Bianca Federici
Bianca Federici is Professor of Geomatics at the University of Genoa (Italy). She teaches in several courses related to surveying techniques and GIS, with special focus on FOSS solutions. Her research mainly concerns the analysis of geospatial data in GIS and remote sensing for environmental analysis, as well as surveying and monitoring of natural and built environments.
In collaboration with several multidisciplinary research groups, she has developed GIS tools for assessing the susceptibility of rainfall-triggered landslides to collapse, for forecasting intense weather events using GNSS measurements, for assessing collision risk in logistical areas, for identifying areas potentially inundated by rivers or tsunamis, for planning GNSS survey campaigns taking into account real obstacles in the area, as well as techniques for extracting seawater turbidity or bathymetry of shallow waters from optical satellite images. She has over 120 scientific research papers.
She is currently a member of the executive committee of GFOSS.it. She was co-chair of the FOSS4G 2022 international conference, she organized or participated in the organization of the Italian GRASS GIS Users Meeting in 2007 and 2013, the Italian OSMit2010 Conference and several Italian FOSS4G conferences since 2017. She has been a member of their scientific committees.
Sessions
Morphodynamics aims to predict the evolution of the topography of rivers, estuaries, and coastal regions under different environmental forcings. Understanding the stability of such systems is a fundamental issue which may help the management of these areas in terms of flood control, erosion prevention, and habitat restoration.
Although the study of morphodynamics has made great progress over the decades, even from a theoretical point of view, models need data to be tested and eventually used in machine learning algorithms. From this point of view, remote sensing is a powerful tool that provides data and a way to monitor changes in these systems over time.
The processing of open images from Sentinel-2 (https://sentinel.esa.int/web/sentinel/missions/sentinel-2) satellite can support the study of the morphodynamic evolution of river, estuaries, and coastal environments. By collecting multispectral images and using appropriate algorithms, the water depth of riverbed and seafloor can be derived, the emerged and submerged areas can be classified automatically into types of bedrocks or vegetation. In addition, satellite images can be used to derive parameters, such as channel width, the evolution of which over time indicates erosion or deposition processes, and water turbidity, which can be an indicator of suspended sediment transport. Hence, data collected through image analysis provides a useful tool for morphodynamic modelling.
We propose combining remote sensing and morphodynamic modelling for a comprehensive river system assessment. This integrated approach can provide an accurate understanding of river morphology, hydrodynamics, and sediment dynamics, supporting informed decision-making for sustainable river management. In this paper, a preliminary application of this novel approach to a case of the Roia river in Liguria is presented. The Sentinel-2 multispectral optical images are processed and integrated with in-situ measurements to create a dataset for the morphodynamic model. In particular, the Satellite Derived Bathymetry is computed to estimate the depth variations along the river course, and the image classification is performed mapping different types of riverbed features such as vegetation, water turbidity, and sedimentation (Apicella et al. 2023, Apicella et al. 2022). Such a dataset is first used to test the capacity of some existing theoretical morphodynamic models (Seminara et a al. 2012, Ragno et al.,2021) to predict the equilibrium topography of the inlet reach of the Roia river. As a second step, the stability and evolution of the system under different scenarios of river discharges and sea forcing will be investigated.
The work is carried on within the Robotics and AI for Socio-economic Empowerment – RAISE (https://www.raiseliguria.it/) project funded by the “Piano Nazionale di Ripresa e Resilienza” - PNRR (https://www.mise.gov.it/it/pnrr), aiming to create a sustainable and resilient ecosystem that supports economic development, social well-being, and environmental conservation. An application activity focuses on the hydrographic, coastal and marine environment, which are key drivers of the local economy. In this context, one of the outcomes will be the risk assessment system and vulnerability of coastal areas (deltas, river mouths and lagoons) to climate change.
Acknowledgments
This work was carried out within the framework of the project "RAISE - Robotics and AI for Socioeconomic Empowerment” and has been supported by European Union – NextGenerationEU.
References
Apicella, L.; De Martino, M.; Ferrando, I.; Quarati, A.; Federici, B. Deriving Coastal Shallow Bathymetry from Sentinel 2-, Aircraft- and UAV-Derived Orthophotos: A Case Study in Ligurian Marinas. J. Mar. Sci. Eng. 2023, 11, 671. https://doi.org/10.3390/jmse11030671
Apicella, L.; De Martino, M.; Quarati, A. Copernicus User Uptake: From Data to Applications. ISPRS Int. J. Geo-Inf. 2022, 11, 121. https://doi.org/10.3390/ijgi11020121
Ragno, N.; Tambroni, N.; Bolla Pittaluga, M. When and where do free bars in estuaries and tidal channels form? Journal of Geophysical Research: Earth Surface 2021, 126, e2021JF006196. https://doi.org/10.1029/2021JF006196
Seminara, G.; Bolla Pittaluga, M.; Tambroni, N. Morphodynamic equilibrium of tidal channels. In W. Rodi, & M. Uhlmann (Eds.), Environmental fluid mechanics: Memorial volume in honour of Prof. Gerhard H. Jirka 2012, pp. 153– 174. CRC Press. https://doi.org/10.1201/b12283