INTRODUCTIONThe IRIDE Project is a space-based observation program initiated under the framework of Italy’s National Recovery and Resilience Plan (PNRR) which aims to establish satellite constellations for Earth observation. It is poised to upgrade Italy's Earth observation capabilities, delivering a wealth of satellite products that will contribute to the nation's approach to environmental monitoring, disaster management, and resource utilization. The IRIDE Project will be completed by 2026 and is composed of the following main components:Upstream Segment: This segment consists of a bundle of six constellations of satellites that will make up the IRIDE space segment.The satellites will be equipped with a variety of imaging sensors, including multispectral, hyperspectral and SAR sensors. They will be placed in low Earth orbit (LEO), which will allow them to provide frequent and detailed images of the Earth.Downstream Segment: This segment encompasses the ground infrastructure that will be used to operate the satellites and to collect, process and distribute the data acquired by the satellites. This part includes the ground stations, the FOS, the PDGS and data access Marketplace including the Cyber Italy.Service Segment: This segment consists of the services that will be provided to the Italian public administration. These services will include EO based data products, analytics, and relevant applications.This paper will describe specifically the suite of EO products and related main characteristics offered by the IRIDE six constellations of satellites: HEO, EAGLET-2, NIMBUS-VHR, NIMBUS-SAR, NOX and PLATINO-HYP.

IRIDE is a new Italian space project, aimed at strengthening the country's Earth observation capabilities to support environmental monitoring, disaster management, security and resources management.IRIDE is funded by Italy's National Recovery and Resilience Plan (PNRR) and the Piano Nazionale Complementare (PNC). The total envelope of the programme is 1.070 Meur. The European Space Agency (ESA) manages the Project implementation with the support of the Agenzia Spaziale Italiana (ASI).The programme is executed in the timeframe from December 2021 until June 2026. This includes the fabrication, deployment, and operational validation of all systems components. As this is a very challenging schedule, IRIDE relies mostly on existing capabilities within the Italian Space Industry, fostering its competences in commercial production.IRIDE will rely on six satellites constellations equipped with various imaging sensors, spanning the electromagnetic spectrum from optical to hyperspectral and SAR domains, to provide comprehensive data coverage of the Earth's surface.The system is composed by the following main components: the Upstream Segment, the Downstream Segment and the Service Segment.

The amount of remote sensing data available from different satellite platforms is increasing freely and openly every day. Thus, raising multiple issues which require innovative approaches to organize, manage, and analyze remote-sensing imagery. Discrete Global Grid Systems (DGGS) currently under study by the OGC DGGS SWG, can in principle act as a unified framework for EO data integration, multisource data fusion and cloud computing on a global scale. This study assesses different DGGS candidates: H3, rHEALpix, ISEA7H, ISEA4T/D, etc., analyzing their main features with the perspective of potentially using them for Copernicus Sentinel-2 mission. We then discuss the first outcomes for the different use cases considered and their applicability regarding the benefits and limitations of the DGGS, with a view to setting up a dedicated demonstrator.

Air pollution and its effects on human health pose a significant challenge in modern society. The PRIMARY (PRIsma for Monitoring AiR quality) research project aims to utilize the capabilities of the Italian Space Agency's (ASI) PRISMA (PRecursor HyperSpectral Application Mission) to enhance air quality monitoring, particularly in urban areas. In particular, the project focuses on the exploitation of the hyperspectral PRISMA data to obtain detailed qualitative and quantitative data on atmospheric aerosol load and composition in urban environments. Current satellite-based characterization of particulate matter is limited due to spatial resolution constraints and to the complexities of the underlying inverse problem involving multiple variables. The PRIMARY project addresses the first issue through the decametric spatial resolution of PRISMA images, while the second issue is tackled by leveraging artificial intelligence approaches.

There are growing and evolving expectations from the Earth Observation (EO) Community for merging an increasing number of input data streams recorded with the various space based Multi-Spectral (MS) High Resolution (HR) EO mission instruments. The various agencies and industries are now delivering Analysis Ready Data (ARD) aiming at stacking together multi source data. One critical objective of ARD is to enable the monitoring of rapid and subtle changes. This category of applications sets some strong requirements regarding the quality of the surface reflectance harmonization in the time series. In the context of Sentinel-2 / Landsat 8, this paper proposes a comprehensive analysis of the Sen2Like processing. It shows that it is possible to increase significantly the geometric coregistration accuracy and to ensure an appropriate cross calibration. However, some issues persist and are due to directional effects. These are partially corrected with the current approach but remain a major source of noise in time series.

