In the era of Space Economy, satellite services represent a key element that must be valued and promoted by institutions at local and global level, because they can ensure sustainable economic development and generate benefits for citizens and society. For this reason, they have been recognized among the top strategic priorities of the Italian Space Agency, which deals with the implementation of national space policies.With the main objective of stimulating the growth of the national downstream ecosystem, the Agency has proposed and started the I4DP – Innovation for Downstream Preparation program, which, through cyclical initiatives, offers support to public and private users for the creation of innovative space solutions helping the processes of management and development of the territory and its resources. This work aims to provide a complete picture of the state-of-the-art of the I4DP program and its future prospects, showing the potential effects to support the entire Italian community along the entire value chain of space services and the downstream economic sector, with a focus on selected projects within some identified topics of particular interest such as infrastructure monitoring, the fight against climate change and the adaptation to its effects, precision farming, the sustainability of cities.

The scarcity of a sufficiently large and representative hyperspectral image dataset is a substantial obstacle to the effective development of algorithms for remote sensing applications. Hyperspectral images can provide rich spectral information for various tasks, such as land cover classification, vegetation monitoring, and environmental assessment. However, the limited availability of diverse and well-annotated hyperspectral datasets hinders the development and optimization of these models in this domain. For this purpose, the generation of synthetic hyperspectral images has emerged as a pivotal area of research.This paper aims to introduce a preliminary analysis of various AI-based methodologies specifically crafted to generate synthetic PRISMA hyperspectral images derived from Sentinel-2 data. By exploring innovative approaches, this study aims to develop novel techniques for creating synthetic datasets, providing valuable insights into the potential of synthetic hyperspectral imagery for algorithm training and evaluation in the absence of extensive real-world hyperspectral datasets.

A big flood affected the Emilia-Romagna region (northern Italy) starting from 16 May 2023. During this event, more than 20 rivers burst their banks and about 15 people were killed. A persistent satellite-based mapping was requested by the Italian Department of Civil Protection (DCP) to monitor the time evolution of the Emilia Romagna flood. For this purpose, the X-band SAR data provided by the COSMO-SkyMed constellations (first and second generation) were exploited. This paper proposes a new procedure to map floods using SAR data acquired with different viewing geometries in order to fully exploit the on-demand capability of satellites like COSMO-SkyMed. The procedure includes the tasking of the satellites, the collection of a set of pre-flood images, the selection for each flood image of the most suitable pre-flood ones, and the generation of the flood maps using an automatic algorithm based on change detection. These activities were performed during the May 2023 Emilia-Romagna flood and allowed us to daily provide DCP with flood maps useful to support decision making and assess the damages.

The paper presents the activities of the TUS:CAN project, funded by ASI, the Italian Space Agency, and focuses on the experimental results obtained at the end of the first year. A Google Earth Engine implementation has been designed for spaceborne image collection and handling, spatial resolution enhancement, classification, and cross-validation with airborne hyperspectral image data and in situ spectral signature acquisitions. Initial trials using Sentinel-2 multispectral imagery over a 95 km2area validate the reliability and consistency of a technique to categorize and quantitatively assess natural and man-made land covers, aimed at updating maps and promoting sustainable land use.

PRISMA (PRecursore IperSpettrale della Missione Applicativa) is an innovative Italian Earth Observation mission using a Hyperspectral/Panchromatic instrument based on a pushbroom scanning technique. The PRISMA mission development is completely funded by ASI (Italian Space Agency) and includes the system development program and the related applications and research activities. The system program is in the development phase (ECSS standard C/D phase) in the framework of a contract signed between ASI and an Italian Industries Consortium, including also the system on orbit commissioning. The launch is planned for the beginning of 2018. Thanks to the Low Earth, Sun Synchronous orbit placement, PRISMA will acquire up to 200.000 km2of daily Panchromatic/hyperspectral images within an Area of interest bounded by 180°W÷180°E - 70°S÷70°N, supporting many earth observation applications with relevant data. The Italian Science Community has been involved both in supporting the system development program, mainly for Calibration and Validation activities and algorithm developments, and in promoting research and applications based on Panchromatic/Hyperspectral remote sensed data.

First results of the assimilation of high-resolution Sentinel-1A based soil moisture products in a distributed, physically based, hydrological model are presented. A comprehensive evaluation of the assimilation's impact on discharge predictions is provided. Results are further compared to those obtained when assimilating the lower-resolution ASCAT-based soil moisture product. The exercise was carried out within the MIDA project framework (funded by the Italian Space Agency) aiming at producing root zone soil moisture maps useful for flood risk management applications. The experimental site is the Orba River Catchment (Italy). The period of investigation is October 2014-February 2015. Using a relatively simple data assimilation technique (Nudging) the results of our case study show that overall the assimilation of currently available Sentinel-1 data only marginally improves discharge simulations. However, the impact becomes more significant when specifically considering predictions of high flow. Further improvements are expected when both Sentinel-1A and B data will be available.

