15 research outputs found

    Wind-Wave induced velocity in ATI SAR Ocean Surface Currents: First experimental evidence from an airborne campaign

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    Conventional and along-track interferometric (ATI) Synthetic Aperture Radar (SAR) sense the motion of the ocean surface by measuring the Doppler shift of reflected signals. Measurements are affected by a Wind-wave induced Artefact Surface Velocity (WASV) which was modelled theoretically in past studies and has been estimated empirically only once before with Envisat ASAR by Mouche et al., (2012). An airborne campaign in the tidally dominated Irish Sea served to evaluate this effect and the current retrieval capabilities of a dual-beam SAR interferometer known as Wavemill. A comprehensive collection of Wavemill airborne data acquired in a star pattern over a well-instrumented validation site made it possible for the first time to estimate the magnitude of the WASV, and its dependence on azimuth and incidence angle from data alone. In light wind (5.5 m/s) and moderate current (0.7 m/s) conditions, the wind-wave induced contribution to the measured ocean surface motion reaches up to 1.6 m/s upwind, with a well-defined 2nd order harmonic dependence on direction to the wind. The magnitude of the WASV is found to be larger at lower incidence angles. The airborne WASV results show excellent consistency with the empirical WASV estimated from Envisat ASAR. These results confirm that SAR and ATI surface velocity estimates are strongly affected by WASV and that the WASV can be well characterized with knowledge of the wind knowledge and of the geometry. These airborne results provide the first independent validation of Mouche et al., 2012, and confirm that the empirical model they propose provides the means to correct airborne and spaceborne SAR and ATI SAR data for WASV to obtain accurate ocean surface current measurements. After removing the WASV, the airborne Wavemill retrieved currents show very good agreement against ADCP measurements with a root mean square error (RMSE) typically around 0.1 m/s in velocity and 10° in direction

    Mapping forest cover and forest cover change with airborne S-band radar

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    Assessments of forest cover, forest carbon stocks and carbon emissions from deforestation and degradation are increasingly important components of sustainable resource management, for combating biodiversity loss and in climate mitigation policies. Satellite remote sensing provides the only means for mapping global forest cover regularly. However, forest classification with optical data is limited by its insensitivity to three-dimensional canopy structure and cloud cover obscuring many forest regions. Synthetic Aperture Radar (SAR) sensors are increasingly being used to mitigate these problems, mainly in the L-, C- and X-band domains of the electromagnetic spectrum. S-band has not been systematically studied for this purpose. In anticipation of the British built NovaSAR-S satellite mission, this study evaluates the benefits of polarimetric S-band SAR for forest characterisation. The Michigan Microwave Canopy Scattering (MIMICS-I) radiative transfer model is utilised to understand the scattering mechanisms in forest canopies at S-band. The MIMICS-I model reveals strong S-band backscatter sensitivity to the forest canopy in comparison to soil characteristics across all polarisations and incidence angles. Airborne S-band SAR imagery over the temperate mixed forest of Savernake Forest in southern England is analysed for its information content. Based on the modelling results, S-band HH- and VV-polarisation radar backscatter and the Radar Forest Degradation Index (RFDI) are used in a forest/non-forest Maximum Likelihood classification at a spatial resolution of 6 m (70% overall accuracy, κ = 0.41) and 20 m (63% overall accuracy, κ = 0.27). The conclusion is that S-band SAR such as from NovaSAR-S is likely to be suitable for monitoring forest cover and its change

    Airborne S-Band SAR for forest biophysical retrieval in temperate mixed forests of the UK

