Heterogeneous and rapid ice loss over the Patagonian Ice Fields revealed by CryoSat-2 swath radar altimetry

The Northern and Southern Patagonian Ice Fields (NPI and SPI) in South America are the largest bodies of ice in the Southern hemisphere outside of Antarctica and the largest contributors to eustatic sea level rise (SLR) in the world, per unit area. Here we exploit swath processed CryoSat-2 interferometric data to produce maps of surface elevation change at sub-kilometer spatial resolution over the Ice Fields for six glaciological years between April 2011 and March 2017. Mass balance is calculated independently for nine sub-regions, including six individual glaciers larger than 300 km². Overall, between 2011 and 2017 the Patagonian Ice Fields have lost mass at a combined rate of 21.29 ± 1.98 Gt a−¹, contributing 0.059 ± 0.005 mm a−¹ to SLR. We observe widespread thinning on the Ice Fields, particularly north of 49° S. However the pattern of surface elevation change is highly heterogeneous, partly reflecting the importance of dynamic processes on the Ice Fields. The Jorge Montt glacier (SPI), whose tidewater terminus is approaching floatation, retreated ~2.5 km during our study period and lost mass at the rate of 2.20 ± 0.38 Gt a−¹ (4.64 ± 0.80 mwe a−¹). In contrast with the general pattern of retreat and mass loss, Pio XI, the largest glacier in South America, is advancing and gaining mass at 0.67 ± 0.29 Gt a−¹ rate

Traitements cohérents d’images RSO multi-modes multi-resolutions pour la caractérisation du milieu urbain

