Integrated Analysis of Rockfalls and Floods in the Jiului Gorge, Romania: Impacts on Road and Rail Traffic

This study examines the impact of rockfalls and floods on road and rail traffic in the Jiului Gorge, Romania, a critical transportation corridor. Using Sentinel-1 radar imagery processed through ESA SNAP and ArcGIS Pro, alongside traffic detection facilitated by YOLO models, we assessed susceptibility to both rockfalls and floods. The primary aim was to enhance public safety for traffic participants by providing accurate hazard mapping. Our study focuses on the area from Bumbești-Jiu to Petroșani, traversing the Southern Carpathians. The results demonstrate the utility of integrating remote sensing with machine learning to improve hazard management and inform more effective traffic planning. These findings contribute to safer, more resilient infrastructure in areas vulnerable to natural hazards.

Authors

Institutions

Publication Details

Journal
Applied Sciences
Published
2024-11-08
DOI
https://doi.org/10.3390/app142210270
Citations
2
Primary Topic
Landslides and related hazards
Type
article
Field-Weighted Citation Impact
1.42
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Integrated Analysis of Rockfalls and Floods in the Jiului Gorge, Romania: Impacts on Road and Rail Traffic

Bogdan Mihai, Marian Puie
2 citations
Applied Sciences
Landslides and related hazards
1.42
article

Integrated Analysis of Rockfalls and Floods in the Jiului Gorge, Romania: Impacts on Road and Rail Traffic

Bogdan Mihai, Marian Puie
article en
2 citations

Abstract

This study examines the impact of rockfalls and floods on road and rail traffic in the Jiului Gorge, Romania, a critical transportation corridor. Using Sentinel-1 radar imagery processed through ESA SNAP and ArcGIS Pro, alongside traffic detection facilitated by YOLO models, we assessed susceptibility to both rockfalls and floods. The primary aim was to enhance public safety for traffic participants by providing accurate hazard mapping. Our study focuses on the area from Bumbești-Jiu to Petroșani, traversing the Southern Carpathians. The results demonstrate the utility of integrating remote sensing with machine learning to improve hazard management and inform more effective traffic planning. These findings contribute to safer, more resilient infrastructure in areas vulnerable to natural hazards.

Applied SciencesVol. 14(22)
University of Bucharest (RO)
Sustainable cities and communities
Openalex Percentile: Top 14%
Landslides and related hazards
1.42
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.