Wind Speed Estimation From CYGNSS Using Artificial Neural Networks

In this article, a retrieval algorithm based on the use of an artificial neural network (ANN) is proposed for wind speed estimations from cyclone global navigation satellite system (CYGNSS). The delay/Doppler map average and the leading edge slope observables, derived from CYGNSS delay/Doppler maps, are used as inputs to the network, along with geographical, geometry, and hardware antenna information. The derivation of the optimal number of hidden layers and neurons is obtained using statistical metrics of agreement between the CYGNSS data and the wind matchups obtained from modelled winds output by the wavewatch 3 (WW3) model. A cumulative distribution function (CDF) matching step is applied to the network outputs, to impose that the CDF of the retrievals matches that of the matchups. The resulting wind speeds are unbiased with respect to WW3 modeled winds, and deliver a global root mean square (RMS) difference (RMSD) of 1.51 m/s, over a dynamic range of wind speeds up to 32 m/s. The obtained RMSD is the lowest among those seen in literature for wind speed retrievals from CYGNSS. A comparison is carried out between the winds retrieved from the ANN approach and those derived using the fully developed sea approach, which represent the CYGNSS baseline wind product. The comparison highlights that the ANN approach outperforms the baseline approach for both low and high wind speeds and removes most of the geographical biases between baseline winds and WW3 winds seen in monthly maps of wind speeds. The ANN approach could well be applied to the entire CYGNSS dataset to generate an enhanced wind speed product

First spaceborne observation of sea surface height using GPS-reflectometry

An analysis of spaceborne Global Positioning System reflectometry (GPS-R) data from the TechDemoSat-1 (TDS-1) satellite is carried out to image the ocean sea surface height (SSH). An SSH estimation algorithm is applied to GPS-R delay waveforms over two regions in the South Atlantic and the North Pacific. Estimates made from TDS-1 overpasses during a 6 month period are aggregated to produce SSH maps of the two regions. The maps generally agree with the global DTU10 mean sea surface height. The GPS-R instrument is designed to make bistatic measurements of radar cross section for ocean wind observations, and its altimetric performance is not optimized. The differences observed between measured and DTU10 SSH can be attributed to limitations with the GPS-R instrument and the lack of precision orbit determination by the TDS-1 platform. These results represent the first observations of SSH by a spaceborne GPS-R instrument

Active packaging for table grapes: Evaluation of antimicrobial performances of packaging for shelf life of the grapes under thermal stress

Abstract The paper reports the formulation of an active packaging based on PET coated with a Layered Double Hydroxide (LDH) hosting 2-acetoxybenzoic anion (salicylate) as antimicrobial molecule. The release of the molecule anchored to the LDH, compared to the molecule free dispersed into the coating, appeared much slower. Permeability of carbon dioxide and oxygen through the packaging at different temperatures was evaluated, as well as the capability of the active material to inhibit Pseudomonas, Listeria and Lactobacillus. Table grape was stored in thermal stress conditions (i.e. 10 °C) into the active packaging and the total mesophilic aerobic count and yeasts and moulds population was evaluated up to 14 days of storage. The experimental results were used for a theoretical prediction of shelf life of the packed grapes and compared with the same fruit packed into untreated material. Global and specific migration of salicylic acid from the active packaging demonstrated, in compliance with the migration limits of the EU regulation, the suitability of the considered material for food contact

The GRSS standard for GNSS-reflectometry

In February 2019 a Project Authorization Request was approved by the Institute of Electrical and Electronics Engineers (IEEE) Standards Association with the title “Standard for Global Navigation Satellite System Reflectometry (GNSS-R) Data and Metadata Content”. A Working Group has been assembled to draft this standard with the purpose of unifying and documenting GNSS-R measurements, calibration procedures, and product level definitions. The Working Group (http://www.grss-ieee.org/community/technical-committees/standards-or-earth-observations/) includes members, collaborators, and contributors from academia, international space agencies, and private industry. In a recent face-to-face meeting held during the ARSI+KEO 2019 Conference, the need was recognized to develop a standard with a wide range of operations, providing procedure guidelines independently of constraints imposed by current limitations on geophysical parameters retrieval algorithms. As such, this effort aims to establish the fundamentals of a potential virtual network of satellites providing inter-comparable data to the scientific community.Peer ReviewedPostprint (author's final draft

