Validation of surface velocity estimated from satellite images

This report concerns the validation of surface velocity estimated from satellite images. The estimation is obtained with a dynamic model based on shallow-water equations. We first compare the stationary assumption to the shallow-water heuristics to justify our choice. Second, we quantify the quality of the estimation by measuring the misfit between the model output and the altimetry measures. Experiments are achieved on Sea Surface Temperature data acquired by the NOAA/AVHRR satellites over the Black Sea. The altimetry measures are obtained by two radar sensors: Envisat and GFO. The good adequacy between the shallow-water output and the altimetry data validates our motion estimation approach.Ce rapport de recherche concerne la validation de l'estimation de la vitesse de surface à partir d'images satellite. Cette estimation est effectuée avec un modèle de la dynamique, basé sur les équations shallow-water. Nous comparons d'abord l'hypothèse de stationnarité aux équations shallow-water afin de justifier notre choix. Puis, nous quantifions la qualité des estimations en mesurant l'écart entre la sortie du modèle et les mesures d'altimétrie. Les expérimentations sont effectuées en utilisant des données de température de surface, acquises au-dessus de la Mer Noire avec les satellites NOAA/AVHRR. Les mesures altimétriques proviennent de deux capteurs radar : Envisat et GFO. La bonne adéquation entre la sortie du modèle shallow-water et les données altimétriques valide notre approche d'estimation du mouvement

Image-based modelling of ocean surface circulation from satellite acquisitions

International audienceSatellite image sequences permit to visualise oceans' surface and their underlying dynamics. Processing these images is then of major interest in order to better understanding of the observed processes. As demonstrated by state-of-the-art, image assimilation allows to retrieve surface motion from image sequences, based on assumptions on the dynamics. In this paper we demonstrate that a simple heuristics, such as the Lagrangian constancy of velocity, can be used, and successfully replaces the complex physical properties described by the Navier-Stokes equations, for assessing surface circulation from satellite images. A data assimilation method is proposed that includes an additional term a(t) to this Lagrangian constancy equation. That term summarises all physical processes other than advection. A cost function is designed, which quantifies discrepancy between satellite data and model values. The cost function is minimised by the BFGS solver with a dual method of data assimilation. The result is the motion field and the additional term a(t). This last component models the forces, other than advection, that contribute to surface circulation. The approach has been tested on Sea Surface Temperature of Black Sea. Results are given on four image sequences and compared with state-of-the-art methods

Fault rheology in an aseismic fold-thrust belt (Shahdad, eastern Iran)

Geodetic observations of aseismic deformation in a thrust belt near Shahdad in eastern Iran have been used to place constraints on the rheology of creeping faults in a thin-skinned thrust belt (<5 km thickness). Creep on shallow and high-angle thrust ramps at the range-front occurs at a steady rate, in response to the topographic gradient across the thrust belt. Parts of these thrust ramps, and the low-angle basal thrust they connect to at depth in a ramp-and-flat geometry, underwent accelerated creep following the nearby Mw 6.6 Fandoqa earthquake in 1998. Estimates of the rate of fault slip and the driving stresses in these two contrasting times reveal a non-linear relationship between the stresses and sliding velocity. The degree of non-linearity rules out bulk shear of a weak layer in the sedimentary section (e.g. evaporites) as the deformation mechanism. Instead, we suggest that the motions are accommodated by slip on faults governed by a friction law with a highly non-linear relationship between shear stress and slip rate (e.g. as predicted by ‘rate and state’ models). The high-angle thrust ramps are responsible for building aspects of the geological and geomorphological signs of active shortening visible at the surface, but the folding preserved in the geology must be accomplished by other methods, possibly during the rapid transient postseismic deformation following nearby earthquakes.We thank James Jackson for use of his field photographs, and for useful dis- cussions. The SAR data used in this study were obtained from the European Space Agency. Our interferograms can be obtained from the corresponding author upon request. The topography data used was the SRTM dataset, which is freely available on the internet. RJ thanks the Marie-Curie ITN ‘iTECC’ for financial support. We thank Gilles Peltzer and two anonymous reviewers for comments that helped improve the manuscript. This work forms part of the NERC- and ESRC-funded project ‘Earthquakes Without Frontiers’.This is the author accepted manuscript. The final version is available from Wiley via http://dx.doi.org/10.1002/2015JB01243

Fault rheology in an aseismic fold-thrust belt (Shahdad, eastern Iran)

Geodetic observations of aseismic deformation in a thrust belt near Shahdad in eastern Iran have been used to place constraints on the rheology of creeping faults in a thin-skinned thrust belt (\textless5 km thickness). Creep on shallow and high-angle thrust ramps at the range front occurs at a steady rate, in response to the topographic gradient across the thrust belt. Parts of these thrust ramps, and the low-angle basal thrust they connect to at depth in a ramp-and-flat geometry, underwent accelerated creep following the nearby Mw 6.6 Fandoqa earthquake in 1998. Estimates of the rate of fault slip and the driving stresses in these two contrasting times reveal a nonlinear relationship between the stresses and sliding velocity. The degree of nonlinearity rules out bulk shear of a weak layer in the sedimentary section (e.g., evaporites) as the deformation mechanism. Instead, we suggest that the motions are accommodated by slip on faults governed by a friction law with a highly nonlinear relationship between shear stress and slip rate (e.g., as predicted by �rate and state� models). The high-angle thrust ramps are responsible for building aspects of the geological and geomorphological signs of active shortening visible at the surface, but the folding preserved in the geology must be accomplished by other methods, possibly during the rapid transient postseismic deformation following nearby earthquakes

