GNSS transpolar earth reflectometry exploriNg system (G-TERN): mission concept

The global navigation satellite system (GNSS) Transpolar Earth Reflectometry exploriNg system (G-TERN) was proposed in response to ESA's Earth Explorer 9 revised call by a team of 33 multi-disciplinary scientists. The primary objective of the mission is to quantify at high spatio-temporal resolution crucial characteristics, processes and interactions between sea ice, and other Earth system components in order to advance the understanding and prediction of climate change and its impacts on the environment and society. The objective is articulated through three key questions. 1) In a rapidly changing Arctic regime and under the resilient Antarctic sea ice trend, how will highly dynamic forcings and couplings between the various components of the ocean, atmosphere, and cryosphere modify or influence the processes governing the characteristics of the sea ice cover (ice production, growth, deformation, and melt)? 2) What are the impacts of extreme events and feedback mechanisms on sea ice evolution? 3) What are the effects of the cryosphere behaviors, either rapidly changing or resiliently stable, on the global oceanic and atmospheric circulation and mid-latitude extreme events? To contribute answering these questions, G-TERN will measure key parameters of the sea ice, the oceans, and the atmosphere with frequent and dense coverage over polar areas, becoming a “dynamic mapper”of the ice conditions, the ice production, and the loss in multiple time and space scales, and surrounding environment. Over polar areas, the G-TERN will measure sea ice surface elevation (<;10 cm precision), roughness, and polarimetry aspects at 30-km resolution and 3-days full coverage. G-TERN will implement the interferometric GNSS reflectometry concept, from a single satellite in near-polar orbit with capability for 12 simultaneous observations. Unlike currently orbiting GNSS reflectometry missions, the G-TERN uses the full GNSS available bandwidth to improve its ranging measurements. The lifetime would be 2025-2030 or optimally 2025-2035, covering key stages of the transition toward a nearly ice-free Arctic Ocean in summer. This paper describes the mission objectives, it reviews its measurement techniques, summarizes the suggested implementation, and finally, it estimates the expected performance.Peer ReviewedPostprint (published version

Wind direction signatures in GNSS-R observables from space

Peer ReviewedPostprint (published version

Ocean Remote Sensing with Synthetic Aperture Radar

The ocean covers approximately 71% of the Earth’s surface, 90% of the biosphere and contains 97% of Earth’s water. The Synthetic Aperture Radar (SAR) can image the ocean surface in all weather conditions and day or night. SAR remote sensing on ocean and coastal monitoring has become a research hotspot in geoscience and remote sensing. This book—Progress in SAR Oceanography—provides an update of the current state of the science on ocean remote sensing with SAR. Overall, the book presents a variety of marine applications, such as, oceanic surface and internal waves, wind, bathymetry, oil spill, coastline and intertidal zone classification, ship and other man-made objects’ detection, as well as remotely sensed data assimilation. The book is aimed at a wide audience, ranging from graduate students, university teachers and working scientists to policy makers and managers. Efforts have been made to highlight general principles as well as the state-of-the-art technologies in the field of SAR Oceanography

A Study of Polarimetric Parameters Used for Sea Ice Classification

The Arctic region of the Earth are largely covered by sea ice, which is important for the marine ecosystems locally in the region, but it also has an impact on the climate systems. Recent climate changes means that the sea ice is melting and the coverage is shrinking which can have a global impact. Monitoring these sea ice changes are important to get an understanding of this impact. There are multiple options for how to carry out this monitoring, but the Arctic is a cold, dark and remote region, so a good option is using satellite images. A special advantage of using SAR (Synthetic Aperture Radar) satellites is that they are insensitive to weather conditions and darkness, which can be a challenge in the Arctic regions, especially during the winter months. Today operational ice services produces sea ice charts using such SAR images but they primarily reply on dual-polarimetric data. These images covers large areas due to the large swath for these modes and are idea for a Pan-Arctic coverage. However, they are impacted by e.g., effects of varying incidence angle throughout the images. This thesis will study the possibilities that lies within radar polarimetry, a field that utilized fully polarimetric data to extract even more information regarding the target on the surface, in this case sea ice. Moreover, these images enabled extraction of scattering type information and through this added information improve the sea ice type classification maps. The images studied here are two sets of fully polarimetric RADARSAT-2 data that covers the same sea ice but with varying incidence angles. Four different polarimetric features; the co-polarization ratio, the M-parameter, degree of polarization as well as the polarimetric coherence, were investigated for their separability measures between different sea ice types as well as how affected they are by incidence angle variations. Out of these four the co-polarization ratio was found to be useful to separate the thinner sea ice types as well as open water from the surrounding thicker sea ice. Both the M-parameter and the degree of polarization showed promise in separating deformed sea ice from the other ice types at higher incidence angles. Though limited consistent separability between different ice types were observed for the polarimetric coherence. The polarimetric coherence was found to be independent on the incidence angle, though the other three parameters showed an incidence angle dependency

