Virginia Zamparelli

Integrated Monitoring of Lake Garda with Radar, Optical Sensors and In Situ Instruments: Insights from the SARLAKES ProjectVirginia Zamparelli1, Simona Verde1, Andrea Petrossi1, Gianfranco Fornaro1, Marina Amadori2,3, Mariano Bresciani2, Giacomo De Carolis2, Francesca De Santi4, Matteo De Vincenzi3, Giulio Dolcetti3, Ali Farrokhi3, Raffaella Frank2, Nicola Ghirardi2,5, Claudia Giardino2, Fulvio Gentilin6, Alessandro Oggioni2, Marco Papetti6, Gianluca Pari7 Andrea Pellegrino2, Sebastiano Piccolroaz3, Tazio Strozzi8, Marco Toffolon3, Maria Virelli7, Nestor Yague-Martinez9, and Giulia Valerio6 1Institute for Electromagnetic Sensing of the Environment (IREA), National Research Council, Naples, Italy2Institute for Electromagnetic Sensing of the Environment (IREA), National Research Council, Milan, Italy3Department of Civil, Environmental and Mechanical Engineering (DICAM), University of Trento, Trento, Italy4Institute for Applied Mathematics and Information Technologies (IMATI), National Research Council, Milan, Italy5 Institute for BioEconomy (IBE), National Research Council, Sesto Fiorentino, Italy6Department of Civil, Environmental, Architectural Engineering and Mathematics (DICATAM), University of Brescia, Brescia, Italy7Italian Space Agency (ASI), Rome, Italy8GAMMA Remote Sensing, Gümligen, Switzerland9Capella Space Corp., San Francisco, CA, USA SARLAKES (SpatiAlly Resolved veLocity and wAves from SAR images in laKES) is a PRIN (Projects of National Interest) project funded in 2022 by the Italian Ministry of University and Research. The project is now in its final phase and is scheduled to end at the beginning of 2026. The project developed a novel, advanced and adaptable tool capable of accurately measuring water dynamics in medium- and large-sized lakes.A key and innovative aspect of the project is the use of spaceborne Synthetic Aperture Radar (SAR) data, which are widely exploited for routine observation of the marine environments but remain relatively underutilized for lake monitoring. SARLAKES investigated the capability of SAR imagery to retrieve the spatial distribution of wind fields, surface currents, and wind-generated waves in lacustrine environments.The project considers Lake Garda and Lake Geneva as case studies, with Lake Garda—the largest lake in Italy—selected as the primary test site due to the research group’s long-standing experience and the availability of extensive historical data.This contribution presents the main results obtained over two years of project activity, with particular emphasis on outcomes from a multidisciplinary field campaign conducted on April 2025. The campaign aimed to reconstruct lake surface currents during a strong wind event in the peri-Alpine Lake Garda region.The field instrumentation included a wave buoy, an acoustic Doppler current profiler (ADCP), Lagrangian drifters, anemometers, a ground-based radar, fixed cameras, a drone, and a conductivity–temperature–depth profiler. Satellite acquisitions from the COSMO-SkyMed Second Generation and Capella Space SAR sensors, as well as from the optical sensor PRISMA were scheduled over the study area during the campaign. Archive data from Sentinel-1, Sentinel-2, Sentinel-3, Landsat, and COSMO-SkyMed missions were also utilized.The project demonstrates how the integration of in-situ instrumentation, spatially distributed flow measurements from remote sensing, and hydrodynamic modeling provides a comprehensive and scalable approach to next-generation monitoring of complex lake systems.

