Tag Archive: LiDAR data processing

Modelling of Road Assets using mobile point cloud data

Another feather in SBL’s cap. SBL was recently awarded a road asset mapping project from mobile point cloud data by a reputed firm of chartered land surveyors in the UK. The project area was mapping a stretch of the A937 highway passing through the town of Laurencekirk, Scotland, UK (see image below).


Figure 1 – Project extents shown by highlighted blue and green lines

The length of road that was mapped was 2.3 kms and all road furniture (top and bottom of curbs, road edges, hedges and gates and walls etc.) markings (parking marks, bus stop marks etc) was captured to a high degree of accuracy. A major challenge in the project was that the input point cloud data was provided without RGB values since the mobile LiDAR survey was carried out at night.
SBL carried out the detailed mapping from the mobile point cloud data using “as is”, rule without generalizing or offsetting any feature. Cross section views at distances of less than 7m were used to capture the data to the highest possible accuracy. Check out the images below which depict graphically the level of expertise and care that was taken by the team at SBL to execute the project.


Figure 2- Input point cloud data (Isometric View)


Figure 3 – Profile view of the curb drawn with vertexes


Figure 4 – Digitized top and bottom of curbs


Figure 5 – Modelling of street markings

A significant achievement on this project was that SBL provided a “first time right” work with high levels of accuracy in a very short turnaround time of 4 working days. This was possible only because of the dedication and expertise of the LiDAR modelling team of SBL. We hope to come up with more such success stories in the coming days, so stay tuned.

GIS 3D feature extraction and modelling for railways using LIDAR technology

With the global drive towards Building Information Modelling (BIM) compliance gathering pace, we have seen an increased requirement for highly accurate and detailed geospatial data within utilities and engineering projects. This has resulted in a corresponding increase in the application of LIDAR technology within these sectors.

In particular, railways have a wide range of complex and critical assets that extend across the rail network. LiDAR survey point cloud data and feature extraction has become an accurate and effective means of modelling, sharing, managing and storing large asset information databases of this sort.

The primary benefit of LIDAR technology lies in its ability to capture assets in 3D. For rail networks, train mounted LIDAR equipment is on the increase because it allows accurate, dense point clouds to be acquired along with the RGB images from the in-cabin video. Having worked on a number of such high-profile projects, SBL has built up a large team of LIDAR modellers and analysts who can process and extract the full range of railway features and assets.

Fig 1 A wire frame model of a sample gantry derived from LIDAR point clouds

Railway assets include electrical network and equipment, telecommunication network and equipment, tracks and related features, signal systems and station assets. The advantage of deriving 3 dimensional data from LIDAR point clouds is that it will be accurate to a millimetre level. All the peripheral equipment can be modelled in a 3D environment as well. Along the tunnel sections of the network LiDAR is the only technology that can provide comprehensive, highly accurate information on assets.

Fig 2 station and its component assets as captured from LIDAR point clouds

Mapping to high detail and then rendering in various model platforms is the key to usage of LIDAR based capturing of railway assets. All features within the corridor width of the tracks can be captured to the same very high detail. Stations have innumerable assets components but all these components can be captured effectively using LIDAR point clouds. The creation of a real world situation using 3D models has attracted the attention and approval of many of SBL’s stakeholders and partners. Our LIDAR analysts have achieved these impressive results through 3D wire frame and surface modelling. These models were created and delivered in global GIS formats such as .dgn or .dwg or gml.

Fig.3 A tunnel section captured from point clouds

This kind of LIDAR technology based railway mapping will benefit different disciplines in different ways. This database will act a pre indicator for drivers and is of great help in their training. For construction engineers it is a monitoring mechanism. For design engineers it the only information provide kinematics of the entire system. For maintenance and operation teams it is a database where they can pinpoint hot spots where repairs are required allowing ground staff to be sent directly to those locations. Using this database a virtual railway stations and tracks can be created for various applications. Overall asset and facilities management will be greatly improved with such a 3-dimensional database.



Management of road networks and its associated assets is a huge task for all transportation agencies around the world. The traditional ways of collection of data was time consuming and the productivity of the staff was at the best average. With the advent of new technologies like Mobile LiDAR Mapping, the collection, assimilation, analysis, design, construct, maintain and storage of data has become very fast, accurate and cost sensitive This dynamic system of mensuration can be used to acquire highly accurate and compact 3D statistics by safely driving a gathering vehicle at public road speeds

Mobile Lidar systems is made up of of four different devices: a laser, a scanner, a photodetector and a GPS/IMU positioning system. These four systems assimilate to measure the distance to an object by lighting the target with throbs of light from the laser instrument and gauging the time it takes for each throb to bounce back to the sensor. For the reason that light moves at a persistent and known speed, the distance between the laser instrument and an entity can be measured with a high degree of accuracy. A briskly firing laser can cover entire scenes in a few strokes, visualizing the topography and extracting data. A highly capable processing software then transforms raw data into colorful 3-D point clouds, and the end results are multifaceted, high-resolution maps.

