Maltese, Antonino

In this poster we present the realization and the surveys performed to establish a new reference gravity and elevation network in Sicily with the aim to provide new reference systems useful for all the scientific and technological activities related to the gravity field and to the proper definition of a modern height system in this region. This network belongs to the under construction new Italian Reference Gravity Network (G0) that is part of the INGV Project Pianeta Dinamico, Task S2, during the period 2019-2022. The Sicilian network encloses 5 stations (Catania, Centuripe, Milazzo, Noto, and Palermo), evenly distributed forming a large mesh network which roughly covers the entire Sicily (Fig.1). All absolute stations are hosted inside structures that guarantee protection for the instrumentation during the measurements and the necessary power supply. In addition to the absolute gravity value, at each station, the vertical gravity gradient and the gravity difference (Δg) between the indoor absolute gravity and an outdoor satellite station were also measured. Gravity measurements were carried out between the end of 2021 and the 2022 with the Microg LaCoste FG5#238 and the Scintrex CG-6 gravimeters for absolute and relative measurements, respectively. Gravity data have been corrected for known effects ensuring the reliability and accuracy at the µGal level. The coordinates and the orthometric heights were at the same time measured with mixed terrestrial and satellite local networks at each site. The precise coordinates obtained after the adjustments were useful to post-process the absolute gravity data and to refer all the gravity measurements presented in this work to the equipotential surface of the gravity field. Since three of the five selected stations were measured in the past, it was also possible to evaluate the long-term stability of the gravity values at these stations.

Services from the Continuously Operating Reference Stations (CORS) of the Global Navigation Satellite System (GNSS) provide data and insights to a range of research areas such as physical sciences, engineering, earth and planetary sciences, computer science, and environmental science. Even though these fields are varied, they are all linked through the GNSS operational application. GNSS CORS have historically been deployed for three-dimensional positioning but also for the establishment of local and global reference systems and the measurement of ionospheric and tropospheric errors. In addition to these studies, CORS is uncovering new, emerging scientific applications. These include real-time monitoring of land subsidence via network real-time kinematics (NRTK) or precise point positioning (PPP), structural health monitoring (SHM), earthquake and volcanology monitoring, GNSS reflectometry (GNSS-R) for mapping soil moisture content, precision farming with affordable receivers, and zenith total delay to aid hydrology and meteorology. The flexibility of CORS infrastructure and services has paved the way for new research areas. The aim of this study is to present a curated selection of scientific papers on prevalent topics such as network monitoring, reference frames, and structure monitoring (like dams), along with an evaluation of CORS performance. Concurrently, it reports on the scientific endeavours undertaken by the Geomatics Research Group at the University of Palermo in the realm of GNSS CORS over the past 15 years.

The aim of this research is to use hyperspectral MIVIS data to map the Posidonia oceanica prairies in a coastal lagoon (Stagnone di Marsala). It is approximately 12 km long and 2 km wide and is linked to the open sea by two shallow openings. This environment is characterised by prairies of phanerogams, the most common of which is Posidonia oceanica, an ideal habitat for numerous species of fish, molluscs and crustaceans. A knowledge of the distribution of submerged vegetation is useful to monitor the health of the lagoon. In order to classify the MIVIS imagery, the attenuation effects of the water column have been removed from the signal using Lyzenga’s technique. A comparison between classifications using indices obtained using band pairs from only the first spectrometer, and using band pairs of the first and second spectrometers, shows that the best classification is obtained from some indices derived from the first spectrometer. Field controls carried out in July 2002 were used to determine the training sites for the supervised classification. Twelve classes of bottom coverage were obtained from the classification, of which four are homogeneous and eight are mixed coverage. The methodology applied demonstrates that hyperspectral sensors can be used to effectively map submerged vegetation in shallow waters.