Häftad, Engelska, 2025
Probabilistic Vision of the Physical World
A Point of View of Earth Sciences
Av Fernando Sansò, Alberta Albertella
Del i serien Lecture Notes in Geosystems Mathematics and Computing
1512 kr
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Beskrivning
Produktinformation
- Utgivningsdatum: 2025-05-16
- Mått: 155 x 235 x 10 mm
- Vikt: 248 g
- Format: Häftad
- Språk: Engelska
- Serie: Lecture Notes in Geosystems Mathematics and Computing
- Antal sidor: 139
- Förlag: Birkhauser Verlag AG
- ISBN: 9783031882678
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Fernando Sansò is professor emeritus at the Polytechnic University of Milan and a Honorary President of the International Association of Geoscience (IAG). He established the International Geoid Service in 1992 and served as its President until 2011. He is a full member of the Accademia dei Lincei, a fellow of the Royal Astronomical Society (UK), and the president of Geomatics and Research Development (GReD), which he founded in 2012. His research areas include gravity field modelling, boundary value problems, statistics, generalized random fields, and GNSS theory.Sansò has received numerous accolades, including the Bomford Prize for Geodesy in 1979 and the Feltrinelli Award for Astronomy, Geodesy, Geophysics, and Applications in 1986. He holds honorary doctorates from the University of Copenhagen, the University of Thessaloniki, and the University of Stuttgart. Throughout his career, he has (co)-authored over 500 works.Alberta Albertella is Associate Professor of Geodesy at Politecnico di Milano. She earned her Ph.D in Geodetic, Surveying, and Photogrammetric Sciences from the Politecnico of Turin, Italy, in 1993. She has conducted extensive research in satellite geodesy, specializing in satellite gradiometry and gravity field determination. She contributed to multiple European and Italian satellite missions,. From 2005 to 2012, she was a research partner in the German project GEOTOP, which focused on ocean circulation using geodetic observations. Her expertise includes statistical and numerical data analysis for physical geodesy, geoid estimation, Bayesian methods, and remote sensing. She has also worked on digital mapping, GIS applications, and contributed to Citizen Science projects.
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