Sen2Cor is a Level-2A processor designed to correct Sentinel-2 Level-1C products from the effects of the atmosphere in order to deliver a Level-2A surface reflectance product. ESA has been using Sen2Cor for systematic Level-2A processing of Sentinel-2 acquisitions over Europe since June 2017. It has since then been successfully integrated into Sentinel-2 ground segment (PDGS) with a global production over the World started in December 2018. In this manuscript, the Level-2A product and algorithm are presented. The performance of this operational Level-2A product is described in terms of cloud screening accuracy and atmospheric correction accuracy. Finally, the on-going parallel developments aimed at improving the product quality at global scale in terms of cloud screening and atmospheric correction are discussed.

Sen2Like is a processor designed to produce harmonized Level 2 surface reflectance dataset considering as reference Sentinel-2 data. Sen2Like fits with the on-going and growing expectations of the Earth Observation (EO) Community for the merging of an increasing number of input data streams from the various Multi-Spectral (MS) High Resolution (HR) EO mission instruments. The harmonization is an essential processing stage in order to fully exploit all the potential of physical data in the context of land use /land change classification/detection. However, because harmonization addresses several issues in the field of atmospheric/geometric/directional effects/spectral difference corrections, there is not a standard way to achieve this objective. To initiate this project, the Landsat 8 (LS8) mission has been considered as the most appropriate. The Sen2Like processor is now delivering S2/LS8 Analysis Ready Data (ARD) on S2 tiling system at a map resolution of 30 m and 10 m. After a description of the algorithms involved in Sen2Like, this paper discusses testing and validation results.

Sentinel-2 is an Earth Observation optical mission developed and operated by the European Space Agency (ESA) in the frame of the Copernicus program of the European Commission. The mission consists on a MultiSpectral Instruments (MSI) on board a constellation of two satellites flying on the same orbit but phased at 180°: Sentinel-2A launched in June 2015 and Sentinel-2B launched in March 2017. It covers the Earth's land surfaces and inland and coastal waters every five days at the equator under the same viewing conditions with high spatial resolution and wide field of view. Accurate radiometric calibration is key to the success of the mission; therefore, in-orbit calibration and validation activities are conducted within the Sentinel-2 Mission Performance Centre (MPC), including a consortium of Expert Support Laboratories (ESL). The Database of Imaging Multispectral Instrument and Tool for Radiometric Intercomparison (DIMITRI) is used to perform the vicarious validation of Level-l products delivered to users. The aims of this validation are 1) to assess the quality of the data product at Level-1, 2) to monitor the evolution of the radiometry of both instruments and 3) to ensure that the products meet the mission requirement accuracy. Three vicarious methods are used, such as Rayleigh scattering, Desert Pseudo- Invariant Calibration Sites (PICS) and Sensor-to-Sensor intercalibration methods. Although the results indicate good stability and performance of both sensors MSI-A/B, a slight discrepancy between them of ~1 % over desert sites could be observed. Slight decrease of band B8A (865 nm) signal over Algeria-3 site has been detected since April 2017. This effect seems to be related to the impact of human and industry activities near the area. Radiometric performances and image quality of Sentinel-2 MSI-A/B level-1C products appear stable and meet the mission requirements.

As part of the Copernicus programme of the European Commission (EC), the European Space Agency (ESA) operates the Sentinel-2 mission that acquires high spatial resolution optical imagery. The consistency of the image time series is ensured by some specific performance requirements such as multi-temporal spatial registration and radiometric stability, routinely monitored by the Sentinel-2 Mission Performance Centre (S2MPC). The products also provide a rich set of metadata and auxiliary data to support high-level processing activities. This presentation provides a description of the main level-1 products calibration and validation activities, performed by the S2MPC including several Expert Support Laboratories (ESL). Measured performances and analysed results show the good quality of the mission products both in terms of radiometry and geometry. The current performances for Sentinel-2A and Sentinel-2B are compared to mission product quality requirements.

This paper is aimed to outline the possible uses of SAR derived wind fields in coastal meteorology, taking advantage of two running projects: the first of meteorological flavor, aimed to measure and reproduce the surface wind field in a small coastal area; the second to investigate the possibilities offered by the combined use of simultaneous COSMO-SkyMed and RADARSAT-2 SAR images in the description of the wind field in the same area. The main issues faced in this study and partially solved are: the development of a suitable methodology to extract the wind field from SAR images at different bands, polarization, incidence angle; the understanding of the potentialities of the SAR derived winds to catch the patterns of the spatial variability of the wind over the coastal area; the assessment of the SAR derived wind from comparisons with the simultaneous experimental data. Of course, the results presented here are not exhaustive, but only aim to track the ongoing research on the topic of wind over local coastal areas.

