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The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Articles | Volume XLVIII-G-2025
https://doi.org/10.5194/isprs-archives-XLVIII-G-2025-1035-2025
© Author(s) 2025. 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-G-2025-1035-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
30 Jul 2025
| 30 Jul 2025
LiDAR-driven Topographic Surveys for Floodplain Management
Eva Savina Malinverni
Università Politecnica delle Marche, Dipartimento di Ingegneria Civile Edile e Architettura (DICEA), Italy
Francesco Di Stefano
Università Politecnica delle Marche, Dipartimento di Ingegneria Civile Edile e Architettura (DICEA), Italy
Stefano Chiappini
Università Politecnica delle Marche, Dipartimento di Ingegneria Civile Edile e Architettura (DICEA), Italy
Giovanna Darvini
Università Politecnica delle Marche, Dipartimento di Ingegneria Civile Edile e Architettura (DICEA), Italy
Davide Fronzi
Università Politecnica delle Marche, Dipartimento di Scienze e Ingegneria della Materia, dell'Ambiente ed Urbanistica (SIMAU), Italy
Roberto Pierdicca
Università Politecnica delle Marche, Dipartimento di Ingegneria Civile Edile e Architettura (DICEA), Italy
Alberto Tazioli
Università Politecnica delle Marche, Dipartimento di Scienze e Ingegneria della Materia, dell'Ambiente ed Urbanistica (SIMAU), Italy
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Short summary
Short summary
We analyzed the water budget of nested karst catchments using simple methods and modeling. By utilizing the available data on precipitation and discharge, we were able to determine the response lag-time by adopting new techniques. Additionally, we modeled snow cover dynamics and evapotranspiration with the use of Earth observations, providing a concise overview of the water budget for the basin and its subbasins. We have made the data, models, and workflows accessible for further study.
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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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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
F. Di Stefano, A. Gorreja, E. S. Malinverni, and C. Mariotti
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIV-4-W1-2020, 19–26, https://doi.org/10.5194/isprs-archives-XLIV-4-W1-2020-19-2020, https://doi.org/10.5194/isprs-archives-XLIV-4-W1-2020-19-2020, 2020
C. Morbidoni, R. Pierdicca, R. Quattrini, and E. Frontoni
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIV-4-W1-2020, 95–102, https://doi.org/10.5194/isprs-archives-XLIV-4-W1-2020-95-2020, https://doi.org/10.5194/isprs-archives-XLIV-4-W1-2020-95-2020, 2020
S. Chiappini, A. Fini, E. S. Malinverni, E. Frontoni, G. Racioppi, and R. Pierdicca
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B4-2020, 441–448, https://doi.org/10.5194/isprs-archives-XLIII-B4-2020-441-2020, https://doi.org/10.5194/isprs-archives-XLIII-B4-2020-441-2020, 2020
F. Matrone, A. Lingua, R. Pierdicca, E. S. Malinverni, M. Paolanti, E. Grilli, F. Remondino, A. Murtiyoso, and T. Landes
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2020, 1419–1426, https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-1419-2020, https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-1419-2020, 2020
E. S. Malinverni, R. Pierdicca, M. Paolanti, M. Martini, C. Morbidoni, F. Matrone, and A. Lingua
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W15, 735–742, https://doi.org/10.5194/isprs-archives-XLII-2-W15-735-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W15-735-2019, 2019
M. Paolanti, R. Pierdicca, M. Martini, A. Felicetti, E. S. Malinverni, E. Frontoni, and P. Zingaretti
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W15, 871–878, https://doi.org/10.5194/isprs-archives-XLII-2-W15-871-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W15-871-2019, 2019
E. S. Malinverni, S. Chiappini, and R. Pierdicca
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W11, 771–776, https://doi.org/10.5194/isprs-archives-XLII-2-W11-771-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W11-771-2019, 2019
E. S. Malinverni, F. Mariano, F. Di Stefano, L. Petetta, and F. Onori
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W11, 777–784, https://doi.org/10.5194/isprs-archives-XLII-2-W11-777-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W11-777-2019, 2019
E. S. Malinverni, R. Pierdicca, F. Di Stefano, M. Sturari, M. Mameli, E. Frontoni, R. Orazi, and F. Colosi
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W11, 785–792, https://doi.org/10.5194/isprs-archives-XLII-2-W11-785-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W11-785-2019, 2019
R. Quattrini, R. Pierdicca, A. Lucidi, F. Di Stefano, and E. S. Malinverni
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W9, 647–654, https://doi.org/10.5194/isprs-archives-XLII-2-W9-647-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W9-647-2019, 2019
G. Fangi, R. Pierdicca, M. Sturari, and E. S. Malinverni
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2, 331–337, https://doi.org/10.5194/isprs-archives-XLII-2-331-2018, https://doi.org/10.5194/isprs-archives-XLII-2-331-2018, 2018
R. Pierdicca, E. S. Malinverni, F. Piccinini, M. Paolanti, A. Felicetti, and P. Zingaretti
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2, 893–900, https://doi.org/10.5194/isprs-archives-XLII-2-893-2018, https://doi.org/10.5194/isprs-archives-XLII-2-893-2018, 2018
E. S. Malinverni, R. Pierdicca, M. Sturari, F. Colosi, and R. Orazi
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-5-W1, 203–210, https://doi.org/10.5194/isprs-archives-XLII-5-W1-203-2017, https://doi.org/10.5194/isprs-archives-XLII-5-W1-203-2017, 2017
R. Quattrini, R. Pierdicca, C. Morbidoni, and E. S. Malinverni
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-5-W1, 275–281, https://doi.org/10.5194/isprs-archives-XLII-5-W1-275-2017, https://doi.org/10.5194/isprs-archives-XLII-5-W1-275-2017, 2017
E. S. Malinverni and R. Pierdicca
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W3, 459–465, https://doi.org/10.5194/isprs-archives-XLII-2-W3-459-2017, https://doi.org/10.5194/isprs-archives-XLII-2-W3-459-2017, 2017
E. S. Malinverni, C. Conati Barbaro, R. Pierdicca, C. A. Bozzi, and A. N. Tassetti
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B1, 1149–1155, https://doi.org/10.5194/isprs-archives-XLI-B1-1149-2016, https://doi.org/10.5194/isprs-archives-XLI-B1-1149-2016, 2016
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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