The refinement of Synthetic Aperture Radar (SAR) imagery makes the monitoring of urban areas possible. Different acquisition modes of multivariate SAR images are available, such as the polarimetric mode that gives information about the nature or the geometry of imaged objects, or the interferometric mode that enables the measure of their height or the displa- cement between two acquisitions. However, all the acquisition modes do not reach the same spatial resolution. The major goal of this work was to combine polarimetric images and a mono-channel high-resolution image to create high resolution polarimetric images with the same properties as the initial polarimetric image.This work started with the study of covariance matrices estimation from which meaningful parameters linkable to physical infor- mation, such as the phase, can be extracted. We first showed that the variance is not adapted to describe the fluctuations of the estimated phase. We proposed a directional statistics indicator to describe the estimated phase fluctuations, whichever the definition interval of the phase. This indicator can be used to separate two populations of pixels with different phase fluctuations or to compare the measured phase to a modeled phase. We also showed that the resolution has an impact on the covariance matrix estimation, because it restrains the size of the sample of pixels which values can be considered as independent and identically distributed for the covariance matrix estimation.We chose to model the urban scatterers as a combination of randomly responding scatterers and deterministic bright point-like scatterers. The values of the pixels representing the random scatterers are modeled following the fully developed speckle ; the point-like scatterers are supposed to be white and isotropic. The Pol-Sharpening algorithms that we developed are based on the point-like scatterers spectral properties. One of the key issue is to have a sufficient sample size in order to limit the fluctuation of the polarimetric information estimation without introducing mixing. The chosen spectral method enables to focalize the point- like scatterers, i.e. to refine the resolution, while preserving their polarimetric and interferometric properties. If the developed algorithms keep the value of intensity and phase of the pixels included in homogeneous speckle areas, they modify their statistical parameters.Finally, we studied the measure of the height and the deformation of the Eiffel Tower and three other towers on the Front de Seine in Paris using a temporal stack of 98 TerraSAR-X images acquired between 2008 and 2012. We showed that neglecting the deformation during the height measurement could result in outliers. Even though these outliers can be removed during the study of a temporal stack, it is still a limitation of the interferometry techniques on buildings. By measuring a monoscopic height, we could measure deformations up to four centimeters for the Eiffel Tower. These deformations do not present any seasonal trend contrary to the deformations measured on the Mirabeau Tower, which are minimal in winter and maximal in summer. Nevertheless, we neglected the impact of the atmosphere on the deformation measurement and this work hypothesis limits our measurement accuracy to the centimeter.Nous nous sommes intéressés à l’étude du milieu urbain par l’imagerie Radar à Synthèse d’Ouverture (RSO), rendue possible par l’amélioration des résolutions des images. Différents modes d’acquisition d’images RSO multi-variées sont possibles, comme la polarimétrie qui apporte des informations sur la nature et la géométrie des objets présents sur la scène et l’interférométrie qui permet d’en mesurer la hauteur ou le déplacement entre différentes acquisitions. Cependant, tous ces modes n’ont pas la même résolution. L’objectif de ce travail a été de combiner des images polarimétriques et des images mono-canales de résolution plus fine pour former des images de résolution fine conservant les propriétés polarimétriques et interférométriques des images originales.Nous avons commencé par étudier l’estimation des matrices de covariance des images qui permet l’extraction de paramètres tels que la phase, qui peuvent être reliés à des informations physiques. Nous avons tout d’abord montré que la variance n’est pas un indicateur statistique adapté pour décrire les fluctuations de la phase estimée. Nous avons alors proposé un indicateur basé sur la théorie des statistiques directionnelles qui permet de séparer deux populations de pixels dont les fluctuations de la phase sont différentes ou de comparer des phases mesurées à des phases simulées, quel que soit l’intervalle de définition de la phase. Nous avons aussi montré que la résolution impacte l’estimation des statistiques des images du milieu urbain en imposant des contraintes sur la taille de l’échantillon de pixels dont les valeurs peuvent être considérées comme indépendantes et identiquement distribuées pour l’estimation de la matrice de covariance.Nous avons modélisé les diffuseurs présents en milieu urbain en une combinaison de diffuseurs ayant un comportement aléatoire et des diffuseurs déterministes, ponctuels et très énergétiques appelés points-brillants. Les valeurs des pixels qui représentent les diffuseurs aléatoires sont modé- lisées selon le modèle de speckle pleinement développé ; les points-brillants sont supposés blancs et isotropes. Les algorithmes de raffinement de la résolution des images polarimétriques que nous avons développés sont fondés sur les propriétés spectrales de ces points-brillants. L’un des enjeux majeurs est d’utiliser un échantillon de taille suffisamment grande pour limiter la fluctuation de l’estimation des informations polari- métriques, sans introduire de mélange, tout en gardant les propriétés aléatoires du speckle. La méthode spectrale choisie permet d’assurer la focalisation des points-brillants et donc le raffinement de la résolution tout en préservant leurs informations polarimétriques et interférométriques. Si les algorithmes développés conservent bien les valeurs d’intensité et de phase des pixels des zones homogènes de speckle, ils en diminuent le degré d’aléatoire.Enfin, nous nous sommes intéressés à la mesure de la hauteur et de la déformation de la Tour Eiffel et de trois autres tours situées sur le Front de Seine, en utilisant une pile temporelle de 98 images TerraSAR-X acquises entre 2008 et 2012. Nous avons montré que négliger les déformations lors de la mesure de la hauteur peut résulter en des hauteurs aberrantes. Si ces hauteurs aberrantes peuvent être supprimées dans le cadre de l’étude d’une pile temporelle, elles sont néanmoins une limitation de la technique d’interférométrie sur des bâtiments. En mesurant une hauteur monoscopique, nous avons pu mesurer des déformations allant jusqu’à quatre centimètres pour la Tour Eiffel. Ces déformations ne présentent pas de tendance saisonnière contrairement aux déformations mesurées sur la Tour Mirabeau, qui sont minimale en hiver et maximale en été. Par contre, nous avons négligé l’impact de l’atmosphère dans la mesure de la déformation ce qui limite la précision de la mesure de la déformation au centimètre

Traitements cohérents d’images RSO multi-modes multi-resolutions pour la caractérisation du milieu urbain

