The FABSPACE 2.0 Project For Geodata-Driven Innovation

Now that the Galileo and Copernicus satellite programmes are entering their operational phase, innovation possibilities in the field of satellite data driven applications are getting wider. Thanks to these two massive investments in technology, European and worldwide companies are starting to benefit from increasing, regular and cheaper (not to say free of charge) data flows, which could lead to the development of new and innovative applications and services in an incredibly vast range of markets, including non-space markets. The exploitation of satellite data, as well as open data (from public authorities in particular) has the potential to generate a lot of innovative solutions. In this context the FabSpace 2.0 project aims at putting the Universities at the front line for the take-off of Earth Observation based applications in Europe and worldwide. This can be pursued by hosting and animating open places dedicated to space and geodata-driven innovation where young developers from the civil society, experienced developers from industry or academic and research institutes, public administrations as well as civil organizations can meet, work together and co-create new tools and business models. They can create an ecosystem fitting (and developed according to) the particularities of geodata-driven innovation, in particular for the emergence of Space data downstream services. In this innovative environment, innovation is driven by the needs of users through the involvement of civil society in the innovation process and in the definition of new challenges. Moreover the actors making innovation will be anonymous civilians (students and researchers in particular) and will thus be at the same time developers and end-users of the applications they develop. That is why the FabSpace 2.0 project is expected to improve the capacity of Universities to generate more innovations and generate positive socio-economic impacts. All partner universities are centers of excellence in research in the field of geomatics and space based information. They are not only offering a highly-qualified human capital likely to generate innovation, but also providing open access to data generated within previous research works. Thus the FabSpace 2.0 project can be a particularly relevant opportunity for research teams to make a step forward towards Science 2.0

Tropospheric ozone column retrieval from OMI data by means of neural networks: a validation exercise with ozone soundings over Europe

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USE OF NEURAL NETWORKS AND SAR INTERFEROMETRY FOR THE AUTOMATIC RETRIEVAL OF TECTONIC PARAMETERS

ABSTRACT From its first application in 1992 to detect the displacement field originated from the Landers earthquake In the recent years InSAR capabilities, together with classic seismological and geophysical data such as strong motion records and GPS, have also been used by geophysicists for the assessment of normal fault models Neural networks have already been recognized as being a powerful tool for inversion procedure in remote sensing applications In this study we propose an innovative approach for the seismic source classification and the fault parameter quantitative retrieval. The originality of such an approach consists in exploiting at the same time the capabilities of neural networks and of InSAR measurements in the described context. The network is trained by using a data set generated by the RNGCHN software and then tested on real measured data. The input of the net consists of a set of features calculated from the interferometric image while the output vector contains the parameters characterizing the fault. Two problems have been analysed. The first one is the identification of the seismic source mechanism. The second one addresses the fault plane parameters estimation. The paper illustrates such a methodology and its validation on a set of experimental data. The experimental set up was composed by three case studies covering different types of faults: normal, strike slip, reverse

an application of cosmo sky med to coastal erosion studies

AbstractStarted in 2009, the COSMOCoast project aims to the investigation of the potential of Remote Sensing in support to the management of coastal areas. Particular attention is paid to the contribution of data acquired from the COSMO-SkyMed constellation, in view of their frequency of acquisitions and ground resolution; in particular this paper aims at assessing the potential of COSMO-SkyMed data for coastline delineation. The results are conceived to be of particular interest for public administration bodies in charge of coastal defense. Keywords: Remote Sensing, Coastal Zones Management, COSMO-SkyMed

Tuning of dye optical properties by environmental effects: a QM/MM and experimental study

The present work is aimed to a deeper investigation of two recently synthesized heteroaromatic fluorophores by means of a computational multilayer approach, integrating quantum mechanics (QM) and molecular mechanics (MM). In particular, dispersion of the title dyes in a polymer matrix is studied in connection with potential applications as photoactive species in luminescent solar concentrators (LSCs). Molecular dynamics simulations, based on accurate QM-derived force fields, reveal increased stiffness of these organic dyes when going from CHCl3 solution to polymer matrix. QM/MM computations of UV spectra for snapshots extracted from MD simulations show that this different flexibility permits to explain the different spectral shapes obtained experimentally for the two different environments. Moreover, the general spectroscopic trends are well reproduced by static computations employing a polarizable continuum description of environmental effects

Data Assimilation of Satellite-Derived Rain Rates Estimated by Neural Network in Convective Environments: A Study over Italy