In this work, we present the results of a comparative analysis between the first-generation Advanced Synthetic Aperture Radar (ASAR) sensor mounted on board the ENVISAT platform and the novel ICEYE micro-satellite synthetic aperture radar (SAR) sensor in measuring the radial velocity of ocean currents through the Doppler Centroid Anomaly (DCA) technique. First, the basic principles of DCA and the theoretical precision of the Doppler Centroid (DC) estimates are introduced. Subsequently, the role of the DC measurements in retrieving the sea surface current velocity is addressed. To achieve this goal, two sets of SAR data gathered by ASAR (C-band) and from the X-band ICEYE instruments, respectively, are exploited. The standard deviation of DCA measurements is derived and tested against what is expected by theory. The presented analysis results are beneficial to evaluate the pros and cons of the new-generation X-band to the first-generation ASAR/ENVISAT system, which has been extensively exploited for ocean currents monitoring applications. As an outcome, we find that with inherently selected methods for DC estimates, the performance offered by ICEYE is comparable to, or even better than (with specific parameters selection), the consolidated approaches based on the ASAR sensor. Nonetheless, new SAR constellations offer an undoubted advantage regarding improved spatial resolution and time repeatability.

Nowadays, sea surface analysis and monitoring increasingly use remote sensing, with particular interest in Synthetic Aperture Radar (SAR). Several SAR techniques exist in literature to understand the marine phenomena affecting the sea surface. In this work, we focus on the Doppler Centroid Anomaly (DCA), which accounts for the Doppler shift induced by sea surface movements. Starting from SAR raw data, we develop a processing chain to elaborate them and output the surface velocity map using DCA. The DCA technique has often been presented in the marine literature for estimating sea surface velocity, but more recently it has also been used to detect near-surface wind fields. This paper deals with estimating the sea surface wind field using Doppler information and SAR backscatter, combined with wind information provided by ECMWF and geophysical wind and Doppler model functions. We investigate the application of the approach in the coastal area of the northern Adriatic Sea (Northeast Italy). The test site is interesting, both for its particular orography, as it is a semi-enclosed basin largely surrounded by mountains, and for its complex meteorological phenomena, such as the Bora wind. Results obtained combining SAR backscatter and DCA information show an improvement in wind field estimation.

Remote sensing technologies are extensively applied to prevent, monitor, and forecast hazardous risk conditions in the present-day global climate change era. This paper presents an overview of the current stage of remote sensing approaches employed to study coastal and delta river regions. The advantages and limitations of Earth Observation technology in characterizing the effects of climate variations on coastal environments are also presented. The role of the constellations of satellite sensors for Earth Observation, collecting helpful information on the Earth’s system and its temporal changes, is emphasized. For some key technologies, the principal characteristics of the processing chains adopted to obtain from the collected raw data added-value products are summarized. Emphasis is put on studying various disaster risks that affect coastal and megacity areas, where heterogeneous and interlinked hazard conditions can severely affect the population.

Non-climate-related anthropogenic processes and frequently encountered natural hazards exacerbate the risk in coastal zones and megacities and amplify local vulnerability. Coastal risk is amplified by the combination of sea level rise (SLR) resulting from climate change, associated tidal evolution, and the local sinking of land resulting from anthropogenic and natural hazards. In this framework, the authors of this investigation have actively contributed to the joint European Space Agency (ESA) and the Chinese Ministry of Science and Technology (MOST) Dragon IV initiative through a project (ID. 32294) that was explicitly designed to address the issue of monitoring coastal and delta river regions through Earth Observation (EO) technologies. The project’s primary goals were to provide a complete characterization of the changes in target scenes over time and provide estimates of future regional sea level changes to derive submerged coastal areas and wave fields. Suggestions are also provided for implementing coastal protection measures in order to adapt and mitigate the multifactor coastal vulnerability. In order to achieve these tasks, well-established remote sensing technologies based on the joint exploitation of multi-spectral information gathered at different spectral wavelengths, the exploitation of advanced Differential Interferometric Synthetic Aperture Radar (DInSAR) techniques for the retrieval of ground deformations, the realization of geophysical analyses, and the use of satellite altimeters and tide gauge data have effectively been employed. The achieved results, which mainly focus on selected sensitive regions including the city of Shanghai, the Pearl River Delta in China, and the coastal city of Saint Petersburg in Europe, provide essential assets for planning present and future scientific activities devoted to monitoring such fragile environments. These analyses are crucial for assessing the factors that will amplify the vulnerability of low-elevation coastal zones.

