Italian Space Agency Research Articles

CALVAL EVALUATION OF DESIS PRODUCTS IN AMIAZ PLAIN AND MAKHTESH RAMON TEST SITES, SOUTHERN ISRAEL

Abstract. The new era of hyperspectral remote (HSR) sensors in orbit is approaching. Missions such as CHIME of the European Space Agency (ESA), EMIT/SBG of NASA, EnMAP of the German Aerospace Center (DLR), and SHALOM of the Israel Space Agency (ISA) will launch in the near future, while other HSR sensors are already in orbit, such as DESIS of DLR, PRISMA of the Italian Space Agency (ASI), and HISUI of the Japan Aerospace Exploration Agency (JAXA). Vicarious calibration (VC) of satellite sensors is vital to tracking a sensor's performance during its lifetime and is a routine procedure in any satellite mission. Accordingly, searching for ideal sites for CAL/VAL operation is an important task that should be part of the mission planning. This study demonstrates two areas in southern Israel that can be acquired in one overpass as VC sites: Amiaz Plain (AP) and Makhtesh Ramon (MR), which were evaluated for their fulfillment of all VC requirements for HSR sensors. AP (5 km2 of homogeneous bright target) was found suitable for radiometric calibration, and MR (200 km2) for spectral and thematic validations. We checked the applicability of these sites using a high-end airborne HRS sensor (AisaFENIX 1K sensor with 420 bands, 375–2500 nm spectral range, and 1.5-m spatial resolution) along with comprehensive field studies and ground measurements. Accordingly, we developed an operational VC protocol to use these sites for both radiometric and spectral quality inspection of HRS satellites. We demonstrated this capability on recent PRISMA and DESIS reflectance products. Here we provide these analyses and recommend how to use these areas to further examine DESIS data's performance. We call for collaborations with individuals and space agencies in using these VC sites, where we will provide ground-truth information and fulfill any other requirements for VC.

Involving the new generations in particle physics endeavours

Since 1984 INFN and University of Pisa scientists performing experiments at Fermilab have been running a two-month summer training program for Italian students at the lab. In 1984 the program involved only a few physics students from the University of Pisa, but it was later extended to other INFN groups and to engineering students. Since 2004 the program has been supported in part by the US Department of Energy (DOE) in the frame of an exchange agreement with INFN and has been run by the Cultural Association of Italians at Fermilab (CAIF). In 2007 the Sant’Anna School of Advanced Studies (Pisa) established an agreement with Fermilab to share the cost of four engineering students each year. In the almost 40 years of its history, the program has hosted at Fermilab approximately 550 Italian students from more than 20 Italian universities and from some non-Italian universities. In addition, in the years 2010-2019, with the support of the Italian National Institute of Astrophyics (INAF), the Italian Space Agency (ASI), and CAIF, 30 students were hosted in other US laboratories and universities. The Fermilab training programs spanned from data analysis to design and construction of particle detectors and accelerator components, R/D on superconductive elements, theory of accelerators, and analysis of astrophysical data. At the other US laboratories the offered training was on Space Science. In 2015 the University of Pisa endorsed the program as one of its own Summer Schools. The interns are enrolled as Pisa students for the duration of the internship. They are required to write summary reports published in the Fermilab and University of Pisa web pages. Upon positive evaluation by a University board, students are acknowledged 6 ECTS credits. The entire program is expected to expand further under CAIF management. An agreement has been signed between ASI and CAIF, for ASI to support yearly three two-months fellowships in US space science. In the following we inform on student recruiting, training programs, and final evaluation

Advancing cyanobacteria biomass estimation from hyperspectral observations: Demonstrations with HICO and PRISMA imagery

