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Power Lines Classifications

According to the kind of classification analytic ordered, more or less classes will be delivered in the platform, from standard ones to custom classifications.

1. Basic LiDAR Point Cloud Classification

1.1. Usage

This analytic provides a classification of objects from a point cloud generated from LiDAR data. It classifies the power line asset and surrounding environment in 5 classes (4 standard + 1 other):

  1. Ground
  2. Vegetation
  3. Poles
  4. Conductors
  5. Other Objects Class = All other than described in 1 to 4 above

1.2. Required Input

A point cloud already pre processed (step previously carried out with a dedicated LIDAR sensor's manufacturer software) in order to obtain from flight raw data a cloud point in one of the formats listed below. Please note that raw data point cloud processing must include the correction of GPS laser points coordinates with IMU information, and also a first quality check for noise reduction on point cloud. The supported input formats and standards are :

  • Las 1.2 (*.las)
  • Las 1.4 (*.las)

Read here how to create a new LiDAR project if necessary.

1.3. Viewing Classes

Select first the 3D view from the Site main window :

Then tick and click in the Point Cloud layer, which will open the information panel on right side, with CLASSIFICATION chart :

1.4. Deliverables

For each 5 km of power line, a Basic Lidar "Clas" file named with the prefix B_LiDAR_Cl, plus a code composed by adding to power line's unique code (provided by the user and with a reference length of 9 digits) two more digits for defining the portion of line considered.

For example : a power line of 48 km will be delivered in 10 files that will be distinguished at code level by the last two digits while the prefix plus the first 9 will remain the same. Each file contains one georeferenced classified cloud point featured by 4 classes plus a fifth one to define other objects. For double circuit lines placed on the same poles and therefore interested by the same corridor, we have only one file delivered each 5km. Files are delivered in Las 1.2 standard (*.las).

1.5. Export

From the Download section, point clouds can be exported from the All other files section, for use in third-party software :

2. Advanced LiDAR Point Cloud Classification

2.1. Usage

This analytic provides a classification of objects from a point cloud generated from LiDAR data. It classifies the power line asset and surrounding environment in 9 classes (8 standard + 1 other):

  1. Ground
  2. Vegetation
  3. Poles
  4. Conductors
  5. Buildings
  6. Crossing Lines
  7. Roads
  8. Railways
  9. Other Objects Class = All other than described in 1 to 8 above

2.2. Deliverables

For each 5 km of power line a Advanced Lidar "Clas" file named with the prefix A_LiDAR_Cl, plus  a code composed by adding to power line's unique code (provided by the user and with a reference length of 9 digits) two more digits for definying the portion of line considered. For example, a power line of 48 km will be delivered in 10 files that will be distinguished at code level by the last two digits while the prefix plus the first 9 will be the same. Each file contains one georeferenced classified cloud point featured by 8 classes plus a ninth one to define other objects. For double circuit lines placed on the same poles and therefore interested by the same corridor, we have only one file delivered each 5km. Files are delivered in Las 1.2 standard (*.las).

2.3. Required Input

A point cloud already pre-processed (step previously carried out with a dedicated LIDAR sensor's manufacturer software) in order to obtain from flight raw data a point cloud in one of the formats listed below. Please note that raw data point cloud processing must include the correction of GPS laser points coordinates with IMU information,  and also a first quality check for noise reduction on point cloud. The supported input formats and standards are :

  • Las 1.2 (*.las)
  • Las 1.4 (*.las)

3. Basic RGB Classification

3.1. Usage

This analytic provides a classification of objects from a RGB dataset. It classifies the power line asset and surrounding environment in 5 classes (4 standard + 1 other) :

  1. Ground
  2. Vegetation
  3. Poles
  4. Conductors
  5. Other Objects Class = All other than described in 1 to 4 above

3.2. Deliverables

For each 5 km of power line a Basic Lidar Clas file named with the prefix B_RGB_Cl, plus  a code composed adding to power line's unique code (provided by the client and with a reference length of 9 digits)  two more digits for definying the portion of line considered. ( eg: a power line of 48 km will be delivered in 10 files that will be distinguished at code level by the last two digits while the prefix plus the first 9 will be the same). Each file contains one RGB georeferenced classified cloud point featured by 4 classes plus a 5th one to define other objects not included in the first four. For double circuit lines placed on the same poles and therefore interested by the same corrior we have only one file delivered each 5km. Files are delivered in Las 1.2 standard (*.las).

3.3. Required Input

A 3D georeferenced cloud point obtained through stereophotogrammetry. As a reminder please consider that this technique estimates the three-dimensional coordinates of points on an object employing measurements made in two or more photographic images taken from different positions. Common points are identified on each image. A line of sight (or ray) can be constructed from the camera location to the point on the object. 

It is the intersection of these rays (triangulation) that determines the three-dimensional location of the point.

Please note that raw data cloud point processing  must include correction of GPS laser point coordinates with IMU info and also a first quality check for noise reduction on cloud point.

4. Custom Classification

Delair can provide customized classification analytics upon your specific request, for your own use case, especially if other classes of objects or more than 9 classes are required, and with the level of privacy required for the application.

  • If you are not already a delair.ai user, please contact us here.
  • If you already use delair.ai, please contact your Sales Representative at Delair to discuss your requirement.

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