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    Radar backscatter from forest canopies is related to forest cover, canopy structure and aboveground biomass (AGB). The S-band frequency (3.1–3.3 GHz) lies between the longer L-band (1–2 GHz) and the shorter C-band (5–6 GHz) and has been insufficiently studied for forest applications due to limited data availability. In anticipation of the British built NovaSAR-S satellite mission, this study evaluates the benefits of polarimetric S-band SAR for forest biophysical properties. To understand the scattering mechanisms in forest canopies at S-band the Michigan Microwave Canopy Scattering (MIMICS-I) radiative transfer model was used. S-band backscatter was found to have high sensitivity to the forest canopy characteristics across all polarisations and incidence angles. This sensitivity originates from ground/trunk interaction as the dominant scattering mechanism related to broadleaved species for co-polarised mode and specific incidence angles. The study was carried out in the temperate mixed forest at Savernake Forest and Wytham Woods in southern England, where airborne S-band SAR imagery and field data are available from the recent AirSAR campaign. Field data from the test sites revealed wide ranges of forest parameters, including average canopy height (6–23 m), diameter at breast-height (7–42 cm), basal area (0.2–56 m2/ha), stem density (20–350 trees/ha) and woody biomass density (31–520 t/ha). S-band backscatter-biomass relationships suggest increasing backscatter sensitivity to forest AGB with least error between 90.63 and 99.39 t/ha and coefficient of determination (r2) between 0.42 and 0.47 for the co-polarised channel at 0.25 ha resolution. The conclusion is that S-band SAR data such as from NovaSAR-S is suitable for monitoring forest aboveground biomass less than 100 t/ha at 25 m resolution in low to medium incidence angle rang

    SEASTAR: a mission to study ocean submesoscale dynamics and small-scale atmosphere-ocean processes in coastal, shelf and polar seas

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    High-resolution satellite images of ocean color and sea surface temperature reveal an abundance of ocean fronts, vortices and filaments at scales below 10 km but measurements of ocean surface dynamics at these scales are rare. There is increasing recognition of the role played by small scale ocean processes in ocean-atmosphere coupling, upper-ocean mixing and ocean vertical transports, with advanced numerical models and in situ observations highlighting fundamental changes in dynamics when scales reach 1 km. Numerous scientific publications highlight the global impact of small oceanic scales on marine ecosystems, operational forecasts and long-term climate projections through strong ageostrophic circulations, large vertical ocean velocities and mixed layer re-stratification. Small-scale processes particularly dominate in coastal, shelf and polar seas where they mediate important exchanges between land, ocean, atmosphere and the cryosphere, e.g., freshwater, pollutants. As numerical models continue to evolve toward finer spatial resolution and increasingly complex coupled atmosphere-wave-ice-ocean systems, modern observing capability lags behind, unable to deliver the high-resolution synoptic measurements of total currents, wind vectors and waves needed to advance understanding, develop better parameterizations and improve model validations, forecasts and projections. SEASTAR is a satellite mission concept that proposes to directly address this critical observational gap with synoptic two-dimensional imaging of total ocean surface current vectors and wind vectors at 1 km resolution and coincident directional wave spectra. Based on major recent advances in squinted along-track Synthetic Aperture Radar interferometry, SEASTAR is an innovative, mature concept with unique demonstrated capabilities, seeking to proceed toward spaceborne implementation within Europe and beyond

    EU/US/CTAD Task Force: Lessons Learned from Recent and Current Alzheimer's Prevention Trials

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    At a meeting of the EU/US/Clinical Trials in Alzheimer’s Disease (CTAD) Task Force in December 2016, an international group of investigators from industry, academia, and regulatory agencies reviewed lessons learned from ongoing and planned prevention trials, which will help guide future clinical trials of AD treatments, particularly in the pre-clinical space. The Task Force discussed challenges that need to be addressed across all aspects of clinical trials, calling for innovation in recruitment and retention, infrastructure development, and the selection of outcome measures. While cognitive change provides a marker of disease progression across the disease continuum, there remains a need to identify the optimal assessment tools that provide clinically meaningful endpoints. Patient- and informant-reported assessments of cognition and function may be useful but present additional challenges. Imaging and other biomarkers are also essential to maximize the efficiency of and the information learned from clinical trials
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