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ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Articles | Volume X-1/W1-2023
https://doi.org/10.5194/isprs-annals-X-1-W1-2023-33-2023
© Author(s) 2023. 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-annals-X-1-W1-2023-33-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
05 Dec 2023
| 05 Dec 2023
A COMPARISON OF PRE-PROCESSING APPROACHES FOR REMOTELY SENSED TIME SERIES CLASSIFICATION BASED ON FUNCTIONAL ANALYSIS
M. Balestra
Department of Agricultural, Food and Environmental Sciences (D3A), Via Brecce Bianche, Ancona, 60131, Italy
R. Pierdicca
Department of Civil, Building Engineering and Architecture (DICEA), Via Brecce Bianche, Ancona, 60131, Italy
L. Cesaretti
CREA Centro di ricerca Foreste e Legno, Viale Santa Margherita, Arezzo, 52100, Italy
G. Quattrini
Department of Agricultural, Food and Environmental Sciences (D3A), Via Brecce Bianche, Ancona, 60131, Italy
A. Mancini
Department of Information Engineering (D3A), Via Brecce Bianche, Ancona, 60131, Italy
A. Galli
Department of Agricultural, Food and Environmental Sciences (D3A), Via Brecce Bianche, Ancona, 60131, Italy
E. S. Malinverni
Department of Civil, Building Engineering and Architecture (DICEA), Via Brecce Bianche, Ancona, 60131, Italy
S. Casavecchia
Department of Agricultural, Food and Environmental Sciences (D3A), Via Brecce Bianche, Ancona, 60131, Italy
S. Pesaresi
Department of Agricultural, Food and Environmental Sciences (D3A), Via Brecce Bianche, Ancona, 60131, 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.
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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
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F. Di Stefano, M. Cuevas-Gonzalez, G. Luzi, and E. S. Malinverni
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2022, 263–270, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-263-2022, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-263-2022, 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
The International Society for Photogrammetry and Remote Sensing is a non-governmental organization devoted to the development of international cooperation for the advancement of photogrammetry and remote sensing and their applications. The Society operates without any discrimination on grounds of race, religion, nationality, or political philosophy.
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