The refinement of Synthetic Aperture Radar (SAR) imagery makes the monitoring of urban areas possible. Different acquisition modes of multivariate SAR images are available, such as the polarimetric mode that gives information about the nature or the geometry of imaged objects, or the interferometric mode that enables the measure of their height or the displa- cement between two acquisitions. However, all the acquisition modes do not reach the same spatial resolution. The major goal of this work was to combine polarimetric images and a mono-channel high-resolution image to create high resolution polarimetric images with the same properties as the initial polarimetric image.This work started with the study of covariance matrices estimation from which meaningful parameters linkable to physical infor- mation, such as the phase, can be extracted. We first showed that the variance is not adapted to describe the fluctuations of the estimated phase. We proposed a directional statistics indicator to describe the estimated phase fluctuations, whichever the definition interval of the phase. This indicator can be used to separate two populations of pixels with different phase fluctuations or to compare the measured phase to a modeled phase. We also showed that the resolution has an impact on the covariance matrix estimation, because it restrains the size of the sample of pixels which values can be considered as independent and identically distributed for the covariance matrix estimation.We chose to model the urban scatterers as a combination of randomly responding scatterers and deterministic bright point-like scatterers. The values of the pixels representing the random scatterers are modeled following the fully developed speckle ; the point-like scatterers are supposed to be white and isotropic. The Pol-Sharpening algorithms that we developed are based on the point-like scatterers spectral properties. One of the key issue is to have a sufficient sample size in order to limit the fluctuation of the polarimetric information estimation without introducing mixing. The chosen spectral method enables to focalize the point- like scatterers, i.e. to refine the resolution, while preserving their polarimetric and interferometric properties. If the developed algorithms keep the value of intensity and phase of the pixels included in homogeneous speckle areas, they modify their statistical parameters.Finally, we studied the measure of the height and the deformation of the Eiffel Tower and three other towers on the Front de Seine in Paris using a temporal stack of 98 TerraSAR-X images acquired between 2008 and 2012. We showed that neglecting the deformation during the height measurement could result in outliers. Even though these outliers can be removed during the study of a temporal stack, it is still a limitation of the interferometry techniques on buildings. By measuring a monoscopic height, we could measure deformations up to four centimeters for the Eiffel Tower. These deformations do not present any seasonal trend contrary to the deformations measured on the Mirabeau Tower, which are minimal in winter and maximal in summer. Nevertheless, we neglected the impact of the atmosphere on the deformation measurement and this work hypothesis limits our measurement accuracy to the centimeter.Nous nous sommes intéressés à l’étude du milieu urbain par l’imagerie Radar à Synthèse d’Ouverture (RSO), rendue possible par l’amélioration des résolutions des images. Différents modes d’acquisition d’images RSO multi-variées sont possibles, comme la polarimétrie qui apporte des informations sur la nature et la géométrie des objets présents sur la scène et l’interférométrie qui permet d’en mesurer la hauteur ou le déplacement entre différentes acquisitions. Cependant, tous ces modes n’ont pas la même résolution. L’objectif de ce travail a été de combiner des images polarimétriques et des images mono-canales de résolution plus fine pour former des images de résolution fine conservant les propriétés polarimétriques et interférométriques des images originales.Nous avons commencé par étudier l’estimation des matrices de covariance des images qui permet l’extraction de paramètres tels que la phase, qui peuvent être reliés à des informations physiques. Nous avons tout d’abord montré que la variance n’est pas un indicateur statistique adapté pour décrire les fluctuations de la phase estimée. Nous avons alors proposé un indicateur basé sur la théorie des statistiques directionnelles qui permet de séparer deux populations de pixels dont les fluctuations de la phase sont différentes ou de comparer des phases mesurées à des phases simulées, quel que soit l’intervalle de définition de la phase. Nous avons aussi montré que la résolution impacte l’estimation des statistiques des images du milieu urbain en imposant des contraintes sur la taille de l’échantillon de pixels dont les valeurs peuvent être considérées comme indépendantes et identiquement distribuées pour l’estimation de la matrice de covariance.Nous avons modélisé les diffuseurs présents en milieu urbain en une combinaison de diffuseurs ayant un comportement aléatoire et des diffuseurs déterministes, ponctuels et très énergétiques appelés points-brillants. Les valeurs des pixels qui représentent les diffuseurs aléatoires sont modé- lisées selon le modèle de speckle pleinement développé ; les points-brillants sont supposés blancs et isotropes. Les algorithmes de raffinement de la résolution des images polarimétriques que nous avons développés sont fondés sur les propriétés spectrales de ces points-brillants. L’un des enjeux majeurs est d’utiliser un échantillon de taille suffisamment grande pour limiter la fluctuation de l’estimation des informations polari- métriques, sans introduire de mélange, tout en gardant les propriétés aléatoires du speckle. La méthode spectrale choisie permet d’assurer la focalisation des points-brillants et donc le raffinement de la résolution tout en préservant leurs informations polarimétriques et interférométriques. Si les algorithmes développés conservent bien les valeurs d’intensité et de phase des pixels des zones homogènes de speckle, ils en diminuent le degré d’aléatoire.Enfin, nous nous sommes intéressés à la mesure de la hauteur et de la déformation de la Tour Eiffel et de trois autres tours situées sur le Front de Seine, en utilisant une pile temporelle de 98 images TerraSAR-X acquises entre 2008 et 2012. Nous avons montré que négliger les déformations lors de la mesure de la hauteur peut résulter en des hauteurs aberrantes. Si ces hauteurs aberrantes peuvent être supprimées dans le cadre de l’étude d’une pile temporelle, elles sont néanmoins une limitation de la technique d’interférométrie sur des bâtiments. En mesurant une hauteur monoscopique, nous avons pu mesurer des déformations allant jusqu’à quatre centimètres pour la Tour Eiffel. Ces déformations ne présentent pas de tendance saisonnière contrairement aux déformations mesurées sur la Tour Mirabeau, qui sont minimale en hiver et maximale en été. Par contre, nous avons négligé l’impact de l’atmosphère dans la mesure de la déformation ce qui limite la précision de la mesure de la déformation au centimètre