The utility of the images supplied by synthetic aperture radar (SAR) systems for flood mapping was demonstrated by several literature studies and the use of SAR data is presently well-established in operational services for inundation management. However, because of the limited SAR image swath and the need of programming SAR acquisitions in advance, some events might be missed. Nowadays a number of satellite SAR instruments are operative and this allows for a combined use of different sensors in order to cover wide river basins and, when different instruments observe the same area, to potentially improve the accuracy of flood extent maps. To fully exploit these possibilities, the flood mapping algorithm should be able to process data provided by radars working at different frequencies and observing the Earth with different incidence angles, i.e., should be robust and transferable. In order to analyze the possible synergies between X-band and C-band sensors, in this work we present some results obtained through a joint use of an X-band instrument as COSMO-SkyMed and a C-band one as Sentinel-1 for flood monitoring performed during the Po River (Italy) flood occurred in November 2014. We focus on the modifications made to an automatic algorithm originally developed for a quick classification of COSMO-SkyMed in order to increase its reliability, as well as it robustness and transferability.

This paper describes two examples of synergistic management of EO based services for flood emergency monitoring. The first relates to the benefits of collaboration between decision makers, end users and experts reporting the case of the November 2014 Liguria and Po River flooding, when early activation, prior to the occurrence of the flood, was made possible and the second shows the benefits of the synergy between Sentinel-1 (S-1) and COSMO-SkyMed (CSK) contributing missions for monitoring floods at national scale. The two examples are referred to flood monitoring but the conclusions can be easily extended to other risks.

Carbon dioxide (CO2) emissions from industrial sources is one of the main anthropogenic contributors to the greenhouse effect. We investigated the potentiality of satellite hyperspectral sensors, as the Hyperspectral Precursor of the Application Mission (PRISMA) — an optical Earth Observation satellite mission funded by the Italian Space Agency (ASI) — to evaluate significant amounts of CO2concentrations in the lower troposphere. Using synthetic hyperspectra at top of atmosphere, sensitivity analysis to the retrieval of CO2concentrations was performed in the weak (1610 and 1570 nm) and strong (2010 and 2050 nm) absorption bands. Considering the designed spectral and radiometric features of PRISMA, results of the analysis show a relative uncertainty between 3 and 15 % on the retrieval of CO2concentrations between 390 to 5100 ppmv.

The latest generation of synthetic aperture radar (SAR) systems allows providing emergency managers with near real time flood maps characterized by a very high spatial resolution. Near real time flood detection algorithms generally search for regions of low backscatter, thus assuming that floodwater appears dark in a SAR image. It is well known that this assumption is not always valid. For instance, in urban areas, the double bounce backscattering involving ground and vertical walls produce high radar return that can be further increased by the presence of the highly reflective floodwater. In addition, even mapping bare or scarcely vegetated inundated terrains, or crops totally submerged by water can turn out to be a difficult task. In fact, in the presence of significant wind that roughens the water surface, floodwater can appear bright in SAR images. This paper proposes possible strategies to cope with flood mapping using SAR data in urban areas and in the presence of significant wind. In particular, the use of the interferometric coherence for floodwater detection in urban areas and the use of an electromagnetic model able to simulate the radar return from shallow water as function of the wind field are proposed.

In this work, an automatic method to distinguish, in X-band SAR images such as those supplied by Cosmo-SkyMed, water surfaces (either flooded, or permanent water bodies) from artifacts due to heavy precipitation, is designed to improve flood detection accuracy. The method, mainly based on the fuzzy logic, consists of two main steps, i.e., the detection of low backscatter areas and the classification of each dark object present in the considered SAR image. The algorithm uses ancillary data, such as a local incidence angle map and a Land Cover map. Through the fuzzy logic, it integrates different rules for the detection of low backscatter areas (based on the standard deviation of the backscattering coefficient and on a well-established radar backscattering model), as well as different rules for the classification of the low backscatter (dark) areas (i.e., to distinguish water surfaces from artifacts) based on their geometrical and shape features and on both land cover and local incidence angle.

The management of a flood event requires singling out the affected area, quantifying the damages and programming an effective rescue plan. This requires rapid and easy access to all the geographical and observational information available for the target area. Optical imagery allow the identification of land uses, critical infrastructures and the extraction of important information to quantify the actual vulnerability of the area. In this case, the main advantage of satellite imagery is the much higher refresh rate with respect to classical in-situ surveys. When floods occur, the detection of flooded areas allowed by SAR observations such as those provided by Cosmo-SkyMed, helps in rapid and effective evaluation of the damage and organization of the management of the crisis. Here we present an integrated system developed by the team of the Italian Space Agency pilot project “Opera”. The system allows the end user to integrate multispectral high resolution imagery and Cosmo-SkyMed products, in a 3-D environment, providing all the tools to virtually survey the observed area and extract quantitative information for many features relevant to the emergency management. The system has been tested in real time on a prolonged flooding event occurred in Januray 2010 in the Shkoder plain in Albania.