Collection of detailed, high accuracy street-level data of street framework is expedited by having instruments capable of reading GPS/IMU on a automobile platform, achieving immense extents of GIS-friendly LiDAR point cloud data in short amount of time. Terrestrial LiDAR system is competent to see data flanked by buildings and under tree canopy, which airborne systems, will never be able to capture. Mobile mapping systems usually collect a full 360-degree FOV at a speed of 30-40 kilometers per hour. The data collected will be highly precise and can be used to generate convincing 3D data and highly accurate road maps.


Geo-referencing factor of mobile mapping is akin in idea to airborne platforms, but distinctive in run through. It is not possible to keep the GPS lock all the way through an entire mobile survey. The mobile platform must be able to traverse, and accurately map, below tree canopy, under bridges, without loss of positional accuracy. The IMU system become judgmentally important. The airborne system necessities for GPS/IMU quality basically do not apply in these situations.

As is the case with every mapping application, supplementary imagery and substantial data post-processing is often crucial to producing GIS or CAD-compatible final products. The processing applications necessitate solid surfaces with unambiguously defined edges, and topologically-structured feature objects (points, lines, and polygons) with widespread data description and attribution. The time and effort involved in taking out these features from LiDAR point clouds has been a process only knowledgeable persons can work out. This needs special LiDAR/Point cloud processing software and custom data formats, as is for airborne or fixed systems, transfers over to mobile systems and is augmented by the steep quantity and intricacy of the data acquired.

Incorporation of mobile mapping data, generating exhaustive data for highways and metropolitan infrastructure) with mobile topographic LiDAR survey generated terrain models and oblique imagery is sure to turn into the gold standard for street mapping and visualization in the very near future.


Operational administration of green assets such as forests and urban green cover ordinarily necessitates reliable, timely and well-run information about its developments and current status. Tree count management is important for sustaining conservational stability and ecological biodiversity. A systematic tree inventory of the forested areas and in the urban areas can help us involvedly view the causes of decline of forests in the area, decline in green cover in urban areas etc. and assist in decision making. Customary methods for counting trees are labor-intensive catalogue in the field or on an elucidation of large scale aerial photographs. Nevertheless these methods are pricey, time consuming and not pertinent to large, sequestered areas. Remote sensing technology know-how is the operational method for management and monitoring of green resources.
Polygon with tree point

There are different methods of getting the remotely sensed data, like the ones listed below.
2.Satellite Images
3.UAV/Drone Images
4.Terrestrial Photogrammetry

LiDAR methods of data collection is progressively used in forestry applications but also employed in urban environments for green cover calculations, tree canopy mapping and tree counting. Vast point clouds are usually converted software specific readable formats and are used to do the mapping for the tree counting and urban forestry mapping.
Tree Location and count

Satellite Images
One of the most important resources in the earth that needs constant monitoring and needs to be accurately measured for effective management is forest resources. Remotely sensed high-resolution or very high resolution satellite image data are crucial in this management, since it provides detailed information to administrators and planners for better decision making

UAV/Drone Images
Hyperspectral remote sensing, which uses the modern satellite sensors ability to capture the data in multiple-bands, in amalgamation with a properly updated land information system is understood to be a worthy technique to assist in making fast decisions. The practice of using Unmanned Aerial Vehicle (UAV) platform for many remote sensing applications is done to combine the advantages of traditional remote sensing techniques and the inexpensiveness of operating such techniques. UAV drones can fly at varying altitudes subject to the objective of the mission and end-result type. This tractability allows for optimization of the procedures according the meteorological conditions over a given area and the user requirements.

Terrestrial Photogrammetry
Tree counting is crucial for cultivated area and environmental management, biodiversity monitoring and many other applications. Regardless of the factor that satellite and aerial images have been widely used to distinguish, demarcate and count individual tree in urban areas and forested lands, till such techniques becomes widely accessible and knowledge of processing such data is increased, the traditional methods still hold the sway and might be detrimental for the green cover we all wish to have.

