LiDAR-driven Topographic Surveys for Floodplain Management

LiDAR technology has become an essential tool for hydrological monitoring, offering high-resolution topographic data for river basin management. This study presents LiDAR-based topographic surveys conducted on the Metauro and Cesano river basins in Central Italy to improve flood risk assessment and...

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Main Authors: E. S. Malinverni, F. Di Stefano, S. Chiappini, G. Darvini, D. Fronzi, R. Pierdicca, A. Tazioli
Format: Article
Language:English
Published: Copernicus Publications 2025-07-01
Series:The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Online Access:https://isprs-archives.copernicus.org/articles/XLVIII-G-2025/1035/2025/isprs-archives-XLVIII-G-2025-1035-2025.pdf
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author E. S. Malinverni
F. Di Stefano
S. Chiappini
G. Darvini
D. Fronzi
R. Pierdicca
A. Tazioli
author_facet E. S. Malinverni
F. Di Stefano
S. Chiappini
G. Darvini
D. Fronzi
R. Pierdicca
A. Tazioli
author_sort E. S. Malinverni
collection DOAJ
description LiDAR technology has become an essential tool for hydrological monitoring, offering high-resolution topographic data for river basin management. This study presents LiDAR-based topographic surveys conducted on the Metauro and Cesano river basins in Central Italy to improve flood risk assessment and regional planning. Airborne LiDAR and ground-based GNSS techniques have been integrated to generate accurate DTMs and DSMs, enabling precise floodplain mapping and man-made structures analysis. The data processing involved automated classification and manual corrections to differentiate between terrain, vegetation, and built structures. The results provided detailed cross-sectional altimetric profiles, revealing geomorphological changes such as sediment deposition and erosion. Additionally, Airborne LiDAR-derived datasets supported flood modeling, infrastructure assessment, and long-term environmental monitoring. The study highlights the effectiveness of LiDAR data collection in hydrological management, enhancing flood risk mitigation, urban planning, and ecological restoration. Future research should focus on expanding survey coverage, integrating real-time flood forecasting, and leveraging AI-driven techniques for automated data processing. This work contributes to improved geospatial knowledge, providing decision-makers with advanced tools for sustainable surface water resource management.
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issn 1682-1750
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publishDate 2025-07-01
publisher Copernicus Publications
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series The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
spelling doaj-art-5e29d1177457455f8a191da2a2e5c7fa2025-08-20T03:09:31ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342025-07-01XLVIII-G-20251035104210.5194/isprs-archives-XLVIII-G-2025-1035-2025LiDAR-driven Topographic Surveys for Floodplain ManagementE. S. Malinverni0F. Di Stefano1S. Chiappini2G. Darvini3D. Fronzi4R. Pierdicca5A. Tazioli6Università Politecnica delle Marche, Dipartimento di Ingegneria Civile Edile e Architettura (DICEA), ItalyUniversità Politecnica delle Marche, Dipartimento di Ingegneria Civile Edile e Architettura (DICEA), ItalyUniversità Politecnica delle Marche, Dipartimento di Ingegneria Civile Edile e Architettura (DICEA), ItalyUniversità Politecnica delle Marche, Dipartimento di Ingegneria Civile Edile e Architettura (DICEA), ItalyUniversità Politecnica delle Marche, Dipartimento di Scienze e Ingegneria della Materia, dell'Ambiente ed Urbanistica (SIMAU), ItalyUniversità Politecnica delle Marche, Dipartimento di Ingegneria Civile Edile e Architettura (DICEA), ItalyUniversità Politecnica delle Marche, Dipartimento di Scienze e Ingegneria della Materia, dell'Ambiente ed Urbanistica (SIMAU), ItalyLiDAR technology has become an essential tool for hydrological monitoring, offering high-resolution topographic data for river basin management. This study presents LiDAR-based topographic surveys conducted on the Metauro and Cesano river basins in Central Italy to improve flood risk assessment and regional planning. Airborne LiDAR and ground-based GNSS techniques have been integrated to generate accurate DTMs and DSMs, enabling precise floodplain mapping and man-made structures analysis. The data processing involved automated classification and manual corrections to differentiate between terrain, vegetation, and built structures. The results provided detailed cross-sectional altimetric profiles, revealing geomorphological changes such as sediment deposition and erosion. Additionally, Airborne LiDAR-derived datasets supported flood modeling, infrastructure assessment, and long-term environmental monitoring. The study highlights the effectiveness of LiDAR data collection in hydrological management, enhancing flood risk mitigation, urban planning, and ecological restoration. Future research should focus on expanding survey coverage, integrating real-time flood forecasting, and leveraging AI-driven techniques for automated data processing. This work contributes to improved geospatial knowledge, providing decision-makers with advanced tools for sustainable surface water resource management.https://isprs-archives.copernicus.org/articles/XLVIII-G-2025/1035/2025/isprs-archives-XLVIII-G-2025-1035-2025.pdf
spellingShingle E. S. Malinverni
F. Di Stefano
S. Chiappini
G. Darvini
D. Fronzi
R. Pierdicca
A. Tazioli
LiDAR-driven Topographic Surveys for Floodplain Management
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
title LiDAR-driven Topographic Surveys for Floodplain Management
title_full LiDAR-driven Topographic Surveys for Floodplain Management
title_fullStr LiDAR-driven Topographic Surveys for Floodplain Management
title_full_unstemmed LiDAR-driven Topographic Surveys for Floodplain Management
title_short LiDAR-driven Topographic Surveys for Floodplain Management
title_sort lidar driven topographic surveys for floodplain management
url https://isprs-archives.copernicus.org/articles/XLVIII-G-2025/1035/2025/isprs-archives-XLVIII-G-2025-1035-2025.pdf
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