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The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Articles | Volume XLVIII-4-2024
https://doi.org/10.5194/isprs-archives-XLVIII-4-2024-389-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/isprs-archives-XLVIII-4-2024-389-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
21 Oct 2024
| 21 Oct 2024
Augmented Reality for Air Quality Monitoring: Case Study in the Marche Region (Italy)
Marsia Sanità
Dipartimento di Ingegneria Civile, Edile e Architettura (DICEA), Università Politecnica delle Marche, Via Brecce Bianche 12, 60131 Ancona, Italy
Jonathan Fratini
Dipartimento di Ingegneria Civile, Edile e Architettura (DICEA), Università Politecnica delle Marche, Via Brecce Bianche 12, 60131 Ancona, Italy
Nikhil Muralikrishna
Dipartimento di Ingegneria Civile, Edile e Architettura (DICEA), Università Politecnica delle Marche, Via Brecce Bianche 12, 60131 Ancona, Italy
Roberto Pierdicca
Dipartimento di Ingegneria Civile, Edile e Architettura (DICEA), Università Politecnica delle Marche, Via Brecce Bianche 12, 60131 Ancona, Italy
Eva Savina Malinverni
Dipartimento di Ingegneria Civile, Edile e Architettura (DICEA), Università Politecnica delle Marche, Via Brecce Bianche 12, 60131 Ancona, Italy
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Short summary
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For the processing of geomatics data, artificial intelligence (AI) offers overwhelming opportunities. The integration of AI approaches in geomatics has developed into the concept of geospatial artificial intelligence (GeoAI), which is a new paradigm for geographic knowledge discovery and beyond. This contribution outlines AI-based techniques for analysing and interpreting complex geomatics data. How AI approaches have been exploited for the interpretation of geomatic data is explained.
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