Slope Drainage Monitoring and Watershed Analysis
LiDAR and geospatial analysis of rail corridor slopes for inspection and monitoring of slope drainage assets
PROJECT OVERVIEW
The network maintenance team of a major rail operator were required to conduct routine inspection and maintenance on an extensive network of slope drains which existed throughout a remote and rugged stretch of corridor.
The steep slopes, remote location, and relative difficulty of access to this stretch of the rail corridor meant that conventional on-foot inspections has been delayed and postponed for a number of years due to safety concerns and difficulty of physically gaining access.
PROJECT SCOPE
DIODRONE SOLUTION
Diodrone utilised a LiDAR based methodology to assess the presence of vegetation and to confirm where maintenance works had been adequately completed. Drone-based imagery was used to supplement the LiDAR survey and provide a visual record of the top-drain condition in areas where canopy cover permitted.
LiDAR captured by Diodrone in 2019 was compared to LiDAR captured by Diodrone in 2020 to verify where vegetation removal works had been adequately completed by specialist contractors and allow the asset engineer to certify the maintenance activities.
Tripod mounted laser scanning Analysis of drone-LiDAR and imagery enabled inspection of slope drains and an assessment of function, while eliminating working at heights and on-foot access.
Additionally, watershed analysis was carried out on a LiDAR derived digital elevation model to provide an indication of drainage function and identify areas where further drainage maintenance or upgrade may be required.
![LiDAR analysis to verify removal of vegetation defects and debris to indicate function of slope drainage](https://fgdiodrone.wpengine.com/wp-content/uploads/2021/01/IMG_Lidar-analysis_vegetation-defects_northern-line.png)
![Watershed analysis to indicate function of slope drainage](https://fgdiodrone.wpengine.com/wp-content/uploads/2021/01/IMG_watershed-analysis_northern-line-1400x668.png)