Forward and Inverse Modeling of GPS Multipath for Snow Monitoring

Snowpacks provide reservoirs of freshwater, storing solid precipitation and delaying runoff to be released later in the spring and summer when it is most needed. The goal of this dissertation is to develop the technique of GPS multipath reflectometry (GPS-MR) for ground-based measurement of snow depth. The phenomenon of multipath in GPS constitutes the reception of reflected signals in conjunction with the direct signal from a satellite. As these coherent direct and reflected signals go in and out of phase, signal-to-noise ratio (SNR) exhibits peaks and troughs that can be related to land surface characteristics. In contrast to other GPS reflectometry modes, in GPS-MR the poorly separated composite signal is collected utilizing a single antenna and correlated against a single replica. SNR observations derived from the newer L2-frequency civilian GPS signal (L2C) are used, as recorded by commercial off-the-shelf receivers and geodetic-quality antennas in existing GPS sites. I developed a forward/inverse approach for modeling GPS multipath present in SNR observations. The model here is unique in that it capitalizes on known information about the antenna response and the physics of surface scattering to aid in retrieving the unknown snow conditions in the antenna surroundings. This physically-based forward model is utilized to simulate the surface and antenna coupling. The statistically-rigorous inverse model is considered in two parts. Part I (theory) explains how the snow characteristics are parameterized; the observation/parameter sensitivity; inversion errors; and parameter uncertainty, which serves to indicate the sensing footprint where the reflection originates. Part II (practice) applies the multipath model to SNR observations and validates the resulting GPS retrievals against independent in situ measurements during a 1-3 year period in three different environments - grasslands, alpine, and forested. The assessment yields a correlation of 0.98 and an RMS error of 6-8 cm, with the GPS under-estimating in situ snow depth by approximately 15%. GPS daily site averages were found effective in mitigating random noise without unduly smoothing the sharp transitions as captured in new snow events. This work corroborates the readiness of quality-controlled GPS-MR for snow depth monitoring, reinforcing its maturity for operational usage