The monitoring of cataloged landfills and the detection of uncontrolled dump sites is becoming a crucial environmental issue in all European countries. Remote Sensing application has been demonstrated to be helpful in mitigating the problem of landfills monitoring and in the continuous surveillance of known waste disposal sites. In previous works [1][2][3], the suitability of EO data exploitation, coming from SAR and Optical sensors, has been tested to be an important key factor in providing valid information to the local stakeholders for the identification, classification and monitoring of contaminated sites using non-invasive methods. The present paper aims to describe the consolidated and validated results obtained in the framework of the SIMDEO project, co-funded by the Italian Space Agency (ASI) and Euro Soft srl (contract n. I/055/11/0), detailing the algorithms adopted and describing the output products validated using ground-truth data.

The monitoring of landfills and the detection of illegal and uncontrolled dump sites is a central environmental issue in all developed countries and a critical problem particularly in the southern regions of Italy. The consequences of the persisting uncontrolled disposal of wastes are now manifest after the occurrence of numerous critical emergencies (e.g. Naples 2009 and 2010). Furthermore, the strong infiltration of mafia-type criminal organizations in the legal process of waste disposal has led to even more critical conditions. The number of illegal landfills in Italy is constantly increasing; the last estimate made in 2010 has listed more than 5000 not authorized contaminated areas covering 2000 hectares of surface but there is the suspicion that these figures are strongly underestimated. Very recently Italy has been also threatened by the European Commission with €56m fine for having violated the landfill directives in not following the appropriate waste treatment. This work aims at presenting a new synergic approach based on EO optical and SAR data for detecting illegal landfills and monitoring existing and known waste disposal sites.

The estimate of the burned biomass starts from the computation of the FRP (Fire Radiative Power) that is the radiative power released by the fire. By integrating this quantity in the time it is possible to estimate the FRE (Fire Radiative Energy) and the burned biomass, if coefficients providing the burning efficiency of the vegetation interested by the fire are available. The FRP has been estimated by following three different approaches: the method proposed for the MODIS sensor, based on the eighth power of the brightness temperature of the fired pixel times a suitable coefficient; or by using the hypothesis that the fire size and its burning temperature can be computed by means of the Dozier approach and estimating the FRP by using the Stefan-Bolzmann relationship; or avoiding the computation of the brightness temperature of the fired pixel, by using the approach proposed by Wooster, in which the spatial resolution of the satellite image and the fired pixel emitted radiance are considered. Due to the high temporal frequency of the SEVIRI observations, the integration with the time of the FRP (computed every 15 min) can be carried out allowing to estimate the total energy released by the fire (FRE) and possibly the amount of burned biomass (BB). The paper aims at analyzing the suitability of this approach by focusing on the Sardinia region (Italy). The availability of the sizes of burned areas, provided by the Corpo Forestale e di Vigilanza Ambientale of the Sardinia region, allows to check the significance of the retrieved BB value.

One of the most important factors responsible of the fire-detection algorithms fail is represented by the inaccurate cloud detection methods. In fact, the cloud-contaminated pixels are often associated with false fire pixel because of the brightness temperature increase in the mid-infrared channel. On the other hand an incorrect cloud masking could hide a real fire pixel, especially at the borders of clouds. Together with the SEVIRI images EUMETSAT provides its own cloud mask (CLM product). This mask is computed by making full use of the MSG-SEVIRI spectral channels. Among the 12 channels, only channels 8 (IR 9.7) and 12 (HRV) are not included in the cloud detection and analysis. Due to the particular application for which CRPSM is using SEVIRI images, detection of fire at its early stage (sizes lower than 0.1 ha), a high sensitivity to changes in the radiance measured by the sensor in channel 4 (3.9 iquestm) is required. Since the presence of a cloud covering only a fraction of the pixel (~4 times 4 km at mid latitude) can produce an increase in the estimated brightness temperature, in such channel, capable to provoke a false alarm we decided to use also channel 12 in the cloud detection algorithm. Thus, in order to improve the cloud masks provided by EUMETSAT a new methodology has been introduced. The approach is firstly based on the application of the HRV channel during daytime.