Use of Airborne LIDAR in Transmission Line Projects

The growing energy demand is an issue that power utility authorities incessantly face. The creation of new transmission lines is not always probable due to complications in acquiring rights-of-way and obtaining environmental approvals. Airborne LIDAR uses a precise laser scanning technology that offers decidedly accurate terrain and tower elevation data for the transmission line corridor. The advanced software tools allow the analysis of critical distances, obstacles identification, slackness calculation, catenary shape calculation, and location of structures besides allowing data to be exported to specialized engineering softwares.
GIS plays an important role regarding operation planning, data maintenance and design of transmission lines. A great amount of data is required for the operation and maintenance of data related to transmission lines, which includes property ownership data, corridor land use/land cover (LULC), transmission line situation and characteristics. The physical features of the lines and corridor LULC are determined during construction but has to be updated due to the constant change in surroundings during the lifetime. Automation of technological procedures involved in data collection, integration and processing will ensure increased efficiency in the management of the utilities. Dispensation of the data discusses to the production of complete topographic GIS products including their custom-made presentation and analysis.
LIDAR (Light Detection and Ranging) is a contemporary remote sensing technique for the collection of high density and accurate topographic data, which allows high-speed and economical data acquisition of power utility networks. LIDAR together with GIS technology offers efficient tools for database management and analysis.

Fig 1. LIDAR components

Fig 1. LIDAR components

Further to range measurements, some LiDAR systems are also adept in registering the intensity of the backscattered laser pulse. Intensity is defined as the ratio of strength of reflected laser to that of emitted laser, and is influenced mainly by the reflectance of the reflecting object (Song, 2002). Reflectance deviates with material characteristics so that different materials have different reflectance. Therefore intensity images may be supplementary information for a LULC classification. The merging of intensity images with Elevation information produces an image where features can be easily identified. Intrinsic to the collection process the above mentioned images are ortho-rectified images facilitating in the collection of required data for a GIS System. These ortho-images can be used as location image references to maintain or to update an existing GIS database.

Figure 2 – (a) Intensity Image (b) Image obtained by fusing intensity information with elevation information.

Results of the managed LIDAR data consists of 3D information about cables, structures as well as all hindrances along the corridor in a form of a point cloud with X, Y, Z coordinates and intensity value. Post-processing actions are needed in order to classify features and to develop additional information. Ground and cable points are categorized using algorithms available in TerraScan software.


Among the non-ground points power lines strings can be captured using top views and need to ensure that it connects all the towers. This classification is the result of analysis by an automated filter developed which detects all LIDAR hits returns from the power lines and can be categorized as wires. Towers were also can be detected in a similar way. Critical points can be detected along the transmission lines and exact height needs to be assigned to each object. 50m either side of the transmission lines can be considered for object search and exact height of the objects can be derived. The objects encountered will be houses and vegetation in general. A vegetation clearance report will help to details location of the critical points and its complete information.
LIDAR technology provides a well-organized collection of high density and accurate topographic data, being one of the most recognized cost-effective and high-speed method to such projects. Above and beyond the obstacles and vegetation along the corridor, the location and height of the prevailing towers can be derived precisely. The high density of the laser points enables accurate delineation of the cables as well as the derivation of the connection points. LIDAR in concurrence with GIS methodologies provides efficient database updating and analysis.

Rail Utility mapping and digital asset preparation from 3D point clouds

Light Detection And Ranging (LiDAR) technology provides most accurate input data source for utility mapping. High accuracy, operation from multiple platforms, and ability to survey through tunnels makes this technology unique for rail utilities. Lidar data can be acquired in discrete patches and later register to get a complete 3D point cloud of the rail corridor. Hence data handling and processing will be faster when comparing with other technologies. Another added advantage is that its feasibility to get minute details of the intricate features. Ability to collect RGB values along with intensity makes this technology most relevant for 3D model preparations. This will be of great help to rail engineering, designing and maintenance and constructing organizations. So survey grade spatial information can be collected in a faster pace with this kind of data. More over this data can be processes in multiple software platforms like Auto CAD, Leica Cyclone, Terra, Micro station and combination of these.


Digital rail asset mapping

The mail application of lidar survey in rail utility mapping area

  • 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 Gantry

Sample Gantry

Rail right of way area is an asset intensive corridor. So mapping these corridors is labor intensive. SBL has got the technical capabilities to map, capture features and model them in a 3D environment for various design and maintenance activities. In a recent project SBL geo spatial team has collected an exhaustive list of more than 100 features related to rail assets. These are ranging 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 has 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 has been created by classifying the data to 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

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

Sample over bridge

Rail operators are benefited in using such kind of data due to

  • It 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