Signature extension preprocessing for LANDSAT MSS data

There are no author-identified significant results in this report

Coupling dynamic equations and satellite images for modelling ocean surface circulation

International audienceSatellite image sequences visualise the ocean surface and allow assessing its dynamics. Processing these data is then of major interest to get a better understanding of the observed processes. As demonstrated by state-of-the-art, image assimilation permits to retrieve surface motion, based on assumptions on the dynamics. In this paper, we demonstrate that a simple heuristics, such as the Lagrangian constancy of velocity, can be used and successfully replaces the complex physical properties described by the Navier-Stokes equations for assessing surface circulation from satellite images. A data assimilation method is proposed that adds an acceleration term a(t) to this Lagrangian constancy equation, which summarises all physical processes other than advection. A cost function is designed that quantifies discrepancy between satellite data and model values. This cost function is minimised by the BFGS solver with a dual method of data assimilation. The result is the initial motion field and the acceleration terms a(t) on the whole temporal interval. These values a(t) model the forces, other than advection, that contribute to surface circulation. Our approach was tested on synthetic data and with Sea Surface Temperature images acquired on Black Sea. Results are quantified and compared to those of state-of-the-art methods

Towards an Integrated Assessment of Sea-Level Observations Along the U.S. Atlantic Coast

Sea levels are rising globally due to anthropogenic climate change. However, local sea levels that impact coastal ecosystems often differ from the global trend, sometimes by a factor of two or more. Improved understanding of this regional variability provides insights into geophysical processes and has implications for coastal communities developing resilience to ongoing sea-level rise. This dissertation conducts an investigation of sea level and its contributing processes at multiple spatial scales. Focusing on primarily interannual time-scales and data-driven approaches, new data sources and technologies are utilized to reduce current uncertainties. First, sea-level trends are assessed over the global ocean and at coastlines using data from the recently launched ICESat-2 satellite. These trends agree well with independent measurements, while also filling observational gaps along undersampled coastlines and at high-latitudes. Next, the spatial focus is narrowed to the U.S. East Coast, which is experiencing exceptionally high rates of relative sea-level rise, largely due to land subsidence. By incorporating new state-of-the-art estimates of land-ice melt, an existing Bayesian hierarchical space-time model is expanded to assess the relative contributions of sea surface height and vertical land motion to 20th century relative-sea level change. Model results confirm previous findings that identified regional-scale geological processes as the primary driver of spatial variability in East Coast relative sea level. By rigorously quantifying uncertainties, constraints are placed on the current state of knowledge with clear directions for future research. Finally, small-scale vertical land motion in Hampton Roads, VA is investigated using the remote-sensing technology of Interferometric Synthetic Aperture Radar (InSAR). Two different data sources and processing strategies are implemented which independently reveal substantial rates of vertical land motion that vary over short spatial scales. The results highlight the importance of vertical land motion in exacerbating negative impacts of relative sea-level rise such as flooding and inundation. Overall, this study leverages new spaceborne sensors, an innovative statistical model, and state-of-the-art processing strategies to enhance our understanding of ongoing sea-level change

The future of Earth observation in hydrology

In just the past 5 years, the field of Earth observation has progressed beyond the offerings of conventional space-agency-based platforms to include a plethora of sensing opportunities afforded by CubeSats, unmanned aerial vehicles (UAVs), and smartphone technologies that are being embraced by both for-profit companies and individual researchers. Over the previous decades, space agency efforts have brought forth well-known and immensely useful satellites such as the Landsat series and the Gravity Research and Climate Experiment (GRACE) system, with costs typically of the order of 1 billion dollars per satellite and with concept-to-launch timelines of the order of 2 decades (for new missions). More recently, the proliferation of smart-phones has helped to miniaturize sensors and energy requirements, facilitating advances in the use of CubeSats that can be launched by the dozens, while providing ultra-high (3-5 m) resolution sensing of the Earth on a daily basis. Start-up companies that did not exist a decade ago now operate more satellites in orbit than any space agency, and at costs that are a mere fraction of traditional satellite missions. With these advances come new space-borne measurements, such as real-time high-definition video for tracking air pollution, storm-cell development, flood propagation, precipitation monitoring, or even for constructing digital surfaces using structure-from-motion techniques. Closer to the surface, measurements from small unmanned drones and tethered balloons have mapped snow depths, floods, and estimated evaporation at sub-metre resolutions, pushing back on spatio-temporal constraints and delivering new process insights. At ground level, precipitation has been measured using signal attenuation between antennae mounted on cell phone towers, while the proliferation of mobile devices has enabled citizen scientists to catalogue photos of environmental conditions, estimate daily average temperatures from battery state, and sense other hydrologically important variables such as channel depths using commercially available wireless devices. Global internet access is being pursued via high-altitude balloons, solar planes, and hundreds of planned satellite launches, providing a means to exploit the "internet of things" as an entirely new measurement domain. Such global access will enable real-time collection of data from billions of smartphones or from remote research platforms. This future will produce petabytes of data that can only be accessed via cloud storage and will require new analytical approaches to interpret. The extent to which today's hydrologic models can usefully ingest such massive data volumes is unclear. Nor is it clear whether this deluge of data will be usefully exploited, either because the measurements are superfluous, inconsistent, not accurate enough, or simply because we lack the capacity to process and analyse them. What is apparent is that the tools and techniques afforded by this array of novel and game-changing sensing platforms present our community with a unique opportunity to develop new insights that advance fundamental aspects of the hydrological sciences. To accomplish this will require more than just an application of the technology: in some cases, it will demand a radical rethink on how we utilize and exploit these new observing systems