The spectral and radiometric performance of payload SEVIRI onboard the geostationary platform MSG-2, make its data particularly well suited not only to the detection of the onset of volcanic activity, but also to the measurement of thermal radiant fluxes and eruption rates. Thorough testing was carried out on two volcanoes - Stromboli (Aeolian Islands, Southern Italy) and Piton de la Fournaise (Réunion Island, northwestern Indian Ocean) - that mostly give rise to short-lived lava flows. Aimed to comply with the outstandingly high acquisition rate, we developed an ad-hoc code to automatically detect volcanic hot-spots, measure radiant fluxes, and derive lava volume effusion rates within the 15-minute interval between two SEVIRI data streams.

This paper is devoted to describe the activity carried out by CRPSM(Centro di Ricerca Progetto San Marco) in the framework of the SIGRI(Italian acronym for Integrated System for Fire Risks Management) project. This project aims to develop a system, based on satellite data, able to support operationally the activities of users like Italian Civil Protection Agencies or Fire Dept. involved in fighting wild fires. In particular, the system should be able to support all the phases in which a fire fighting activity can be distinguished, namely: Territory management and resources dislocation (fire risk indices), fires detection and monitoring, damage assessment (burned areas and emissions in atmosphere). This paper presents the results obtained in the process of assessing the quality of a fire hazard forecast based on a fire potential index especially designed for the Mediterranean areas. This quality assessment is carried out comparing the daily computed indices with the fire distribution obtained by using a fire detection algorithm based on SEVIRI/MSG images.In fact, using a fire detection algorithm (SFIDE, System for Fires Detection), recently proposed by the authors, a despite of its low spatial resolution,the SEVIRI system is able to reveal, at latitudes corresponding to Italy,fires covering an area of the order of 0.1 ha. The fire potential index (FPI) is one of the most suitable to be computed by using satellite data even if ancillary information are still needed. The computation of this index requires the estimate of the relative greenness, the evaluation of the leaves humidity, the preparation of vegetation fuel maps. Among the parameters needed to compile this index the fuel type map is particularly crucial. In fact, accurate maps of this kind are not available for the Italian territory. Then, first of all, using Corine Land Cover and other available vegetation maps, medium resolution satellite images and "in situ" observations CRPSM carried out the development of these maps for a couple of Italian regions where the summer wild fires problem has higher incidence.

Fires represent one of the main factors of degradation and destruction of the Mediterranean forest heritage. According to fire-fighting agencies, a satellite-based fire-detection system can be considered operationally useful for Mediterranean countries when fires with a minimum extent of 1500 m2can be detected with a temporal resolution of 30 min. In fact, such a system should be able to detect fires at their first stage when it is possible to extinguish them more easily. The Centro di Ricerca Progetto San Marco has been analyzing for several years the possibility of using images acquired by the Spinning Enhanced Visible and Infrared Imager sensor onboard the geostationary satellite Meteosat Second Generation for this purpose. A new processing approach exploiting the increase in both spatial and temporal resolution (15 min) with respect to previous meteosat systems is described in this paper. The idea is based on the use of a change-detection technique to maximize the detection capabilities of the system in spite of its limited spatial resolution. This technique consists of comparing two or more images acquired at 15-min intervals, for which any temperature change can be attributed to fast dynamic phenomena, such as fires, when natural changes are modeled and removed. An assessment of the performances of this algorithm is carried out comparing its results with the report made available by Italian fire-fighting agencies and with fire products based on higher resolution sensors such as the Moderate Resolution Imaging Spectroradiometer

Fires represent one of the main factors of degrada- tion and destruction of the Mediterranean forest heritage. Ac- cording to fire-fighting agencies, a satellite-based fire-detection system can be considered operationally useful for Mediterranean countries when fires with a minimum extent of 1500 m 2 can be detected with a temporal resolution of 30 min. In fact, such a system should be able to detect fires at their first stage when it is possible to extinguish them more easily. The Centro di Ricerca Progetto San Marco has been analyzing for several years the possi- bility of using images acquired by the Spinning Enhanced Visible and Infrared Imager sensor onboard the geostationary satellite Meteosat Second Generation for this purpose. A new processing approach exploiting the increase in both spatial and temporal resolution (15 min) with respect to previous meteosat systems is described in this paper. The idea is based on the use of a change- detection technique to maximize the detection capabilities of the system in spite of its limited spatial resolution. This technique consists of comparing two or more images acquired at 15-min intervals, for which any temperature change can be attributed to fast dynamic phenomena, such as fires, when natural changes are modeled and removed. An assessment of the performances of this algorithm is carried out comparing its results with the reportmadeavailablebyItalianfire-fightingagenciesandwithfire products based on higher resolution sensors such as the Moderate Resolution Imaging Spectroradiometer.