Retrieval of the phycocyanin concentration (PC), a characteristic pigment of, and proxy for, cyanobacteria biomass, from hyperspectral satellite remote sensing measurements is challenging due to uncertainties in the remote sensing reflectance (∆Rrs) resulting from atmospheric correction and instrument radiometric noise. Although several individual algorithms have been proven to capture local variations in cyanobacteria biomass in specific regions, their performance has not been assessed on hyperspectral images from satellite sensors. Our work leverages a machine-learning model, Mixture Density Networks (MDNs), trained on a large (N = 939) dataset of collocated in situ chlorophyll-a concentrations (Chla), PCs, and remote sensing reflectance (Rrs) measurements to estimate PC from all relevant spectral bands. The performance of the developed model is demonstrated via PC maps produced from select images of the Hyperspectral Imager for the Coastal Ocean (HICO) and Italian Space Agency's PRecursore IperSpettrale della Missione Applicativa (PRISMA) using a matchup dataset. As input to the MDN, we incorporate a combination of widely used band ratios (BRs) and line heights (LHs) taken from existing multispectral algorithms, that have been proven for both Chla and PC estimation, as well as novel BRs and LHs to increase the overall cyanobacteria biomass estimation accuracy and reduce the sensitivity to ∆Rrs. When trained on a random half of the dataset, the MDN achieves uncertainties of 44.3%, which is less than half of the uncertainties of all viable optimized multispectral PC algorithms. The MDN is notably better than multispectral algorithms at preventing overestimation on low (<10 mg m−3) PC. Visibly, HICO and PRISMA PC maps show the wider dynamic range that can be represented by the MDN. The available in situ and satellite-derived Rrs matchups and measured in situ PC demonstrate the robustness of the MDN for estimating low (<10 mg m−3) PC and the reduced impact of ∆Rrs on medium-to-high in situ PC (>10 mg m−3). According to our extensive assessments, the developed model is anticipated to enable practical PC products from PRISMA and HICO, therefore the model is promising for planned hyperspectral missions, such as the Plankton Aerosol and Cloud Ecosystem (PACE). This advancement will enhance the complementary roles of hyperspectral radiometry from satellite and low-altitude platforms for quantifying and monitoring cyanobacteria harmful algal blooms at both large and local spatial scales.

Mapping methane point emissions with the PRISMA spaceborne imaging spectrometer

The detection and repairment of methane leaks from fossil fuel production activities have been identified as a key climate change mitigation strategy. Several types of optical satellite sensors have recently shown potential to support this task. Spaceborne imaging spectrometers measuring in the 400–2500 nm spectral range belong to this group. These instruments measure the solar radiation reflected by the Earth in hundreds of spectral channels with a typical spectral resolution of 10 nm and a spatial resolution of 30 m. The PRISMA mission from the Italian Space Agency is the first system of this type providing data openly to the international scientific community. In this work, we evaluate the potential of PRISMA to map methane point emissions, which are typical for fossil fuel production activities. Our retrieval of methane concentration enhancements is based on a matched-filter based algorithm applied to PRISMA spectra in the 2300 nm shortwave infrared spectral region. We perform a simulation-based sensitivity analysis to assess the retrieval performance for different sites. We find that surface brightness and homogeneity are major drivers for the detection and quantification of methane plumes with PRISMA, with retrieval precision errors ranging from 61 to 197 parts-per-billion in the evaluated images. The potential of PRISMA for methane mapping is further illustrated by real plume detections at different methane hotspot regions, including oil and gas extraction fields in Algeria, Turkmenistan, and the USA (Permian Basin), and coal mines in the Shanxi region in China. Our study reports several important findings regarding the potential and limitations of PRISMA for methane mapping, most of which can be extrapolated to upcoming satellite imaging spectroscopy missions.