GNSS-R as a source of opportunity for remote sensing of the cryosphere

This work evaluates the potential use of signals from the Global Navigation Satellite Systems (GNSS) that scatter off the Earth surface for the retrieval of geophysical information from the cryosphere. For this purpose, the present study is based on data collected with a dedicated reflectometry GNSS receiver during two field campaigns, which were focused on two types of characteristic surfaces of the cryosphere: thin sea ice covers and thick dry snow accumulations. During the first experiment, the complete process of formation, evolution and melting of sea ice was monitorized for more than seven months in a bay located in Greenland. This type of ice is typically characterized by its thickness, concentration and roughness. Different observables from GNSS reflections are analyzed to try to infer these properties. The ice thickness is linked to the free-board level, defined as the height of the sea ice surface. Accurate phase altimetry is achieved, showing good agreement with an Arctic tide model. In addition, the long term results of ellipsoidal height retrievals are consistent with the evolution of the ice surface temperature product given by MODIS, which is a key parameter in the rate of growth of sea ice. On the other hand, the presence of salinity in the sea ice modifies its dielectric properties, resulting in different amplitude and phase for the co- and cross-polar components of the complex Fresnel coefficients. The polarimetric measurements obtained show good agreement with visual inspections of ice concentration from an Arctic weather station. Finally, the shape of the reflected signals and its phase dispersion are tested as potential signatures of surface roughness. For comparison, ice charts of the experimental area are employed. In particular, maximums in roughness given by the GNSS observables coincide with fast ice events. Fast ice is defined as ice anchored to the coast, where the tidal movements contribute to the development of strange patterns, cracks, and fissures on its surface, thus consistent with the GNSS-R roughness retrievals. The second experiment took place on Antarctica, monitoring a pristine snow area which is well-known for the calibration of remote sensing instruments. Due to the relative stability of the snow layers, the data acquisition was limited to ten continuous days. Interferometric beats were found after a first analysis of the amplitude from the collected signals, which were consistent with a multipath model where the reflector lies below the surface level. Motivated by these results, a forward model is developed that reconstructs the complex received signal as a sum of a finite number of reflections, coming from different snow layers (a snow density profile obtained from in-situ measurements). The interferometric information is then retrieved from the spectral analysis applied to time series from both real and modeled signals (lag-holograms). We find that the frequency bands predicted by the model are in general consistent with the data and the lag-holograms show repeatability for different days. Then, we attempt a proper inversion of the collected data to determine the dominant layers of the dry snow profile that contribute to L-band reflections, which are related to significant gradients of snow density/permittivity.Aquest treball avalua el possible ús dels senyals dels sistemes mundials de navegació per satèl lit (GNSS) que es reflecteixen a la superfície terrestre, per a l’extracció de la informació geofísica de la criosfera. Amb aquest propòsit, el present estudi es basa en dades recollides amb un reflectòmetre GNSS durant dues campanyes experimentals, centrades en dos tipus de superfícies característiques de la criosfera: cobertes de gel marí i gruixudes acumulacions de neu seca. En el primer experiment, el procés complet de formació, evolució i fusió del gel marí va ser monitoritzat durant més de set mesos a una badia situada a Groenlàndia. Aquest tipus de gel es caracteritza típicament amb el seu gruix, concentració i rugositat. Diferents observables de les reflexions GNSS són analitzats per tractar de fer una estimació d’aquestes propietats. El gruix de gel està relacionat amb el nivell de francbord, que a la seva vegada està relacionat amb l’alçada de la superfície de gel marí. S’ha aconseguit altimetria de fase precisa, que mostra correlació amb un model de marea de l’Àrtic. A més, els resultats a llarg termini de l’alçada elipsoidal segueixen l’evolució de les mesures de temperatura de superfície de gel donades per MODIS. La temperatura és un paràmetre clau en el ritme de creixement del gel marí. Per altra banda, la presència de sal a aquest tipus de gel modifica les seves propietats dielèctriques, el que implica variacions d’amplitud i fase per als coeficients de Fresnel complexos amb polaritzacions oposades. Les mesures polarimètriques obtingudes mostren concordança amb els valors de concentració de gel obtinguts des d’una estació meteorològica propera. Finalment, la forma de la senyal reflectida i la dispersió de la seva fase s’evaluen com a potencials indicadors de la rugositat de superfície. Per a la seva comparació, es fan servir mapes del