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Il futuro della fotogrammetria nella geomatica

Authors: M. Scaioni;

Il futuro della fotogrammetria nella geomatica

Abstract

This editorial reports the content of a keynote given during a workshop organized by the SIFET (on 12th November 2021) in the University IUAV (Venice, Italy) to celebrate the 70th anniversary of its establishment. In a first part, some useful elements to better understand and define the main topic are discussed: pieces of literature, definition of Photogrammetry, national/international societal missions and projects, scientific research and publications. In the central part of the editorial, the main developing directions for the discipline are reported. These are organized in three categories: sensors, methodologies and applications. Among sensors, potential developments for imaging and ranging from multiple platforms and for sensor integration are illustrated. Among methodologies, the analysis concerns data acquisition and planning using robots, big data and ubiquitous ‘geo-’sensing, artificial intelligence, and cloud computing. Among applications the focus is on the setup of digital twins, with special emphasis on constructions and the built environment, on techniques for virtual/augmented/mixed reality, on monitoring (deformations and change detection), and on Cultural Heritage (CH). In this domain, Photogrammetry will continue to support conservation and preservation, but will be also likely to foster promotion and fruition of CH. In the end, some conclusions and considerations about the future of Photogrammetry are drawn. Technology foresight is recognized as an important tool to help facing the challenges of the future.

Country
Italy
Related Organizations
Keywords

laser scanning, Geomatics, Photogrammetry, Technology Foresight

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green