Everything your need to know about LiDAR

Author: Judith Morrison

You would agree 3D point cloud data is one of the most complex types of machine learning data that is used to generate the most useful training datasets for autonomous vehicles. And, LiDAR data is interpreted with a 3D point cloud to present the objects more precisely and in a detectable manner for the self-driving car. Though, you must be wondering How does it relate to, reality capture and more?

"Research shows that the global Light Detection and Ranging (LiDAR) market is estimated to reach $8.7 billion by 2025."

Through this article, I wish to provide a comprehensive overview of the essentials of 3D point cloud data with LiDAR standards for modern surveying. If it hasn’t impacted your industry yet, it will certainly soon. Advances in point cloud processing are making LiDAR more accessible than ever before.

So now is the right time to known about this technology, how it works, and how to use it.

What is LiDAR?

A methodology originated as an amalgamation of "light" and "radar". LiDAR is a surveying and remote sensing technology that uses a laser pulse to calculate measurements and distance of buildings & landscapes. It delivers precise data of objects such as roads, buildings, and sidewalks irrespective of the larger distance using the velocity of the light pulses.

What is point cloud data?

It is a collection of points that represent 3D space or objects. Each point has its own set of coordinates - X, Y and Z and additional attributes in some exceptional cases. It is generated using LiDAR and 3D lase scanners techniques and technology. Each point defines a single laser scan measurement. This combination of scans creates a complete picture of a scene using a process called registration.

Applications

LiDAR technology makes it incredibly easy to collect key data points in remote areas. It is mainly for various long-term and short-term developmental objectives.

  • Explore dangerous hidden areas and dense forest
  • Oceanography to measure ocean depth as well as phytoplankton fluorescence & biomass calculation in the ocean surface.
  • In Agriculture to create a topological map of the fields
  • Mapping features under forest canopies and helps field campaign planning in archaeology
  • To produce 3D representations of terrain elevations on the earth’s surface.
  • In military operations to survey borders, identify suspicious objects, activities, and develop high-resolution maps of remote locations.
  • To collect underwater information relating to a river’s flow depth, width and strength.

    • LiDAR Point Cloud Processing Challenges

    Just like any other state-of-the-art technology, LiDAR has its own limitations.

  • Needs line of sight access
  • Reflective surfaces cause problems for the laser
  • Not recommended for moving objects measurement
  • Bad weather can hinder data collection

    • LiDAR generates data that is complicated to understand with normal vision. So, it is often labeled with point cloud technology to identify objects with deep learning algorithms. The few challenges you need to know about 3D point cloud data includes;

    Big Volume of Data

    Raw LiDAR data generate large data sets that contain information about objects in a 3D space. This requires high configuration devices to store, manage and use such data. Thus, storing, controlling and transferring data whether to a processing point or the data warehouse is difficult.

    Complex Processing

    It is tough to process massive data. Massive computing power is utilized to process or analyze data of a single file or group of files. When merged with the large storage required to work with this type of data, the process gets costly. And the rising costs reduce point cloud data usage profitability.

    User Interface

    As you already know you need to deal with 3D instead of 2D, so you need a more comprehensive user interface management system. And achieving this task is challenging, especially for the annotators who are involved with such data analysis. Though LiDAR has its limitations, still it is one of the popular sensing technologies that provide more accurate information.

    LiDAR system is a powerful scanning tool that gathers data with a tremendous degree of detail. Point cloud processing applications have boundless possibilities — from simple data distribution to simplifying complicated and labor-intensive tasks. An experienced engineering company using advanced software and tools can help you quickly and accurately perform point cloud data to 3d model conversion of your target object along with its surrounding.