Open Access
Open access
volume 13 issue 5 pages 377

Roll/Tip-Over Risk Analysis of Agricultural Self-Propelled Machines Using Airborne LiDAR Data: GIS-Based Approach

Daniele Puri 1
Valerio Tulliani 2
1
 
National Institute for Insurance Against Accidents at Work (INAIL), Via Fontana Candida 1, Monte Porzio Catone, 00078 Rome, Italy
2
 
Independent Researcher, 00100 Rome, Italy
Publication typeJournal Article
Publication date2025-04-30
scimago Q2
wos Q2
SJR0.570
CiteScore4.7
Impact factor2.5
ISSN20751702
Abstract

Occupational Health and Safety (OHS) in agriculture is a critical concern worldwide, with self-propelled machinery accidents, particularly tip/roll-overs, being a leading cause of injuries and fatalities. In such a context, while great attention has been paid to machinery safety improvement, a major challenge is the lack of studies addressing the analysis of the work environment to provide farmers with precise information on field slope steepness. This information, merged with an awareness of machinery performance, such as tilt angles, can facilitate farmers in making decisions about machinery operations in hilly and mountainous areas. To address this gap, the Italian Compensation Authority (INAIL) launched a research programme to integrate georeferenced slope data with the tilt angle specifications of common self-propelled machinery, following EN ISO 16231-2:2015 standards. This study presents the first results of this research project, which was focused on vineyards in the alpine region of the Autonomous Province of Trento, where terrestrial LiDAR technology was used to analyze slope steepness. The findings aim to provide practical guidelines for safer machinery operation, benefiting farmers, risk assessors, and manufacturers. By enhancing awareness of tip/roll-over risks and promoting informed decision-making, this research aims to contribute to improving OHS in agriculture, particularly in challenging terrains.

Found 
Found 

Are you a researcher?

Create a profile to get free access to personal recommendations for colleagues and new articles.
Metrics
1
Share
Cite this
GOST |
Cite this
GOST Copy
Puri D. et al. Roll/Tip-Over Risk Analysis of Agricultural Self-Propelled Machines Using Airborne LiDAR Data: GIS-Based Approach // Machines. 2025. Vol. 13. No. 5. p. 377.
GOST all authors (up to 50) Copy
Puri D., Vita L., Gattamelata D., Tulliani V. Roll/Tip-Over Risk Analysis of Agricultural Self-Propelled Machines Using Airborne LiDAR Data: GIS-Based Approach // Machines. 2025. Vol. 13. No. 5. p. 377.
RIS |
Cite this
RIS Copy
TY - JOUR
DO - 10.3390/machines13050377
UR - https://www.mdpi.com/2075-1702/13/5/377
TI - Roll/Tip-Over Risk Analysis of Agricultural Self-Propelled Machines Using Airborne LiDAR Data: GIS-Based Approach
T2 - Machines
AU - Puri, Daniele
AU - Vita, Leonardo
AU - Gattamelata, Davide
AU - Tulliani, Valerio
PY - 2025
DA - 2025/04/30
PB - MDPI
SP - 377
IS - 5
VL - 13
SN - 2075-1702
ER -
BibTex |
Cite this
BibTex (up to 50 authors) Copy
@article{2025_Puri,
author = {Daniele Puri and Leonardo Vita and Davide Gattamelata and Valerio Tulliani},
title = {Roll/Tip-Over Risk Analysis of Agricultural Self-Propelled Machines Using Airborne LiDAR Data: GIS-Based Approach},
journal = {Machines},
year = {2025},
volume = {13},
publisher = {MDPI},
month = {apr},
url = {https://www.mdpi.com/2075-1702/13/5/377},
number = {5},
pages = {377},
doi = {10.3390/machines13050377}
}
MLA
Cite this
MLA Copy
Puri, Daniele, et al. “Roll/Tip-Over Risk Analysis of Agricultural Self-Propelled Machines Using Airborne LiDAR Data: GIS-Based Approach.” Machines, vol. 13, no. 5, Apr. 2025, p. 377. https://www.mdpi.com/2075-1702/13/5/377.