Joint measurement of height and deformation by radar Interferometry: the example of the Eiffel Tower

International audienceThe measurement of altitude and ground movements are well-known problems in InSAR. With the refinement of the resolution, the same techniques can be considered for monitoring individual buildings. Since the measure of the height and the deformations are interlinked in the interferometric phase, a measure of the height is necessary to obtain the deformations. In this article, we monitor the deformations of the Eiffel Tower using 50 images acquired by TerraSAR-X, with a metric resolution. The height is obtained using a single pass interferogram acquired by TerraSAR-X and TanDEM-X. Then these measures are compared to weather data and optical strand fixed to the Eiffel Tower by the company OSMOS. The normalized correlation of the measured deformations with the minimum temperature measured on the acquisition dates is 0.5 for the Eiffel Tower and the deformation measured by InSAR have the same order of magnitude than the deformation measured by the optical strands. To achieve local deformations measurement by interferometry, it is necessary to have the height of each pixel of the structure. This height can be obtained using a 3D model, provided that the acquisition geometry and backscattering effects are taken into account. The deformations maps obtained using a 3D model or a single pass interferogram have similar orders of magnitude

Sentinel 1 Snow extend and snow change mapping using SVM

International audienceSnow dynamics is a key parameter for the hydrological model predicting the river flow rate used in dam management. In the MORDOR model used by EDF, the information of the daily snow extent isan input to improve the flow prediction. This information is extracted from MODIS NDSI daily product. Due to cloud cover, this information can be lacking or imprecise for multiple consecutivedays over one catchment, reducing the precision of the prediction. The goal of this study is to detect the snow extent using SAR data, since it can acquire images through clouds. We focus over the Guil catchment in the French Alps. Sentinel-1 interferometric stacks from June 2018 to August 2019 are used for three different orbits. Previous studies showed the capacity of the ratio between the current image and a reference image acquired in summer to detect wet snow [Nagler2016], or that the ratio between VH and VV could be linked to the height of snow [Lievens2019]. Interferometry has be shown capable to detect snow since the snow covered area can exhibit a lower coherence [Singh2008]. To compare these parameters using a ground truth, we projected the MODIS NDSI data on ourS1-stack using a 1m DEM and considered pixels as snowy if the NDSI is above 0.4. As pointed in other studies [Löw2002, Wang2015], it is very hard to set a threshold for these parameters, mostly because the vegetation exhibits volume scattering and changes the same way as snow. Using SVM, we investigated the capability of these parameters to detect snow in two setups: - snow detection: the goal is to classify the pixels as snow or snow-free for all the image, using Nagler parameter in VV and VH, the ratio between VH and VV at each date and the polarimetric coherence at each date. For Nagler parameter, the reference image is the temporal average of the images over July and August 2018.-change detection: the goal is to classify the pixels into 4 classes, snow-free to snow-free, snow to snow, snow-free to snow and snow to snow-free. Considering two consecutive images, this wasdone using the variation of the VV and VH ratio, the interferometric coherence between these images, and the ratio between the polarimetric coherences of the images. For each setup, the learning and the testing were done on two samples of 20000 randomly selected pixels, equally distributed between the classes. For the snow detection method, between 54% and 59% of the pixels are correctly classified, for the three orbits. This result is stable with the choice of the learning sample. For the change detection setup only 30% of the pixels are correctly classified. Moreover, the per-class metrics vary widely from one experience to the other. This variability as well as the low classification results underline the difficulty of the task but can also be linked to the resolution difference between MODIS usedas ground truth and S1. To robustify the detection, spatial and temporal regularization seems necessary

