LiDAR and Rail Utility Mapping and Digital Asset Preparation

Light Detection And Ranging (LiDAR) technology provides the most accurate input data source for utility mapping. High accuracy, operation from multiple platforms, and the ability to survey through tunnels makes this technology essential for mapping rail utilities. LiDAR data can be acquired in discrete patches and later registered to get a complete 3D point cloud of the rail corridor. As a result, data handling and processing will be faster when compared with other mapping and data gathering technologies. Another added advantage is LiDAR’s ability to get minute details of intricate features.  The ability to collect RGB values along with intensity makes this technology most relevant for 3D model preparations. LiDAR data collection is an asset to rail engineering, designing and maintenance and constructing organizations. Using LiDAR, survey grade spatial information can be collected more quickly. Moreover, this data can be processed in multiple software platforms such as Auto CAD, Leica Cyclone, Terra, Microstation and ArcGIS.

Digital rail asset mapping

The use of of LiDAR survey data in rail utility mapping is useful for the following:

• Condition assessment of tracks and switches
• Digital rail asset register preparation
• Signage management
• Vegetation encroachment monitoring
• Corridor monitoring
• Corridor design
• Corridor maintenance
• Kinetic monitoring

Sample LiDAR rail mapping 

Rail right of way areas are asset intensive corridors. So mapping these corridors can be labor intensive. SBL has the technical capabilities to map, capture features and model them in a 3D environment for various design and maintenance activities. In a recent project the SBL geo spatial team collected an exhaustive list of more than 100 features related to rail assets. These features ranged from base structures to huge bridges. Presentation of output files in various 3D models pertaining to rail assets was one of the peculiarities of the project. SBL prepared the data in 3D wire face model, 3D surface model, MX GENIO format as well as in Lexica true view formats. Initially, all the features were captured as wire frames and later converted to surface models. A digital terrain model of the area was created by classifying the data into ground and non ground categories. Trimming adjustment with digital terrain models were performed to bring the features to ground level and to obtain accurate height of the features.

Sample electrical structure

Challenges of using lidar data in rail corridor mapping are a). Possibility of features missing due to low intensity of the point clouds, b). Masking of the features due to presence of debris, c). Blockage of features due to presences of temporary articles present over the area and d). Registration related issues.

Sample over bridge

Rail operators benefit from using LiDAR data due to:

• LiDAR provides a complete digital record of all assets
• Change detection is very easy
• Encroachment of vegetation, unauthorized occupation and missing of features can be monitored
• Condition assessment is very easy
• Standard maintenance programme can be implemented and managed effectively.
• Alternate and optimal routes can be established for new tracks and yards
• Prefeasibility studies will became easy

About the Author:

Venugopal is the Insightful Senior Manager (Projects – Geospatial) of SBL. Having rich experience in preparing project proposals and effort estimation for international, national and governmental bids, project formulation reports, schedule charts, project plans and resource plans, he has hands on experience in developing project specification reports and process flows for the projects. He has sound experience in Groundwater Exploration (Hydrogeological); Site selection for exploratory tube wells, feasibility studies for the proposed tube wells. Venugopal is skilled in the development of Digital Elevation Model (DSM & DTM) and monitored drilling activities, conducted long duration aquifer pumping test for determination of aquifer characteristics. His vast experience line involved adept management of a highly efficient and multi-talented Remote Sensing Team. Venugopal is a post graduate in M.Sc. (Applied Geology), Barkatullah University, Bhopal, India and he is adorned with a double M.Tech degree – M.Tech in Remote Sensing from Bharathidasan University, Trichy, India and M.Tech in Hydrology from Indian Institute of Technology, Roorkee, India.