gel de la zona experimental. En concret, els valors màxims a la rugositat estimada a partir pels observables GNSS coincideixen amb el gel fixe, que es refereix a gel ancorat a la costa, on els moviments de les marees contribueixen al desenvolupament de patrons estranys, esquerdes i fissures en la seva superfície. El segon experiment es va dur a terme a l’Antàrtida, monitoritzant una àrea de neu pristina que és ben coneguda per al calibratge d’instruments de teledetecció. A causa de la relativa estabilitat de les capes de neu, l’adquisició de dades es va limitar a deu dies consecutius. Es van trobar pulsacions interferomètriques a partir d’un primer anàlisi de l’amplitud de les senyals recollides, les quals eren compatibles amb un model de propagació multicamí a on el reflector es troba per sota del nivell de superfície. Com a conseqüència d’aquests resultats, s’ha desenvolupat un model que reconstrueix el senyal complexe rebut com la suma d’un nombre finit de reflexions, procedents de diferents capes de neu (determinat per mesures locals). La informació interferomètrica es recupera després de l’anàlisi espectral aplicat a les sèries temporals tant de les senyals reals, com de les modelades (lag-hologrames). Trobem que les bandes de freqüències predites pel model són en general consistents amb les dades i que els lag-hologrames mostren repetibilitat per dies diferents. Posteriorment, es realitza un anàlisi de les dades recollides per determinar les capes dominants del perfil de neu seca que contribueixen a les reflexions en banda L, i que a la seva vegada, estan relacionades amb gradents significatius de densitat/permitivitat.Este trabajo evalúa el posible uso de las señales de los sistemas globales de navegación por satélite (GNSS) que se reflejan en la superficie terrestre para la extracción de información geofísica de la criosfera. Con este propósito, el presente estudio se basa en datos recogidos con un reflectómetro GNSS durante dos campañas experimentales, centradas en dos tipos de superficies características de la criosfera: capas de hielo marino y gruesas acumulaciones de nieve seca. Durante el primer experimento, el proceso completo de formación, evolución y fusión del hielo marino fue monitorizado durante más de siete meses en una bahía ubicada en Groenlandia. Este tipo de hielo se caracteriza típicamente por su grosor, concentración y rugosidad. Diferentes observables de las reflexiones GNSS son analizados para tratar de estimar dichas propiedades. El espesor de hielo está relacionado con el nivel de francobordo o borda libre, que a su vez está relacionado con la altura de la superficie de hielo marino. Se ha logrado altimetría de fase precisa, mostrando correlación con un modelo de marea del Ártico. Además, los resultados a largo plazo de la altura elipsoidal siguen la evolución de las mediciones de temperatura de superficie de hielo proporcionadas por MODIS. La temperatura es un parámetro clave en el ritmo de crecimiento del hielo marino. Por otro lado, la presencia de sal en este tipo de hielo modifica sus propiedades dieléctricas, lo que implica variaciones en las amplitudes y fases de los coeficientes complejos de Fresnel con polarizaciones opuestas. Los resultados polarimétricos concuerdan con los valores de concentración de hielo obtenidos mediante inspección visual desde una estación meteorológica cercana. Por último, la forma de la señal reflejada y la dispersión de su fase son evaluadas como potenciales indicadores de la rugosidad de superficie. Para su comparación, se emplean mapas del hielo de la zona experimental. En particular, valores máximos de rugosidad estimada por los observables GNSS coinciden con hielo fijo, que se refiere al hielo anclado a la costa, donde los movimientos de las mareas contribuyen al desarrollo de patrones extraños, grietas y fisuras en su superficie. El segundo experimento se llevó a cabo en la Antártida, monitorizando una área de nieve pristina que es bien conocida para la calibración de instrumentos de teledetección. Debido a la relativa estabilidad de las capas de nieve, la adquisición de datos se limitó a diez días consecutivos. Se encontraron pulsaciones interferométricas a partir de un primer análisis de la amplitud de las señales recibidas, las cuales eran compatibles con un modelo de propagación multicamino donde el reflector se encuentra por debajo del nivel de la superficie. Como consecuencia de estos resultados, se ha desarrollado un modelo que reconstruye la señal recibida como la suma de un número finito de reflexiones, procedentes de diferentes capas de nieve (caracterizados por mediciones locales). La información interferométrica se recupera después del análisis espectral aplicado a las series temporales tanto de las señales reales, como de las modeladas (lag-hologramas). Encontramos que las bandas de frecuencias predichas por el modelo son en general consistentes con los datos y que los lag-hologramas muestran repetibilidad para días diferentes. Posteriormente, se realiza un análisis de los datos recogidos para determinar las capas dominantes del perfil de nieve seca que contribuyen a las reflexiones en banda L, y que a su vez, están relacionadas con gradientes significativos de densidad/permitivida