Dynamic speckle imaging of human skin vasculature with a high-speed camera

International audienceWe demonstrate the ability of high-speed acquisition (up to 30 kHz) of dynamic speckle to provide images of the human vascularization at various scales. A comparative study involving the speckle contrast, the first term of the intensity autocorrelation function, and the zero-crossings of the field intensity is proposed, together with a proper preprocessing scheme based on image registration and filtering. Experimental results show the potential of the first term of the autocorrelation function to provide efficient model-free mapping of the microvascular activity (i.e. small-scale random motion associated with the presence of a vessel). With the help of this parameter, various scales of vascularization including large vessels in the wrist, microvessels in the ear and fingers, and thinner inflammatory structures are observed, which suggests the imaging abilities of this parameter are broad. The minimum acquisition time is shown to be of the order of 50 ms, demonstrating video imaging capabilities

Urban change detection by comparing SAR images at different resolution and polarimetric modes

International audience<p>Today, the variety of remote sensing satellites increases the interest of combining images of different types to satisfy the needs of earth monitoring with a better reactivity. In this context, this article aims to demonstrate the feasibility of change detection between a high resolution SAR image and a polarimetric SAR image. It highlights the interest of this configuration for change detection but also the analysis of these change areas through to the polarimetric information. The approach is applied to the case of urban areas.</p

Évaluation du couvert neigeux à partir d’images SAR par apprentissage profond basé sur des images optiques de référence

International audienceOptical satellite images are commonly used to evaluate the snow cover. However, part of the information is lost due to clouds. To fill this gap we propose to detect the snow from Sentinel-1 SAR images using a convolutional neural network trained with labels obtained from MODIS optical images. A binary semantic segmentation is computed from two polarimetric SAR inputs: a wet snow ratio and a dry snow ratio. The model, called SESAR U-net, is trained on a small area and then tested over a whole watershed. The missing labels are interpolated and the uncertainty due to clouds is considered. Our proposed method gives anoverall accuracy higher than 80%.Les images satellites optiques sont couramment utilisées pour évaluer le couvert neigeux, mais dépendent des conditions météorologiques telles que les nuages. Pour pallier ce problème, nous proposons de détecter la neige à partir d’images SAR acquises par Sentinel-1 en utilisant un réseau de neurones convolutif entraîné avec des étiquettes issues d’images optiques MODIS. Une segmentation sémantique binaire est calculée à partir de deux entrées SAR polarimétrique : un ratio de neige humide et un ratiode neige sèche. Le modèle, appelé SESAR U-net, est entraîné sur une petite zone puis testé sur l’ensemble d’un bassin versant. Les étiquettes affectées par les nuages sont interpolées et l’incertitude est prise en compte. Notre méthode permet d’obtenir une précision globale supérieure à 80

3D Monitoring of Buildings Using TerraSAR-X InSAR, DInSAR and PolSAR Capacities

The rapid expansion of cities increases the need of urban remote sensing for a large scale monitoring. This paper provides greater understanding of how TerraSAR-X (TSX) high-resolution abilities enable to reach the spatial precision required to monitor individual buildings, through the use of a 4 year temporal stack of 100 images over Paris (France). Three different SAR modes are investigated for this purpose. First a method involving a whole time-series is proposed to measure realistic heights of buildings. Then, we show that the small wavelength of TSX makes the interferometric products very sensitive to the ordinary building-deformation, and that daily deformation can be measured over the entire building with a centimetric accuracy, and without any a priori on the deformation evolution, even when neglecting the impact of the atmosphere. Deformations up to 4 cm were estimated for the Eiffel Tower and up to 1 cm for other lower buildings. These deformations were analyzed and validated with weather and in situ local data. Finally, four TSX polarimetric images were used to investigate geometric and dielectric properties of buildings under the deterministic framework. Despite of the resolution loss of this mode, the possibility to estimate the structural elements of a building orientations and their relative complexity in the spatial organization are demonstrated

A NEW LIGHT ON ORIGINS OF POLARIMETRIC MISCLASSIFICATION OF THE SOMA DISTRICT, DUE TO THE DIFFICULTY TO PREDICT ENTROPY

International audience<p>Entropy is often used in polarimetric classification al- gorithms, for example by unsupervised Wishart classi- fication in alpha entropy feature space. In this frame- work, entropy is supposed to be low for man-made tar- gets. However, on most examples of classification results on San Francisco images, this parameter fails to well clas- sify the SOMA district, which contains a lot skyscrapers with a particular orientation. Even very recent studies fail to compensate the orientation effect on this area. More- over, TerraSAR-X images are also difficult to handle be- cause they show a high entropy with poor contrast be- tween natural and deterministic targets. Then, this paper investigates the reason of these issues. Several aspects are investigated: does entropy depends on noise ratio, wave- length, resolution size, orientation effect or complexity of the medium?</p