverse applications in the field of remote sensing

Polarimetric Synthetic Aperture Radar, Principles and Application

Demonstrates the benefits of the usage of fully polarimetric synthetic aperture radar data in applications of Earth remote sensing, with educational and development purposes. Includes numerous up-to-date examples with real data from spaceborne platforms and possibility to use a software to support lecture practicals. Reviews theoretical principles in an intuitive way for each application topic. Covers in depth five application domains (forests, agriculture, cryosphere, urban, and oceans), with reference also to hazard monitorin

Oil spill and ship detection using high resolution polarimetric X-band SAR data

Among illegal human activities, marine pollution and target detection are the key concern of Maritime Security and Safety. This thesis deals with oil spill and ship detection using high resolution X-band polarimetric SAR (PolSAR). Polarimetry aims at analysing the polarization state of a wave field, in order to obtain physical information from the observed object. In this dissertation PolSAR techniques are suggested as improvement of the current State-of-the-Art of SAR marine pollution and target detection, by examining in depth Near Real Time suitability

Monitoring Soil Moisture and Freeze/Thaw State Using C-band Imaging Radar

Soil moisture is an important state variable in many hydrological and meteorological applications. This thesis explores the use of the C-band synthetic aperture radar (SAR) parameters to monitor soil moisture and freeze/thaw state in a cold-season hydrologic environment. The circular-linear compact polarimetric (CP) configuration is considered as a possible alternative of the quad polarimetric (QP) system because it acquires images with wider swath and reduced complexity, cost and energy requirement of the radar system while maintaining the information content of the acquired imagery. In this study, 15 RADARSAT-2 QP images were acquired from October 2013 to June 2014 and CP images were simulated from each RADARSAT-2 QP imagery acquired. Field measurements of soil properties were collected along with the radar imagery acquisitions. The backscattering coefficients in all polarizations were able to discriminate frozen and unfrozen soils. But their correlations with soil moisture content were weak if examining frozen or unfrozen soils separately. The Oh et al. (1992) model was implemented in this study to compare with acquired RADARSAT-2 data. A good agreement was found between the linear polarimetric backscattering coefficients simulated by the Oh model and the RADARSAT-2 data, indicating that the study site even with 10 cm tall standing hay was consistent with a bare soil site at C-band and the Oh model can be applied to frozen soils. With respect to CP parameters, the first and fourth Stokes parameters and m-δ surface and volume scattering components can detect soil freeze/thaw state and have potential for frozen/unfrozen soils mapping. The influence of vegetation on selected CP parameters was also evident in this study. Results demonstrated the utility of C-band radar in detecting soil freeze/thaw state rather than monitoring the changes of soil moisture content. More image acquisitions during the freezing and thawing periods, continuous field measurements of soil moisture and state, and ground measurements collected over wider study area can help further develop understanding of the CP parameters and facilitate future use of the CP mode. The contribution of this thesis is to provide better understanding of the CP parameters at a specific site and to demonstrate that CP parameters can replicate QP SAR variables to detect surface soil conditions

Microwave Satellite Measurements for Coastal Area and Extreme Weather Monitoring

In this project report, the main outcomes relevant to the Sino-European Dragon-4 cooperation project ID 32235 “Microwave satellite measurements for coastal area and extreme weather monitoring” are reported. The project aimed at strengthening the Sino-European research cooperation in the exploitation of European Space Agency, Chinese and third-party mission Earth Observation (EO) microwave satellite data. The latter were exploited to perform an effective monitoring of coastal areas, even under extreme weather conditions. An integrated multifrequency/polarization approach based on complementary microwave sensors (e.g., Synthetic Aperture Radar, scatterometer, radiometer), together with ancillary information coming from independent sources, i.e., optical imagery, numerical simulations and ground measurements, was designed. In this framework, several tasks were addressed including marine target detection, sea pollution, sea surface wind estimation and coastline extraction/classification. The main outcomes are both theoretical (i.e., new models and algorithms were developed) and applicative (i.e., user-friendly maps were provided to the end-user community of coastal area management according to smart processing of remotely sensed data). The scientific relevance consists in the development of new algorithms, the effectiveness and robustness of which were verified on actual microwave measurements, and the improvement of existing methodologies to deal with challenging test cases