The accurate prediction of heavy precipitation in convective environments is crucial because such events, often occurring in Italy during the summer and fall seasons, can be a threat for people and properties. In this paper, we analyse the impact of satellite-derived surface-rainfall-rate data assimilation on the Weather Research and Forecasting (WRF) model's precipitation prediction, considering 15 days in summer 2022 and 17 days in fall 2022, where moderate to intense precipitation was observed over Italy. A 3DVar realised at CNR-ISAC (National Research Council of Italy, Institute of Atmospheric Sciences and Climate) is used to assimilate two different satellite-derived rain rate products, both exploiting geostationary (GEO), infrared (IR), and low-Earth-orbit (LEO) microwave (MW) measurements: One is based on an artificial neural network (NN), and the other one is the operational P-IN-SEVIRI-PMW product (H60), delivered in near-real time by the EUMETSAT HSAF (Satellite Application Facility in Support of Operational Hydrology and Water Management). The forecast is verified in two periods: the hours from 1 to 4 (1-4 h phase) and the hours from 3 to 6 (3-6 h phase) after the assimilation. The results show that the rain rate assimilation improves the precipitation forecast in both seasons and for both forecast phases, even if the improvement in the 3-6 h phase is found mainly in summer. The assimilation of H60 produces a high number of false alarms, which has a negative impact on the forecast, especially for intense events (30 mm/3 h). The assimilation of the NN rain rate gives more balanced predictions, improving the control forecast without significantly increasing false alarms

Anthropogenic Heat Flux Estimation from Space: Results of the first phase of the URBANFLUXES Project

H2020-Space project URBANFLUXES (URBan ANthrpogenic heat FLUX from Earth observation Satellites) investigates the potential of Copernicus Sentinels to retrieve anthropogenic heat flux, as a key component of the Urban Energy Budget (UEB). URBANFLUXES advances the current knowledge of the impacts of UEB fluxes on urban heat island and consequently on energy consumption in cities. This will lead to the development of tools and strategies to mitigate these effects, improving thermal comfort and energy efficiency. In URBANFLUXES, the anthropogenic heat flux is estimated as a residual of UEB. Therefore, the rest UEB components, namely, the net all-wave radiation, the net change in heat storage and the turbulent sensible and latent heat fluxes are independently estimated from Earth Observation (EO), whereas the advection term is included in the error of the anthropogenic heat flux estimation from the UEB closure. The project exploits Sentinels observations, which provide improved data quality, coverage and revisit times and increase the value of EO data for scientific work and future emerging applications. These observations can reveal novel scientific insights for the detection and monitoring of the spatial distribution of the urban energy budget fluxes in cities, thereby generating new EO opportunities. URBANFLUXES thus exploits the European capacity for space-borne observations to enable the development of operational services in the field of urban environmental monitoring and energy efficiency in cities. H2020-Space project URBANFLUXES (URBan ANthrpogenic heat FLUX from Earth observation Satellites)investigates the potential of Copernicus Sentinels to retrieve anthropogenic heat flux, as a key component of the UrbanEnergy Budget (UEB). URBANFLUXES advances the current knowledge of the impacts of UEB fluxes on urban heatisland and consequently on energy consumption in cities. This will lead to the development of tools and strategies tomitigate these effects, improving thermal comfort and energy efficiency. In URBANFLUXES, the anthropogenic heatflux is estimated as a residual of UEB. Therefore, the rest UEB components, namely, the net all-wave radiation, the netchange in heat storage and the turbulent sensible and latent heat fluxes are independently estimated from EarthObservation (EO), whereas the advection term is included in the error of the anthropogenic heat flux estimation from theUEB closure. The project exploits Sentinels observations, which provide improved data quality, coverage and revisittimes and increase the value of EO data for scientific work and future emerging applications. These observations canreveal novel scientific insights for the detection and monitoring of the spatial distribution of the urban energy budgetfluxes in cities, thereby generating new EO opportunities. URBANFLUXES thus exploits the European capacity forspace-borne observations to enable the development of operational services in the field of urban environmentalmonitoring and energy efficiency in cities

Anthropogenic heat flux estimation from space: first results

While Earth Observation (EO) has made significant advances in the study of urban areas, there are several unanswered science and policy questions to which it could contribute. To this aim the recently launched Horizon 2020 project URBANFLUXES (URBan ANthrpogenic heat FLUX from Earth observation Satellites) investigates the potential of EO to retrieve anthropogenic heat flux, as a key component in the urban energy budget. The anthropogenic heat flux is the heat flux resulting from vehicular emissions, space heating and cooling of buildings, industrial processing and the metabolic heat release by people. Optical, thermal and SAR data from existing satellite sensors are used to improve the accuracy of the radiation balance spatial distribution calculation, using also in-situ reflectance measurements of urban materials are for calibration. EO-based methods are developed for estimating turbulent sensible and latent heat fluxes, as well as urban heat storage flux and anthropogenic heat flux spatial patterns at city scale and local scale by employing an energy budget closure approach. Independent methods and models are engaged to evaluate the derived products and statistical analyses provide uncertainty measures as well. Ultimate goal of the URBANFLUXES is to develop a highly automated method for estimating urban energy budget components to use with Copernicus Sentinel data, enabling its integration into applications and operational services. Thus, URBANFLUXES prepares the ground for further innovative exploitation of European space data in scientific activities (i.e. Earth system modelling and climate change studies in cities) and future and emerging applications (i.e. sustainable urban planning) by exploiting the improved data quality, coverage and revisit times of the Copernicus data. The URBANFLUXES products will therefore have the potential to support both sustainable planning strategies to improve the quality of life in cities, as well as Earth system models to provide more robust climate simulations. More information on the project can be found at http://urbanfluxes.eu/