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The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Articles | Volume XLIX-B1-2026
https://doi.org/10.5194/isprs-archives-XLIX-B1-2026-405-2026
© Author(s) 2026. 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-XLIX-B1-2026-405-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
22 Jul 2026
| 22 Jul 2026
UAV data fusion approach to assess vegetation recovery dynamics after pipeline construction
Mattia Balestra
Department of Construction, Civil Engineering and Architecture (DICEA), Marche Polytechnic University, 60131 Ancona, Italy
Department of Agricultural, Food and Environmental Sciences (D3A), Marche Polytechnic University, 60131 Ancona, Italy
Stefano Chiappini
Department of Agricultural, Food and Environmental Sciences (D3A), Marche Polytechnic University, 60131 Ancona, Italy
Bojana Petrovic
Department of Construction, Civil Engineering and Architecture (DICEA), Marche Polytechnic University, 60131 Ancona, Italy
Department of Geology and Soil Science, Faculty of Forestry and Wood Technology, Mendel University in Brno, Czech Republic
Filippo Giusti
Hystrix – Società di ricerca, progettazione e consulenza naturalistica ed ambientale, 61032 Fano, Italy
Giacomo Quattrini
Department of Agricultural, Food and Environmental Sciences (D3A), Marche Polytechnic University, 60131 Ancona, Italy
Simone Pesaresi
Department of Agricultural, Food and Environmental Sciences (D3A), Marche Polytechnic University, 60131 Ancona, Italy
Marco Bonacoscia
Hystrix – Società di ricerca, progettazione e consulenza naturalistica ed ambientale, 61032 Fano, Italy
Roberto Pierdicca
Department of Construction, Civil Engineering and Architecture (DICEA), Marche Polytechnic University, 60131 Ancona, Italy
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Short summary
Short summary
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.
M. Balestra, S. Chiappini, A. Vitali, E. Tonelli, F. Malandra, A. Galli, C. Urbinati, E. S. Malinverni, and R. Pierdicca
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D. Abate, M. Paolanti, R. Pierdicca, A. Lampropoulos, K. Toumbas, A. Agapiou, S. Vergis, E. Malinverni, K. Petrides, A. Felicetti, and P. Zingaretti
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2022, 729–736, https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-729-2022, https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-729-2022, 2022
A. Murtiyoso, F. Matrone, M. Martini, A. Lingua, P. Grussenmeyer, and R. Pierdicca
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-2-2022, 317–324, https://doi.org/10.5194/isprs-annals-V-2-2022-317-2022, https://doi.org/10.5194/isprs-annals-V-2-2022-317-2022, 2022
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