What is the Difference Between LiDAR and Point Cloud?

Introduction

In the world of 3D scanning, LiDAR and point clouds are often mentioned together—but they are distinct concepts. Understanding the difference between LiDAR and point clouds is crucial for professionals in industries like construction, surveying, and architecture. This post explains how these technologies work and how they complement each other.

What is LiDAR?

LiDAR (Light Detection and Ranging) is a remote sensing technology that uses laser light to measure distances to objects within range. LiDAR is typically used for documenting existing conditions, surveying, mapping, and analyzing topography, as it captures millions of data points to generate precise, accurate results.  The data collected by LiDAR scanners can then be used to create highly detailed 3D models of those physical environments.

What is a Point Cloud?

A point cloud is the result of the data captured by a LiDAR scanner. Essentially, it's a 3D collection of points that represents the surface of objects, buildings, or landscapes. These points are organized in a way that forms a digital model that can be visualized and used for further analysis.  Point clouds can also be created using software applications with data captured by other technologies such as photogrammetry, which we will cover in a future post.

Key Differences Between LiDAR and Point Clouds

1. Functionality vs. Output

• LiDAR is the technology used to gather spatial data, while a point cloud is the data output produced by LiDAR technology.

• LiDAR sensors scan the environment to collect data, which is then processed into a point cloud file.

2. Data Characteristics

• LiDAR collects raw measurements and attributes, like distance and intensity. A point cloud takes these measurements and converts them into a 3D point model, often including additional data such as color and elevation.

3. Applications in Industries

• LiDAR is used for data collection, while point clouds are used in design, analysis, and modeling. For example, LiDAR is used to capture data for land surveying or building documentation, and point clouds are used in 3D modeling of the terrain or architecture.

Conclusion

While LiDAR and point clouds are intrinsically linked, understanding their terms helps bring clarity to communication and an understanding of the roles for each technology. LiDAR is a powerful data collection tool, while point clouds turn that raw data into detailed, actionable insights for professionals across various industries.