Mario Luiz Mascagni holds a Master’s degree in Oceanography from the Oceanographic Institute of the University of São Paulo (IOUSP), Brazil. His training has focused on Remote Sensing and Numerical Modeling of coastal morphodynamic processes, with special emphasis on coastal protection and management.
During his degree in Oceanography, she participated in the project “Oil Spill Sensitivity Charting in the Santos Basin” of the Brazilian Ministry of Environment, collaborating in the processing of data for a GIS platform oriented to coastal risk analysis.
His master’s thesis consisted of morphodynamic modeling of a river mouth at a high-energy sandy beach, using Delft3D to evaluate the enlargement of a breakwater to improve navigability at the river access bar.
In parallel to his graduate studies, he worked as a researcher at the Hydraulics Technological Center Foundation of the University of São Paulo, participating in studies with small-scale physical models of the ports Ponta da Madeira (PDM) and Terminal Ilha Guaíba (TIG), operated by VALE S.A., the largest Brazilian mining company. These projects included simulations of mooring plans, berthing and unberthing maneuvers, as well as port expansion and security studies.
After completing his master’s degree, he was a beneficiary of the PIPE/FAPESP program (Support Program for Small Innovative Enterprises), developing an accident risk warning system for coastal ports based on operational numerical models of waves, wind, currents and ship mooring. In addition, he collaborated in several coastal engineering projects applying remote sensing techniques and numerical modeling of rivers and coastal areas, acquiring experience in dredging studies, shelter works, water quality, erosion and coastal restoration.
He is currently a PhD student at the Federal University of Rio Grande do Sul (UFRGS, Brazil), where he is developing satellite-derived bathymetry (SDB) models, both through empirical methods based on spectral relationships from multispectral optical sensors, and through convolutional neural networks (CNN), in order to improve the quality of digital elevation models and reconstruct the historical morphological evolution of intertidal and shallow areas.
AREAS OF SPECIALIZATION
Coastal morphodynamic monitoring and evolution
Resilience and management of coastal ecosystems
Coastal protection and restoration works
Environmental quality and water quality modeling
Mascagni, M.L., Klein, A.H. da F., Fernandes, A.M. da R., Coelho, D.K., Santos, A.B. dos, Pool, L. (2025). Machine Learning Approaches for Tidal Data Interpolation in Satellite-Derived Bathymetry Applications.EGU25, Copernicus Meetings. https://doi.org/10.5194/egusphere-egu25-10452
Mascagni, M.L.; Klein, A.H.F.; Fernandes, A.M.R.; Coelho, D.K.; Santos, A.B.; Pool, L. (2024). Satellite-Derived Bathymetry (SDB) for Shallow Waters in Regions of High Optical Complexity Using Empirical Methods and AI – Multi-Layer Perceptron (MLP). In: 20º COLACMAR 2024, Itajaí-SC, Brasil. pp. 1542–1543.
dos Santos, A.B., Mascagni, M.L., de Souza Guckert, K., da Silva Freitas, L.P., da Rocha Fernandes, A.M., da Fontoura Klein, A.H., Coelho, D.K. (2025). Machine Learning Applied to Remote Sensing in the Context of Intertidal Zone Mapping: A Literature Review. Geomatica, 100080. https://doi.org/10.1016/j.geomat.2025.100080
Daniel, E., Harari, J., de Camargo, R., Soares, S., Mascagni, M.L., Fetter Filho, A.F.H. (2025). Sea level variation along the Brazilian coastline from the perspective of climate change. Regional Studies in Marine Science, 89, 104309. https://doi.org/10.1016/j.rsma.2025.104309
Pool, L., Mascagni, M.L., Klein, A.H.F., Carvalho, J.L.B., Lima, L.G., Costa, W.L.L., Gonçalves, R.Q., Fiorini, L.P. (2025). Revealing intertidal topography with public satellite imagery: Adaptations of the waterline method. Environmental Modelling & Software, 193, 106600. https://doi.org/10.1016/j.envsoft.2025.106600
Pinto, M.W., Mascagni, M.L., Klein, A.H. da F., Farina, L. (2024). Decadal fluctuations in sediment input and vegetation within the transgressive dunefield of Santinho, Southern Brazil. Journal of South American Earth Sciences, 143, 105013. https://doi.org/10.1016/j.jsames.2024.105013
Mascagni, M.L., Siegle, E., Tessler, M.G., Goya, S.C.Y. (2018). Morphodynamics of a wave-dominated embayed beach on an irregular rocky coastline. Brazilian Journal of Oceanography, 66, 172–188. https://doi.org/10.1590/S1679-87592018005006602
Omachi, C.Y., Siani, S.M.O., Chagas, F.M., Mascagni, M.L., Cordeiro, M., Garcia, G.D., Thompson, C.C., Siegle, E., Thompson, F.L. (2018). Atlantic Forest loss caused by the world’s largest tailing dam collapse (Fundão Dam, Mariana, Brazil). Remote Sensing Applications: Society and Environment, 12, 30–34. https://doi.org/10.1016/j.rsase.2018.08.003