Regional-Scale Systematic Mapping of Archaeological Mounds and Detection of Looting Using COSMO-SkyMed High Resolution DEM and Satellite Imagery

“Tells” are archaeological mounds formed by deposition of large amounts of anthropogenic material and sediments over thousands of years and are the most important and prominent features in Near and Middle Eastern archaeological landscapes. In the last decade, archaeologists have exploited free-access global digital elevation model (DEM) datasets at medium resolution (i.e., up to 30 m) to map tells on a supra-regional scale and pinpoint tentative tell sites. Instead, the potential of satellite DEMs at higher resolution for this task was yet to be demonstrated. To this purpose, the 3 m resolution imaging capability allowed by the Italian Space Agency’s COSMO-SkyMed Synthetic Aperture Radar (SAR) constellation in StripMap HIMAGE mode was used in this study to generate DEM products of enhanced resolution to undertake, for the first time, a systematic mapping of tells and archaeological deposits. The demonstration is run at regional scale in the Governorate of Wasit in central Iraq, where the literature suggested a high density of sites, despite knowledge gaps about their location and spatial distribution. Accuracy assessment of the COSMO-SkyMed DEM is provided with respect to the most commonly used SRTM and ALOS World 3D DEMs. Owing to the 10 m posting and the consequent enhanced observation capability, the COSMO-SkyMed DEM proves capable to detect both well preserved and levelled or disturbed tells, standing out for more than 4 m from the surrounding landscape. Through the integration with CORONA KH-4B tiles, 1950s Soviet maps and recent Sentinel-2 multispectral images, the expert-led visual identification and manual mapping in the GIS environment led to localization of tens of sites that were not previously mapped, alongside the computation of a figure as up-to-date as February 2019 of the survived tells, with those affected by looting. Finally, this evidence is used to recognize hot-spot areas of potential concern for the conservation of tells. To this purpose, we upgraded the spatial resolution of the observations up to 1 m by using the Enhanced Spotlight mode to collect a bespoke time series. The change detection tests undertaken on selected clusters of disturbed tells prove how a dedicated monitoring activity may allow a regular observation of the impacts due to anthropogenic disturbance (e.g., road and canal constructions or ploughing).

Stratospheric balloon tracking system design through Software Defined Radio applications: STRAINS experiment

The new concept aerospace mission profiles, such as stratospheric airships or suborbital vehicles, impose new requirements for the tracking and surveillance systems, with particular regards to manned missions. New technologies and innovative tracking systems can be supporting such operations. The STRAINS (Stratospheric Tracking Innovative Systems) Experiment, conceived by Sapienza University of Rome and ALTEC (Aerospace Logistics Technology Engineering Company) and supported by ASI (Italian Space Agency), to be launched in Q3/Q4 2021, is aiming at demonstrating TDOA (Time Difference of Arrival), FDOA (Frequency Difference of Arrival) and single station tracking for a Zero-Pressure Balloon Flight in the framework of the HEMERA H2020 balloon launch infrastructure. This paper describes the design of the STRAINS stratospheric experiment, including the stratospheric and the ground segment, the analyses carried out for optimizing the experiment functionalities, the mission analysis for defining the multi-lateration stations locations and the performance evaluation for the designed TDOA tracking system.

Atmospheric Compensation of PRISMA Data by Means of a Learning Based Approach

Atmospheric compensation (AC) allows the retrieval of the reflectance from the measured at-sensor radiance and is a fundamental and critical task for the quantitative exploitation of hyperspectral data. Recently, a learning-based (LB) approach, named LBAC, has been proposed for the AC of airborne hyperspectral data in the visible and near-infrared (VNIR) spectral range. LBAC makes use of a parametric regression function whose parameters are learned by a strategy based on synthetic data that accounts for (1) a physics-based model for the radiative transfer, (2) the variability of the surface reflectance spectra, and (3) the effects of random noise and spectral miscalibration errors. In this work we extend LBAC with respect to two different aspects: (1) the platform for data acquisition and (2) the spectral range covered by the sensor. Particularly, we propose the extension of LBAC to spaceborne hyperspectral sensors operating in the VNIR and short-wave infrared (SWIR) portion of the electromagnetic spectrum. We specifically refer to the sensor of the PRISMA (PRecursore IperSpettrale della Missione Applicativa) mission, and the recent Earth Observation mission of the Italian Space Agency that offers a great opportunity to improve the knowledge on the scientific and commercial applications of spaceborne hyperspectral data. In addition, we introduce a curve fitting-based procedure for the estimation of column water vapor content of the atmosphere that directly exploits the reflectance data provided by LBAC. Results obtained on four different PRISMA hyperspectral images are presented and discussed.