This paper assesses the impact of soil moisture indexes that can be retrieved via different techniques from thermal IR satellite observations on the re-initialization of flood prediction models. The work considers 2 types of index, one based on thermal inertia, and the second that puts together satellite derived LST and a simplified energy balance model using a variational data assimilation schemes. Results are discussed with reference to an operational flood forecasting framework. Case studies are three catchments in Italy.

On April 6th2009 a Mw=6.3 earthquake struck the area around the city of L'Aquila in Italy. SAR systems have been proven to be valuable sensors for analyzing the effect of earthquakes and monitoring post-seismic displacements. Due to the low deformation rate, the study of post-seismic events requires the use of a multi-temporal InSAR approach. COSMO/SKYMED is a constellation of SAR sensors of 4 X-band sensors operative also for the civilian use. Thanks to the availability of a stack of ascending acquisitions, ad hoc programmed by ASI on the area stricken by the earthquake, it was possible to provide post-seismic deformation maps by using two different multi-temporal interferometric approaches: the SPINUA and SBAS techniques. The work is carried out in the framework of the MORFEO project dedicated to the monitoring of the landslides risk by means of Earth Observation data. The displacement maps related to the post-seismic activity are presented and commented. The results clearly show the potentiality of the COSMO/SKYMED constellation use for emergency monitoring.

COSMO-SkyMed is a Dual-Use (Civilian and Defence) End-to-End Earth Observation System aimed at establishing a global service supplying provision of data, products and services relevant to a wide range of applications, such as Risk Management, Scientific and Commercial Applications and Defence Applications. The system consists of a constellation of four LEO mid-sized satellites, each equipped with a multi-mode high-resolution SAR operating at X-band. Three out of four COSMO-SkyMed satellites have been successfully launched, while the remaining satellite will be deployed within 2010. The first two satellites have been launched in 2007 while COSMO-SkyMed-3 has been launched on October 25th2008. Since its launch COSMO-SkyMed-3 has been put in an orbital position at 67,5° from COSMO-SkyMed-2, in the so-called “one-day interferometry configuration”. Since then COSMO-SkyMed-2 and COSMO-SkyMed-3 are providing a interferometric pairs for a wide range of applications.

This paper illustrates some applications of COSMO-SkyMed (CSK) observations for rapid mapping of flooded areas and damages in small to medium size catchments. The results presented here have been obtained within the framework of the project "OPERA Civil protection from floods" funded by the Italian Space Agency and run by a team of scientific research centres and private companies. The project aims to the systematic evaluation of the added value of the use of Earth Observation techniques into operational flood prediction chains. Due to the specific geomorphology of Italy, the focus is mainly on flash floods on small sized river catchments. Monitoring and modelling processes at proper space-time scales in this environment raise several issues to be solved, compared to applications in larger river basins. Here we address some related to the suitable use of CSK imagery.

The COSMO-SkyMed mission is expected to give a fundamental contribution for flood mapping, because of the high revisit time and throughput achieved by the four satellites that form the constellation. To study the potentiality of COSMO-SkyMed radar data for this purpose, two inundation events are analyzed in this paper, namely the flood occurred in Myanmar in May 2008 and the event that took place in the city of Alessandria (Italy) in April 2009. For the first event, two radar images were considered, one temporally close to the peak of the event, and the other one acquired one week later. As for the Alessandria flood, a time series of images was available, so that an attempt to monitor the temporal evolution of the inundation was accomplished.

Image co-registration is basilar for interferometry SAR remote sensing applications. This paper describes a parallel implementation based on the Farm skeleton using the MPI library for the co-registration module of SAR Toolbox software.

COSMO-SkyMed constellation will acquire data from its four SAR satellites in several image modes, and will generate focused data products. As images will be acquired at fine geometric resolution and will cover medium sized swath, the SAR processing involved will result well suited to parallel programming implementation.

The COSMO-SkyMed (Constellation of Small satellites for the Mediterranean basin Observation) constellation is a project of the Italian Space Agency (ASI) tailored for risk management, coastal zone monitoring and sea pollution in a dual use approach (military and civil applications). The COSMO-SkyMed payload is constituted of a fixed antenna with electronic scanning capabilities in both the azimuth and the elevation planes. It has been designed to implement three different operation modes in order to acquire the images at the required resolution: Spotlight mode, Stripmap mode and ScanSAR mode. This paper describes the algorithms implemented to focus images acquired in the above three different modes together with the first results obtained using simulated and real data. Telespazio, in cooperation with Consorzio Innova and Digimat, is the prime-contractor of the COSMO-SkyMed CREDO project, in which is foreseen the development of a SAR ground processing chain.