The SAR Doppler frequencies are directly related to the motion of the scatterers in the illuminated area and have already been used in marine applications to monitor moving water surfaces. Here we investigate the possibility of retrieving surface water velocity from SAR Doppler analysis in medium-size lakes. ENVISAT images of the test site (Lake Garda) are processed and the Doppler Centroid Anomaly technique is adopted. The resulting surface velocity maps are compared with the outputs of a hydrodynamic model specifically validated for the case study. Thermal images from MODIS Terra are used in support of the modeling results. The surface velocity retrieved from SAR is found to overestimate the numerical results and the existence of a bias is investigated. In marine applications, such bias is traditionally removed through Geophysical Model Functions (GMFs) by ascribing it to a fully developed wind waves spectrum. We found that such an assumption is not supported in our case study, due to the small-scale variations of topography and wind. The role of wind intensity and duration on the results from SAR is evaluated, and the inclusion of lake bathymetry and the SAR backscatter gradient is recommended for the future development of GMFs suitable for lake environments.

In this work, we study ground deformation of ocean-reclaimed platforms as retrieved from interferometric synthetic aperture radar (InSAR) analyses. We investigate, in particular, the suitability and accuracy of some time-dependent models used to characterize and foresee the present and future evolution of ground deformation of the coastal lands. Previous investigations, carried out by the authors of this paper and other scholars, related to the zone of the ocean-reclaimed lands of Shanghai, have already shown that ocean-reclaimed lands are subject to subside (i.e., the ground is subject to settling down due to soil consolidation and compression), and the temporal evolution of that deformation follows a certain predictable model. Specifically, two time-gapped SAR datasets composed of the images collected by the ENVISAT ASAR (ENV) from 2007 to 2010 and the COSMO-SkyMed (CSK) sensors, available from 2013 to 2016, were used to generate long-term ground displacement time-series using a proper time-dependent geotechnical model. In this work, we use a third SAR data set consisting of Radarsat-2 (RST-2) acquisitions collected from 2012 to 2016 to further corroborate the validity of that model. As a result, we verified with the new RST-2 data, partially covering the gap between the ENV and CSK acquisitions, that the adopted model fits the data and that the model is suitable to perform future projections. Furthermore, we extended these analyses to the area of Pearl River Delta (PRD) and the city of Shenzhen, China. Our study aims to investigate the suitability of different time-dependent ground deformation models relying on the different geophysical conditions in the two areas of Shanghai and Shenzhen, China. To this aim, three sets of SAR data, collected by the ENV platform (from both ascending and descending orbits) and the Sentinel-1A (S1A) sensor (on ascending orbits), were used to obtain the ground displacement time-series of the Shenzhen city and its surrounding region. Multi-orbit InSAR data products were also combined to discriminate the up–down (subsidence) ground deformation time-series of the coherent points, which are then used to estimate the parameters of the models adopted to foresee the future evolution of the land-reclaimed ground consolidation procedure. The exploitation of the obtained geospatial data and products are helpful for the continuous monitoring of coastal environments and the evaluation of the socio-economical impacts of human activities and global climate change.

Several studies have shown the capabilities of Synthetic Aperture Radar to map sea currents in ocean regions mainly characterized by large flows. We consider the well known method based on the analysis of the Doppler Centroid. The Doppler, as, in general, the scattering from the sea, is sensitive to several phenomena, occurring between the upper ocean and atmospheric boundary layers. To investigate such phenomena, we considered the combined use of both ENVISAT calibrated amplitude and Doppler data in conjunction with hindcast wind information provided by atmospheric models as well as Wind and Doppler Geophysical Model Functions (W/D-GMF) developed, in the literature, for C-Band systems. This integrated analysis for the interpretation of the Doppler surface currents measurements was carried out on a case study located in the Mediterranean Sea which is characterized by a general low circulation regime: specifically, the coastal region around the city of Naples. In this case study, we show that generally, wind plays a direct significant role in the observed Doppler surface current. The availability of an oceanographic numerical model for one of the analyzed cases also allowed us to attempt to interpret the effect of the typical thermohaline circulation pattern on the Doppler anomaly.