PRISMA sensor evaluation: a case study of mineral mapping performance over Makhtesh Ramon, Israel

ABSTRACT The Italian Space Agency (ASI)’s PRecursore IperSpettrale della Missione Applicativa (PRISMA) hyperspectral remote sensing (HSR) satellite was launched on 22 March 2019. This spectral imaging sensor, with 238 bands across the 400–2500 nm range and 30-m spatial resolution, can advance remote-sensing studies for vast applications worldwide. The present study evaluates the capability of the sensor’s L1 (Top-of the- atmosphere TOA radiance) and L2D (reflectance) products for mapping minerals and geology in Makhtesh Ramon (MR), a national park in southern Israel that covers approximately 200 km2. The exceptional geological features in this area, with hardly any vegetation and mostly clear skies year-round, make it an ideal site for remote-sensing studies in general and HSR studies in particular. The quality of the PRISMA sensor’s technical and thematic performance was assessed by examining its radiometry and spectral products against a highly calibrated airborne HSR sensor (AisaFENIX 1K; 420 spectral bands, range 375–2500 nm, 1.5-m spatial resolution). Airborne and field data acquisition captured the entire MR area, followed by comprehensive fieldwork with a portable ASD FieldSpec spectrometer (400–2500 nm spectral range). The PRISMA sensor’s radiance performance was evaluated by examining the top of the atmosphere radiance product against simulated radiance using the MODTRAN® radiative transfer code. The simulated radiance used in-situ ground reflectance measurements in several locations across MR. The L1 and L2D products presented fair results with some outliers for PRISMA’s L2D SWIR 2 long-wavelength region. The L2D product was further studied to map mineral occurrences and demonstrated promising results compared to MR’s well-known geology and mineral distribution, and it was highly correlated to the high-spatial-resolution spectral mapping generated by the AisaFENIX 1K airborne sensor. Based on these results, we successfully mapped different types of minerals, such as iron oxides in the VNIR, gypsum in SWIR 1, and clay in SWIR 2. The PRISMA data’s reflectance interference across the longer wavelengths of SWIR 2 did not permit fine mapping for carbonates, probably because of the L2D’s poor performance in this spectral range. The quantitative performance of PRISMA’s mineral mapping was judged relative to the quantitative products of the AisaFENIX 1K sensor for these same minerals, revealing about 80% accuracy for PRISMA’s products.

The impact of the Italian Space Agency on scientific knowledge: Evidence from academic publications

AbstractIndustrial and research activities in the space sector involve a heterogeneous group of actors such as private and public firms, universities, research institutes and space agencies, collaborating to different stages of missions’ realization. Such collaborations are associated to the creation of spillover effects, proxied in different ways, such as the number of patents recorded, post‐graduate students involved, spin‐off activities and co‐authored papers.The aim of this paper is to investigate the impact of the collaboration between universities /research institutes and the Italian Space Agency (ASI). To this aim, we focus on papers where the authors acknowledge grants received by ASI. We use data on publications and citations to capture the association between ASI funding of a large number of scientific articles published in the period 1989–2017 and the quality of research, proxied by the number of citations received.By performing parametric estimates with multiple levels of fixed effects (year, author and coauthors fixed effects), we find that articles mentioning ASI in the funding information are associated to a higher citation impact with respect to articles not financially supported by ASI. Such result suggests a positive impact on the scientific community of public funds granted to universities and research institutes.

