The monitoring of water biophysical parameters and the management of aquatic ecosystems are crucial to address the current state of degradation of inland and coastal waters. Water quality monitoring not only supports management decisions, but also provides important insights to better understand changing structural and functional processes. To date, most applications developed for inland waters have relied on multispectral and medium to coarse resolution satellites, while a new generation of spaceborne imaging spectroscopy is now available and future global missions are under development. This study aims to evaluate both the Level 1 PRISMA products, in different processing versions, and the Level 2 products based on coincident in-situ data collected in different aquatic ecosystems. Examples of water quality mapping in different use cases will then be provided, also in synergy with other missions such as EnMAP and Sentinel-2.

Climate change is having a significant negative impact on freshwater systems, which provide multiple ecosystem services. In this context, the present study aims to show an overview of the main objectives achieved by exploiting the hyperspectral reflectance data provided by the PRISMA sensor to map aquatic ecosystems. Water quality products were generated using three different approaches: the bio-optical model BOMBER, adaptive semi-empirical algorithms, and machine learning models. These methods were tested in very different waterbodies worldwide: five lakes, two lagoons and one river. To assess the accuracy of the water quality products, comparisons were performed with reference measurements. The results showed an average R2= 0.70 and encourage using PRISMA data for aquatic applications in synergy with existing multispectral and future hyperspectral data.

The unique spectral content provided by PRISMA's hyperspectral sensor gives the possibility to study the Earth's surface and environment from space in unprecedented detail. In this respect, our work presents the results of an Italian Space Agency-funded project aiming to develop eight prototypes for providing Value Added products based on such data. Prototypes focus on vegetation, urban areas, water quality, material detection, and natural hazards, combining multiple state-of-the-art techniques based on Machine Learning, physical models, and index-based algorithms. This is particularly relevant given the increasing demand for accurate information to address sustainable policies and support decision-making processes. Through a series of case studies, we highlight the versatility and utility of PRISMA's hyperspectral data for various scientific and operational applications.

PRISMA (PRecursore IperSpettrale della Missione Applicativa) is a demonstrative spaceborne mission, fully deployed by the Italian Space Agency (ASI). To support the calibration/validation activities of the PRISMA hyperspectral mission, ASI and the National Research Council (CNR) started in 2019 the PRISCAV project (Scientific CAL/VAL of PRISMA mission). The main objective of PRISCAV is the comprehensive characterization of the performances of the PRISMA payload in orbit in different operational scenarios and the verification of the durability in time of the performances. To this end, PRISCAV created a network of 12 instrumented sites showing different land-use and surface settings (Snow; Sea; Inland and Coastal Water; Forest and Cropland) to obtain independent and traceable in-situ and airborne Fiducial Reference Measurements (FRM) simultaneous to PRISMA acquisitions in order to assess the required performance of sensor, data products, and processors at the different levels (i.e. Top-of-Atmosphere Level 1 Radiances and Bottom-of-Atmosphere Level 2 Reflectance standard products). Moreover, on some of these sites, simultaneous PRISMA and airborne AVIRISNG acquisitions were made coupling remote sensing with in-situ observations to support new mission development and in particular the Copernicus Hyperspectral Imaging Mission for the Environment (CHIME). Recent updates on CAL/VAL activities and on AVIRSNG campaigns are presented in this contribution.

COVID-19 lockdown measures brought to a drastic reduction of anthropic impacts on the environment, including the marine-coastal system. EO data have the potential to monitor and diagnose the subsequent effects of the lockdown in terms of water quality. The ESA-RACE project SOON aims to link complex patterns that may arise from the environmental changes due to COVID-19 lockdown by using EO data, also seeking to assess connectivity between inland and marine system. Within this frame, here we present a holistic, satellite-based analysis of the spatial-temporal variability of environmental parameters in the North Adriatic Sea (NAS; Mediterranean basin), exploiting the synergy of OC and SST products from different sensors, as well as in situ hydrologic data. Our analysis indicates a favorable interplay of environmental variability and reduction of anthropogenic activity that results in negative anomalies of Chlorophyll-a and Total Suspended Matter with respect to the climatologic values.

This study presents an assessment of PRISMA (PRecursore IperSpettrale della Missione Applicativa) for water applications, by including a general description of the mission and by focusing on the standard Level 1 (L1) and Level 2 (L2) products acquired on different aquatic systems. A preliminary analysis on the estimation of signal-to-noise ratio (SNR) from L1 PRISMA products in the visible near infrared spectra (VISNIR) is indicating values comparable to Sentinel-2 MSI from literature, apart at short wavelengths where PRISMA SNR is lower. Few examples of L2 products in terms of water reflectance are also presented to encourage the exploitation of PRISMA for aquatic ecosystem mapping. The results of this study are indicating that even if some applications might be developed with the standard L2 products, an ad-hoc processing might be necessary to include the specific requirements of atmospheric correction of water targets. Further analyses with a higher number of imagery data are however recommended to fully characterize the PRISMA products.

PRISMA, in orbit since March the 22nd 2019, opened the user access in spring 2020. After one year, many hundreds of users have gained the capability to program new acquisitions or download image products from the online archive containing more than 67k datasets, under a quasi-open & free data policy and licensing scheme. During this time frame and despite the COVID-19 related difficulties, PRISMA performed normal operations delivering not only nominal verified quality data to users but establishing collaborations with other space agencies, in order to enable and support synergies with other hyperspectral missions. This paper describes the mission and the results achieved in this first period of full operational usage.

In order to control the spread of the pandemic of Corona-Virus Disease 2019 (COVID-19), lockdowns of various durations and intensities have been established in many countries over the world all through the year 2020. The trilateral dashboard jointly implemented by NASA, JAXA and ESA aims at exploiting remote-sensing data to evaluate the impact of these restrictions, and subsequent recovery phases on many different environmental, agriculture and economic indicators. More specifically, this paper presents the indicators implemented to monitor the impact of COVID-19 restrictions on Water Quality, together with preliminary analysis results over a few Areas of Interest.

In this study, in situ data and hyperspectral MIVIS (Multispectral Infrared and Visible Imaging Spectrometer) images collected over a period of 14 years were used to assess changes in submerged macrophytes colonization patterns in southern Lake Garda.