Multi-technique approach to rockfall monitoring in the Montserrat massif (Catalonia, NE Spain)

Montserrat Mountain is located near Barcelona in Catalonia, in the northeast of Spain, and its massif is formed by conglomerate interleaved by siltstone/sandstone with steep slopes very prone to rockfalls. The increasing number of visitors in the monastery area, reaching 2.4 million per year, has highlighted the risk derived from rockfalls for this building area and also for the terrestrial accesses, both roads and the rack railway. A risk mitigation plan has been launched, and its first phase during 2014-2016 has been focused largely on testing several monitoring techniques for their later implementation. The results of the pilot tests, performed as a development from previous sparse experiences and data, are presented together with the first insights obtained. These tests combine four monitoring techniques under different conditions of continuity in space and time domains, which are: displacement monitoring with Ground-based Synthetic Aperture Radar and characterization at slope scale, with an extremely non-uniform atmospheric phase screen due to the stepped topography and atmosphere stratification; Terrestrial Laser Scanner surveys quantifying the frequency of small or even previously unnoticed rockfalls, and monitoring rock block centimetre scale displacements; the monitoring of rock joints implemented through a wireless sensor network with an ad hoc design of ZigBee loggers developed by ICGC; and, finally, monitoring singular rock needles with Total Station.Peer ReviewedPostprint (author's final draft

Coherence estimation in synthetic aperture radar data based on speckle noise modeling

In the past we proposed a multidimensional speckle noise model to which we now include systematic phase variation effects. This extension makes it possible to define what is believed to be a novel coherence model able to identify the different sources of bias when coherence is estimated on multidimensional synthetic radar aperture (SAR) data. On the one hand, low coherence biases are basically due to the complex additive speckle noise component of the Hermitian product of two SAR images. On the other hand, the availability of the coherence model permits us to quantify the bias due to topography when multilook filtering is considered, permitting us to establish the conditions upon which information may be estimated independently of topography. Based on the coherence model, two coherence estimation approaches, aiming to reduce the different biases, are proposed. Results with simulated and experimental polarimetric and interferometric SAR data illustrate and validate both, the coherence model and the coherence estimation algorithms.Peer Reviewe

Fusion of VNIR Optical and C-Band Polarimetric SAR Satellite Data for Accurate Detection of Temporal Changes in Vegetated Areas

In this paper, we propose a processing chain jointly employing Sentinel-1 and Sentinel-2 data, aiming to monitor changes in the status of the vegetation cover by integrating the four 10 m visible and near-infrared (VNIR) bands with the three red-edge (RE) bands of Sentinel-2. The latter approximately span the gap between red and NIR bands (700 nm–800 nm), with bandwidths of 15/20 nm and 20 m pixel spacing. The RE bands are sharpened to 10 m, following the hypersharpening protocol, which holds, unlike pansharpening, when the sharpening band is not unique. The resulting 10 m fusion product may be integrated with polarimetric features calculated from the Interferometric Wide (IW) Ground Range Detected (GRD) product of Sentinel-1, available at 10 m pixel spacing, before the fused data are analyzed for change detection. A key point of the proposed scheme is that the fusion of optical and synthetic aperture radar (SAR) data is accomplished at level of change, through modulation of the optical change feature, namely the difference in normalized area over (reflectance) curve (NAOC), calculated from the sharpened RE bands, by the polarimetric SAR change feature, achieved as the temporal ratio of polarimetric features, where the latter is the pixel ratio between the co-polar and the cross-polar channels. Hyper-sharpening of Sentinel-2 RE bands, calculation of NAOC and modulation-based integration of Sentinel-1 polarimetric change features are applied to multitemporal datasets acquired before and after a fire event, over Mount Serra, in Italy. The optical change feature captures variations in the content of chlorophyll. The polarimetric SAR temporal change feature describes depolarization effects and changes in volumetric scattering of canopies. Their fusion shows an increased ability to highlight changes in vegetation status. In a performance comparison achieved by means of receiver operating characteristic (ROC) curves, the proposed change feature-based fusion approach surpasses a traditional area-based approach and the normalized burned ratio (NBR) index, which is widespread in the detection of burnt vegetation