ANALYSIS AND DETECTION OF WILDFIRES BY USING PRISMA HYPERSPECTRAL IMAGERY

Abstract. This paper deals with the analysis and detection of wildfires by using PRISMA imagery. Precursore IperSpettrale della Mis­sione Applicativa (Hyperspectral Precursor of the Application Mission, PRISMA) is a new hyperspectral mission by ASI (Agenzia Spaziale Italiana, Italian Space Agency) launched in 2019. This mission provides hyperspectral images with a spectral range of 0.4–2.5 µm and an average spectral resolution less than 10 nm. In this work, we used the PRISMA hypercube acquired during the Australian bushfires of December 2019 in New South Wales. The analysis of the image is presented considering the unique amount of information contained in the continuous spectral signature of the hypercube. The Carbon dioxide Continuum-Interpolated Band Ratio (CO2 CIBR), Hyperspectral Fire Detection Index (HFDI), and Normalized Burn Index (NBR) will be used to analyze the informative content of the image, along with the analysis of some specific visible, near-infrared and shortwave-infrared bands. A multiclass classification is presented by using a I-dimensional convolutional neural network (CNN), and the results will be com­pared with the ones given by a support vector machine classifier reported in literature. Finally, some preliminary results related to wildfire temperature estimation are presented.

THE NUTRISS STUDY: A NEW APPROACH TO CALIBRATE DIET AND EXERCISE IN LONG-TERM SPACE MISSIONS

Energy balance maintenance is crucial to preserve astronaut's wellness during longduration-spaceflight. Nutritional intervention can counteract the detrimental effect of microgravity on body composition and metabolism. NutrISS is an Italian Space Agency biomedical experiment. This proof-of-concept study aim to monitor the body composition of astronauts and to provide nutritional advice during long-term mission. The study has been executed on the ISS and sponsored by ESA. The payloads selected for the mission “BEYOND” result from a public-call funded and coordinated by ASI, in the frame of its national mission of promoting and fostering the culture of space across the Country and providing access to the ISS as a laboratory in space to the Italian research community. The utilization support services is ensured by Argotec/Telespazio (UTISS Team). The Italian astronaut Luca Parmitano underwent to baseline data collections, i.e. body composition, anthropometric evaluation and energy and metabolic assessment carried out by the scientific team. Body composition has been assessed by a BioImpedance Analyser device (Akern) modified by Kayser Italia. To maintain the near-neutral energy balance, the NutISS team monitored monthly the astronaut body mass during flight. Results are now classified for privacy reasons. The study was extended since collected data improved physical performance and quality of life of the astronaut during spaceflight and optimize the astronaut recovery-phases on Earth after landing. Obtained experimental data could have an important impact both on astronaut quality of life and clinical management of malnourished and/or obese immobilized patients, therefore improving the quality of human bedridden patients on Earth.

Moon Mapping Project Results on Solar Wind Ion Flux and Composition

The “Moon Mapping” project is a collaboration between the Italian and Chinese Governments allowing cooperation and exchange between students from both countries. The main aim of the project is to analyze remotely-sensed data collected by the Chinese space missions Chang’E-1/2 over the Moon surface. The Italian Space Agency is responsible for the Italian side and the Center of Space Exploration, while the China Ministry of Education is responsible for the Chinese side. In this article, we summarize the results of the “Moon Mappining” project topic #1: “map of the solar wind ion” using the data collected by Chang’E-1 satellite. Chang’E-1 is a lunar orbiter, its revolution period lasts 2 h, and its orbit is polar. The satellite is equipped with two Solar Wind Ion Detectors (SWIDs) that are two perpendicular electrostatic spectrometers mapping the sky with a field of view of 15° × 6.7° × 24 ch. The spectrometers can measure solar wind flux in the range 40 eV/q–17 keV/q with an energy resolution of 8% and time resolution of ∼3 s. The data collected by the two Solar Wind Ion Detectors are analyzed to characterize the solar wind flux and composition on the Moon surface and to study the time variations due to the solar activity. The data measured by Chang’E-1 compared with the one measured in the same period by the electrostatic spectrometers onboard the ACE satellite, or with another solar activity indicator as the sunspot number, enrich the multi-messenger/multi-particle view of the Sun, gathering valuable information about the space weather outside the Earth magnetosphere.