Remote Sensing of Forest Biomass Using GNSS Reflectometry

In this study, the capability of Global Navigation Satellite System Reflectometry in evaluating forest biomass from space has been investigated by using data coming from the TechDemoSat-1 (TDS-1) mission of Surrey Satellite Technology Ltd. and from the Cyclone Satellite System (CyGNSS) mission of NASA. The analysis has been first conducted using TDS-1 data on a local scale, by selecting five test areas located in different parts of the Earth's surface. The areas were chosen as examples of various forest coverages, including equatorial and boreal forests. Then, the analysis has been extended by using CyGNSS to a global scale, including any type of forest coverage. The peak of the Delay Doppler Map calibrated to retrieve an "equivalent" reflectivity has been exploited for this investigation and its sensitivity to forest parameters has been evaluated by a direct comparison with vegetation optical depth (VOD) derived from the Soil Moisture Active Passive L-band radiometer, with a pantropical aboveground biomass (AGB) map and then with a tree height (H) global map derived from the Geoscience Laser Altimeter System installed on-board the ICEsat satellite. The sensitivity analysis confirmed the decreasing trend of the observed equivalent reflectivity for increasing biomass, with correlation coefficients 0.31 ≤ R ≤ 0.54 depending on the target parameter (VOD, AGB, or H) and on the considered dataset (local or global). These correlations were not sufficient to retrieve the target parameters by simple inversion of the direct relationships. The retrieval has been therefore based on Artificial Neural Networks making it possible to add other inputs (e.g., the incidence angle, the signal to noise ratio, and the lat/lon information in case of global maps) to the algorithm. Although not directly correlated to the biomass, these inputs helped in improving the retrieval accuracy. The algorithm was tested on both the selected areas and globally, showing a promising ability to retrieve the target parameter, either AGB or H, with correlation coefficients R ≃ 0.8

Scouting for Climate Variable with Small Satellites

HydroGNSS is a small satellite mission under the new ESA Scout programme tapping into NewSpace, within ESA’s FutureEO programme. The mission will use an innovative GNSS-Reflectometry instrument to collect parameters related to the Essential Climate Variables (ECVs): soil moisture, inundation, freeze/thaw, biomass, ocean wind speed and sea ice extent. GNSS-Reflectometry is a type of bistatic radar utilizing abundant GNSS signals as signals of opportunity, empowering small satellites to provide measurement quality associated with larger satellites. The HydroGNSS instrument introduces novel measurements compared to its predecessors on UKSA TechDemoSat-1 and NASA CYGNSS missions. These include: the acquisition of Galileo(E1) reflections, and firsts such as dual- polarization, complex ‘coherent channel’ (amplitude/phase) and second frequency (L5/E5a) acquisitions. These measurements enable HydroGNSS to innovate the L2 products, e.g. improving the ground resolution and soil moisture measurement, as dual-polarized reflections allow the discrimination of vegetation effects from soil moisture. HydroGNSS will: ● Complement and potentially gap fill other missions sensing soil moisture e.g. ESA’s SMOS and NASA’s SMAP missions. ● Complement ESA’s Biomass mission addressing coverage restrictions over Europe, North and Central America. ● Expand GNSS-Reflectometry techniques. ● Lay the foundations for a future constellation capable of offering continuity in high spatial-temporal resolution observations of the Earth’s weather and climate

How future surgery will benefit from SARS-COV-2-related measures: a SPIGC survey conveying the perspective of Italian surgeons

COVID-19 negatively affected surgical activity, but the potential benefits resulting from adopted measures remain unclear. The aim of this study was to evaluate the change in surgical activity and potential benefit from COVID-19 measures in perspective of Italian surgeons on behalf of SPIGC. A nationwide online survey on surgical practice before, during, and after COVID-19 pandemic was conducted in March-April 2022 (NCT:05323851). Effects of COVID-19 hospital-related measures on surgical patients' management and personal professional development across surgical specialties were explored. Data on demographics, pre-operative/peri-operative/post-operative management, and professional development were collected. Outcomes were matched with the corresponding volume. Four hundred and seventy-three respondents were included in final analysis across 14 surgical specialties. Since SARS-CoV-2 pandemic, application of telematic consultations (4.1% vs. 21.6%; p < 0.0001) and diagnostic evaluations (16.4% vs. 42.2%; p < 0.0001) increased. Elective surgical activities significantly reduced and surgeons opted more frequently for conservative management with a possible indication for elective (26.3% vs. 35.7%; p < 0.0001) or urgent (20.4% vs. 38.5%; p < 0.0001) surgery. All new COVID-related measures are perceived to be maintained in the future. Surgeons' personal education online increased from 12.6% (pre-COVID) to 86.6% (post-COVID; p < 0.0001). Online educational activities are considered a beneficial effect from COVID pandemic (56.4%). COVID-19 had a great impact on surgical specialties, with significant reduction of operation volume. However, some forced changes turned out to be benefits. Isolation measures pushed the use of telemedicine and telemetric devices for outpatient practice and favored communication for educational purposes and surgeon-patient/family communication. From the Italian surgeons' perspective, COVID-related measures will continue to influence future surgical clinical practice

Infected pancreatic necrosis: outcomes and clinical predictors of mortality. A post hoc analysis of the MANCTRA-1 international study