Monitoring wetlands and water bodies in semi-arid Sub-Saharan regions

Surface water in wetlands is a critical resource in semi-arid West-African regions that are frequently exposed to droughts. Wetlands are of utmost importance for the population as well as the environment, and are subject to rapidly changing seasonal fluctuations. Dynamics of wetlands in the study area are still poorly understood, and the potential of remote sensing-derived information as a large-scale, multi-temporal, comparable and independent measurement source is not exploited. This work shows successful wetland monitoring with remote sensing in savannah and Sahel regions in Burkina Faso, focusing on the main study site Lac Bam (Lake Bam). Long-term optical time series from MODIS with medium spatial resolution (MR), and short-term synthetic aperture radar (SAR) time series from TerraSAR-X and RADARSAT-2 with high spatial resolution (HR) successfully demonstrate the classification and dynamic monitoring of relevant wetland features, e.g. open water, flooded vegetation and irrigated cultivation. Methodological highlights are time series analysis, e.g. spatio-temporal dynamics or multitemporal-classification, as well as polarimetric SAR (polSAR) processing, i.e. the Kennaugh elements, enabling physical interpretation of SAR scattering mechanisms for dual-polarized data. A multi-sensor and multi-frequency SAR data combination provides added value, and reveals that dual-co-pol SAR data is most recommended for monitoring wetlands of this type. The interpretation of environmental or man-made processes such as water areas spreading out further but retreating or evaporating faster, co-occurrence of droughts with surface water and vegetation anomalies, expansion of irrigated agriculture or new dam building, can be detected with MR optical and HR SAR time series. To capture long-term impacts of water extraction, sedimentation and climate change on wetlands, remote sensing solutions are available, and would have great potential to contribute to water management in Africa

Processing of optic and radar images.Application in satellite remote sensing of snow, ice and glaciers

Ce document présente une synthèse de mes activités de recherche depuis la soutenance de ma thèse en 1999. L'activité rapportée ici est celle d'un ingénieur de recherche, et donc s'est déroulée en parallèle d'une activité ``technique'' comprenant des taches d'instrumentation en laboratoire, d'instrumentation de plateformes en montagne, de raids scientifiques sur les calottes polaires, d'élaboration de projets scientifiques, d'organisation d'équipes ou d'ordre administratif. Je suis Ingénieur de recherche CNRS depuis 2004 affecté au laboratoire Gipsa-lab, une unité mixte de recherche du CNRS, de Grenoble-INP, de l'université Joseph Fourier et de l'université Stendhal. Ce laboratoire (d'environ 400 personnes), conventionné avec l'INRIA, l'Observatoire de Grenoble et l'université Pierre Mendès France, est pluridisciplinaire et développe des recherches fondamentales et finalisées sur les signaux et les systèmes complexes.}Lors de la préparation de ma thèse (mi-temps 1995-99) au LGGE, je me suis intéressé au traitement des images de microstructures de la neige, du névé et de la glace. C'est assez naturellement que j'ai rejoint le laboratoire LIS devenu Gipsa-lab pour y développer des activités de traitement des images Radar à Synthèse d'Ouverture (RSO) appliqué aux milieux naturels neige, glace et glaciers. Etant le premier à générer un interférogramme différentiel des glaciers des Alpes, j'ai continué à travailler sur la phase interférométrique pour extraire des informations de déplacement et valider ces méthodes sur le glacier d'Argentière (massif du Mont-Blanc) qui présente l'énorme avantage de se déplacer de quelques centimètres par jour. Ces activités m'ont amené à développer, en collaboration avec les laboratoires LISTIC, LTCI et IETR, des méthodes plus générales pour extraire des informations dans les images RSO.Ma formation initiale en électronique, puis de doctorat en physique m'ont amené à mettre à profit mes connaissances en traitement d'images et des signaux, en électromagnétisme, en calcul numérique, en informatique et en physique de la neige et de la glace pour étudier les problèmes de traitement des images RSO appliqués à la glace, aux glaciers et à la neige