Exploring PRISMA Scene for Fire Detection: Case Study of 2019 Bushfires in Ben Halls Gap National Park, NSW, Australia

Precursore IperSpettrale della Missione Applicativa (Hyperspectral Precursor of the Application Mission, PRISMA) is a new hyperspectral mission by the ASI (Agenzia Spaziale Italiana, Italian Space Agency) mission launched in 2019 to measure the unique spectral features of diverse materials including vegetation and forest disturbances. In this study, we explored the potential use of this new sensor PRISMA for active wildfire characterization. We used the PRISMA hypercube acquired during the Australian bushfires of 2019 in New South Wales to test three detection techniques that take advantage of the unique spectral features of biomass burning in the spectral range measured by PRISMA. The three methods—the CO2-CIBR (continuum interpolated band ratio), HFDI (hyperspectral fire detection index) and AKBD (advanced K band difference)—were adapted to the PRISMA sensor’s characteristics and evaluated in terms of performance. Classification techniques based on machine learning algorithms (support vector machine, SVM) were used in combination with the visual interpretation of a panchromatic sharpened PRISMA image for validation. Preliminary analysis showed a good overall performance of the instrument in terms of radiance. We observed that the presence of the striping effect in the data can influence the performance of the indices. Both the CIBR and HFDI adapted for PRISMA were able to produce a detection rate spanning between 0.13561 and 0.81598 for CO2-CIBR and that between 0.36171 and 0.88431 depending on the chosen band combination. The potassium emission index turned out to be inadequate for locating flaming in our data, possibly due to multiple factors such as striping noise and the spectral resolution (12 nm) of the PRISMA band centered at the potassium emission.

LICIACube - The Light Italian Cubesat for Imaging of Asteroids In support of the NASA DART mission towards asteroid (65803) Didymos

“LICIACube – the Light Italian Cubesat for Imaging of Asteroids” is managed by the Italian Space Agency (ASI) and will be part of the NASA DART mission, with the aim of i) documenting the DART impact’s effects on the secondary member of the (65803) Didymos binary asteroid system, ii) characterizing the shape of the target, and iii) performing dedicated scientific investigations on it. DART probe will be launched at the end of 2021 and LICIACube will be hosted as piggyback during the interplanetary cruise, then released 10 days before the impact, and autonomously guided along its fly-by trajectory. The LICIACube payload is composed by LEIA, a narrow FoV camera, and LUKE, a wide FoV imager with an RGB Bayer pattern filter, that will collect and transmit to Earth several unique images of the effects of the DART impact on the asteroid, such as the formation and the development of the plume potentially determined by the impact.LICIACube will be the first deep space mission developed and autonomously managed by an Italian team: the design, integration and test of the CubeSat have been assigned by ASI to the aerospace company Argotec, while the LICIACube Ground Segment has a complex architecture based on the Argotec Mission Control Center, antennas of the NASA Deep Space Network and data archiving and processing, managed at the ASI Space Science Data Center. The LICIACube team includes a wide Italian scientific community, involved in the definition of all the aspects of the mission: trajectory design; mission definition (and real-time orbit determination during operations); impact, plume and imaging simulation and modelling, in preparation of a suitable framework for the analysis and interpretation of in-situ data. The major technological mission challenge, i.e. the autonomous targeting and imaging of such a small body during a fast fly-by, to be accomplished with the limited resources of a CubeSat, is affordable thanks to a strong synergy of all the mentioned teams in support of the engineering tasks.