: The identification of high-risk patients in the early stages of infected pancreatic necrosis (IPN) is critical, because it could help the clinicians to adopt more effective management strategies. We conducted a post hoc analysis of the MANCTRA-1 international study to assess the association between clinical risk factors and mortality among adult patients with IPN. Univariable and multivariable logistic regression models were used to identify prognostic factors of mortality. We identified 247 consecutive patients with IPN hospitalised between January 2019 and December 2020. History of uncontrolled arterial hypertension (p = 0.032; 95% CI 1.135-15.882; aOR 4.245), qSOFA (p = 0.005; 95% CI 1.359-5.879; aOR 2.828), renal failure (p = 0.022; 95% CI 1.138-5.442; aOR 2.489), and haemodynamic failure (p = 0.018; 95% CI 1.184-5.978; aOR 2.661), were identified as independent predictors of mortality in IPN patients. Cholangitis (p = 0.003; 95% CI 1.598-9.930; aOR 3.983), abdominal compartment syndrome (p = 0.032; 95% CI 1.090-6.967; aOR 2.735), and gastrointestinal/intra-abdominal bleeding (p = 0.009; 95% CI 1.286-5.712; aOR 2.710) were independently associated with the risk of mortality. Upfront open surgical necrosectomy was strongly associated with the risk of mortality (p < 0.001; 95% CI 1.912-7.442; aOR 3.772), whereas endoscopic drainage of pancreatic necrosis (p = 0.018; 95% CI 0.138-0.834; aOR 0.339) and enteral nutrition (p = 0.003; 95% CI 0.143-0.716; aOR 0.320) were found as protective factors. Organ failure, acute cholangitis, and upfront open surgical necrosectomy were the most significant predictors of mortality. Our study confirmed that, even in a subgroup of particularly ill patients such as those with IPN, upfront open surgery should be avoided as much as possible. Study protocol registered in ClinicalTrials.Gov (I.D. Number NCT04747990)

Investigating the Effect of Ocean Waves on GNSS-R Microwave Remote Sensing Measurements

Global Navigation Satellite System-Reflectometry (GNSS-R) is an innovative technique for ocean remote sensing. It exploits signals of opportunity from navigation constellations, to look primarily at the ocean surface roughness. This dissertation investigates the capabilities of GNSS-Reflectometry to convey information about sea state, and the response of GPS reflected signals to different wind and wave conditions. This is done through the use of real GPS-R data, as well as through simulations of the scattering of GPS signals from realistic ocean surfaces. A retrieval of ocean roughness parameters is carried out on four GNSS-R datasets, collected onboard the UK-DMC Satellite. Measured Delay-Doppler Maps (DDMs) from GPS-R data are least-square fitted to DDMs simulated using a theoretical (Zavorotny-Voronovich, or Z-V) model. The retrieved parameters are compared and validated against measurements from co-located NDBC buoys, and theoretical calculations, and a reasonable agreement is observed.A GPS scattering simulator is then presented, that uses explicit 3D ocean surface representations, and an innovative facet-based polarimetric scattering model, called the Facet Approach (FA). The results of the GPS scattering simulator are first analysed in the spatial domain, as 2D maps of normalized radar cross section and polarization ratio. These maps exhibit clear features related to the explicit waves of the underlying sea surface.A detailed analysis of noise-free idealized DDMs of both scattered GPS power and polarization ratio is then carried out for a variety of different ocean surfaces, both linearand non-linear. This analysis stresses in particular the importance of wave directionality as a crucial parameter that influences the DDM sensitivity to sea surface roughnessii and wave direction, and the polarization effects on the scattered signal. It is revealed that polarization is another important parameter, as it can convey information on wave direction and directionality, and potentially be used to identify nonlinearities on the sea surface. Finally, an investigation of subsets of noise-free idealized DDMs, computed at a high DD resolution, is presented, and its potentials as a tool for detecting the explicit waves on the sea surface are highlighted.The research and analyses of this PhD dissertation represent novel contributions to the field of GPR-Reflectometry. In particular, the analysis of satellite GPS-R data is the first one that makes use of the whole DDM, and of data collected onboard a satellite. The results from the GPS scattering simulator provide a comprehensive description of how and to what extent different parameters of the ocean surface, linked to wind and waves, influence the scattering of GPS signals. Furthermore, they identify polarization as a new crucial parameter for future GNSS-R missions, since it provides additional information about sea-state, and might be used as a potential indicator of sea surface nonlinearities

Bayesian wind speed estimation conditioned on significant wave height for GNSS-R ocean observations

Spaceborne Global Navigation Satellite System reflectometry observations of the ocean surface are found to respond to components of roughness forced by local winds and to a longer wave swell that is only partially correlated with the local wind. This dual sensitivity is largest at low wind speeds. If left uncorrected, the error in wind speeds retrieved from the observations is strongly correlated with the significant wave height (SWH) of the ocean. A Bayesian wind speed estimator is developed to correct for the long-wave sensitivity at low wind speeds. The approach requires a characterization of the joint probability of occurrence of wind speed and SWH, which is derived from archival reanalysis sea-state records. The Bayesian estimator is applied to spaceborne data collected by the Technology Demonstration Satellite-1 (TechDemoSat-1) and is found to provide significant improvement in wind speed retrieval at low winds, relative to a conventional retrieval that does not account for SWH. At higher wind speeds, the wind speed and SWH are more highly correlated and there is much less need for the correction