The New Hyperspectral Satellite PRISMA: Imagery for Forest Types Discrimination.

Different forest types based on different tree species composition may have similar spectral signatures if observed with traditional multispectral satellite sensors. Hyperspectral imagery, with a more continuous representation of their spectral behavior may instead be used for their classification. The new hyperspectral Precursore IperSpettrale della Missione Applicativa (PRISMA) sensor, developed by the Italian Space Agency, is able to capture images in a continuum of 240 spectral bands ranging between 400 and 2500 nm, with a spectral resolution smaller than 12 nm. The new sensor can be employed for a large number of remote sensing applications, including forest types discrimination. In this study, we compared the capabilities of the new PRISMA sensor against the well-known Sentinel-2 Multi-Spectral Instrument (MSI) in recognition of different forest types through a pairwise separability analysis carried out in two study areas in Italy, using two different nomenclature systems and four separability metrics. The PRISMA hyperspectral sensor, compared to Sentinel-2 MSI, allowed for a better discrimination in all forest types, increasing the performance when the complexity of the nomenclature system also increased. PRISMA achieved an average improvement of 40% for the discrimination between two forest categories (coniferous vs. broadleaves) and of 102% in the discrimination between five forest types based on main tree species groups.

Analysis of the Quality of SLR Station Coordinates Determined from Laser Ranging to the LARES Satellite.

The LARES (LAser RElativity Satellite) was built by the Italian Space Agency (ASI) and launched on 13 February 2012 by the European Space Agency. It is intended for studying the Lense–Thirring effect resulting from general relativity as well as for geodynamic studies and satellite geodesy. The satellite is observed by most ground laser stations. The task of this work is to determine the station coordinates and to assess the quality of their determination by comparison with the results from the LAGEOS-1 and LAGEOS-2 satellites. Observation results in the form of normal points (396,105 normal points in total) were downloaded from the EUROLAS Data Center for the period from 29 February 2012 to 31 December 2015. Seven-day orbital arcs were computed by the NASA GSFC GEODYN-II software, determining the coordinates of seventeen selected measuring stations. The average Root Mean Square (RMS) (15.1 mm) of the determined orbits is nearly the same as for LAGEOS (15.2 mm). The stability of the coordinates of each station (3DRMS) is from 9 mm to 46 mm (for LAGEOS, from 5 mm to 15 mm) with the uncertainty of determining the coordinates of 3–11 mm (LAGEOS 2–7 mm). The combined positioning for the LARES + LAGEOS-1 + LAGEOS-2 satellites allows for the stability of 5–18 mm with an uncertainty of 2–6 mm. For most stations, this solution is slightly better than the LAGEOS-only one.

Satellite X-band SAR data exploitation trends in the framework of ASI’s COSMO-SkyMed Open Call initiative

Abstract COSMO-SkyMed (Constellation of Small satellites for Mediterranean basin Observation) is an Italian Earth Observation (EO) and Dual-Use (Civilian and Defense) Space System conceived with the aim to establish a worldwide service providing Synthetic Aperture Radar (SAR) data, products and services compliant with well-established international standards and relevant to a wide range of applications, such as emergency and risk management, scientific and commercial applications and defense Applications. Starting from 2007, the Italian Space Agency (ASI) has promoted the COSMO-SkyMed SAR data exploitation through several initiatives such as “Announcement of Opportunity”, “Open Call for Science” and “Open Call for National Small and Medium Enterprises (SMEs)”. This paper is focused on the trends and results observed in the context of the “Open Call for Science”, an initiative completely addressed to the national and international scientific community since 2015. In particular, in this framework, the observed trend and advances in science and applications of SAR imagery and Interferometric SAR (InSAR) are summarized and assessed, also in light of the scientific evidence published in the recent literature by scientific users of ASI’s “Open Call for Science”.

Water Quality Retrieval from PRISMA Hyperspectral Images: First Experience in a Turbid Lake and Comparison with Sentinel-2

A new era of spaceborne hyperspectral imaging has just begun with the recent availability of data from PRISMA (PRecursore IperSpettrale della Missione Applicativa) launched by the Italian space agency (ASI). There has been pre-launch optimism that the wealth of spectral information offered by PRISMA can contribute to a variety of aquatic science and management applications. Here, we examine the potential of PRISMA level 2D images in retrieving standard water quality parameters, including total suspended matter (TSM), chlorophyll-a (Chl-a), and colored dissolved organic matter (CDOM) in a turbid lake (Lake Trasimeno, Italy). We perform consistency analyses among the aquatic products (remote sensing reflectance (Rrs) and constituents) derived from PRISMA and those from Sentinel-2. The consistency analyses are expanded to synthesized Sentinel-2 data as well. By spectral downsampling of the PRISMA images, we better isolate the impact of spectral resolution in retrieving the constituents. The retrieval of constituents from both PRISMA and Sentinel-2 images is built upon inverting the radiative transfer model implemented in the Water Color Simulator (WASI) processor. The inversion involves a parameter (gdd) to compensate for atmospheric and sun-glint artifacts. A strong agreement is indicated for the cross-sensor comparison of Rrs products at different wavelengths (average R ≈ 0.87). However, the Rrs of PRISMA at shorter wavelengths (&lt;500 nm) is slightly overestimated with respect to Sentinel-2. This is in line with the estimates of gdd through the inversion that suggests an underestimated atmospheric path radiance of PRISMA level 2D products compared to the atmospherically corrected Sentinel-2 data. The results indicate the high potential of PRISMA level 2D imagery in mapping water quality parameters in Lake Trasimeno. The PRISMA-based retrievals agree well with those of Sentinel-2, particularly for TSM.

ASI Space Science Data Center participation to high-school outreach program

Since 2017 the Italian Space Agency (ASI) participates to so-called ‘Alternanza Scuola-Lavoro’ (i.e. ‘school-work synergy’) outreach projects promoted by the Italian government, and the ASI Space Science Data Center (SSDC) actively contributes to them, with the primary aim of bringing students closer to space-related activities before choosing their university studies.The SSDC outreach programme is split into two parts: one theoretical, in which relevant topic are presented and explained, and one practical, consisting of hands-on activities aimed to replicate scientific analysis of real space data. The impact of the programme on students’ attitude is then evaluated by means of questionnaires specifically designed to gather information on the students’ educational background, the level of engagement triggered by the proposed activities, their relevance to school-based activities, and the perceived ease of understanding of the covered topics.As reported in this paper, the analysis of the answers clearly shows that students greatly appreciated this outreach project, supporting its possible expansion and development, even articulated in a more complex pedagogical plan, as already done for one school in a pilot case. Therefore, we plan to expand these activities in the next future both by including new topics (e.g. cosmology, stellar physics), and by proposing new more articulated teaching pathways inclusive of on-site activities in the classroom.

Detection and Classification of Non-Photosynthetic Vegetation from PRISMA Hyperspectral Data in Croplands

This study introduces a first assessment of the capabilities of PRISMA (PRecursore IperSpettrale della Missione Applicativa)—the new hyperspectral satellite sensor of the Italian Space Agency (ASI)—for Non-Photosynthetic Vegetation (NPV) monitoring, a topic which is becoming very relevant in the field of sustainable agriculture, being an indicator of crop residue (CR) presence in the field. Data-sets collected during the mission validation phase in croplands are used for mapping the NPV presence and for modelling the diagnostic absorption band of cellulose around 2.1 μm with an Exponential Gaussian Optimization approach, in the perspective of the prediction of the abundance of crop residues. Results proved that PRISMA data are suitable for these tasks, and call for further investigation to achieve quantitative estimates of specific biophysical variables, also in the framework of other hyperspectral missions.