InspectionsWhat is a Point Cloud Survey?

If you’re not familiar with the term point cloud, don’t worry, you’re not alone.

A Point Cloud is a collection of data points scanned by a 3D scanner. These points are then combined to create a 3D model of the object or area.

This blog post will show you how to create a point cloud scan of a specific area. We’ll also talk about which software is best for processing cloud points. As well as point cloud uses in industries.

Skykam is Scotland’s leading drone survey service. We have been providing point clouds to businesses of all sizes for years. We’re passionate about helping clients get the most out of this technology.

What is a Point Cloud

A point cloud is a set of data points or coordinates in three dimensions. The points may represent a physical 3D shape or object. Each point position has its set of coordinates (X, Y, Z). Point clouds are created using 3D scanners or photogrammetry software.

A point cloud is a huge collection of tiny individual points plotted in 3D space. It’s made up of points captured using a 3D laser scanner.

Point Cloud Survey

This technology emits laser beams in all directions. The distance between these beams and the object is calculated.

This data is then used to create a 3D model (Digital Twin) of the scanned object or area. A digital twin is a virtual representation of an asset.

Digital twins have many uses. Surveys, design, analysis, and simulations all make use of digital twins.

History Of Point Clouds

Point Cloud Surveys first began as Geographical Information systems (GIS). A Geographic Information System (GIS) is a computer system. That analyzes and displays referenced information. This can include maps, data, and analysis results.

GIS software creates and analyses spatial data. This data can be in the form of points, lines, polygons, or rasters (images).

GIS was used to analyse all kinds of terrains.

GIS was first created in the 1960s as a way to manage and analyze spatial data. Used for mapping and analyzing the terrain.

In the 1990s increased accuracy meant GIS began to be used for other tasks. Beginning to expand from terrain to surveying and accident investigations.

In the 2000s, GIS began to create digital twins of assets.

In the 2010s, GIS would be used for creating 3D models from point clouds. This allowed for even more accurate simulations and analyses.

Creating accurate point cloud data, that could create a three-dimensional map of an object.

How to Create a Point Cloud Scan

To capture a cloud scan you will need to first decide which method is best for you.

There are three types of cloud point scanners:

  • Terrestrial
  • Mobile
  • Drone

Terrestrial Laser Scanner

The most common type of scanner is the terrestrial laser scanner (TLS). TLSs are fixed in one location and have a range of up to several hundred meters. Used for surveying large areas, such as construction sites or forests.

Mobile Scanners

Mobile scanners are handheld devices that can be carried around and used on the move. They have a shorter range than TLSs but are much more versatile.

Mobile scanners are often used for scanning small objects, such as statues or vases. This allows for a more detailed scan of smaller objects. Producing a higher-quality 3D model.

Drone Scanners

Drone point cloud scanners are a new technology that is becoming popular. They are small, unmanned aerial vehicles that use lasers to scan objects from above. This allows for a 360-degree scan of the object. Useful for capturing detail that is not visible from the ground.

Drones scan large areas making them a valuable tool for land surveys and mapping. They are also becoming popular for accident investigation and security purposes.

LiDAR vs Photogrammetry

There are two different methods of creating a point cloud, LiDAR and photogrammetry.

LiDAR (Light Detection and Ranging)

LiDAR technology is like radar, in that it uses pulsed light to measure distances. It creates point clouds of objects and landscapes and is often used in surveying and mapping. LiDAR can penetrate vegetation and tree cover. Capturing data about the shape and structure of the underlying land surface.

 

 

Photogrammetry

Photogrammetry is a technique for creating three-dimensional models from two-dimensional images. It uses photography to calculate the position of points in space. Created from the overlapping images of a scene. Photogrammetry can create point clouds, but it is not as accurate as LiDAR.

LiDAR is the better option for creating a point cloud. LiDAR technology is more accurate than photogrammetry. LiDAR uses pulsed light to measure distances rather than relying on photographs.

LiDAR can penetrate vegetation and tree cover. Capturing data about the shape and structure of the underlying land surface. Whereas photogrammetry cannot.

However, LiDAR is more expensive to use and requires specialist equipment.

How to Create a Point Cloud Scan of a Desired Area

To create a point cloud scan, you need a 3D scanner.

Scan your object with a 3D laser scanner such as a Riegl VZ-400i. This device emits laser beams in all directions, which return points as they hit surfaces.

The software then calculates the distance between these beams and the object they hit.

The scanner can only record data points within the scanner’s line of sight. If you want to capture all the details on an object, you need to move the scanner around it. Create many scans from different viewpoints and angles.

This is necessary for objects with intricate details or curved surfaces. A single scan from one viewpoint may not be able to capture all the details.

Covering every angle, it can create an accurate 3D map of the object.

What Measurements are in a Point Cloud?

Point Cloud Co-ordinates

Each point in the point cloud is located on a three-dimensional coordinate system by its X, Y and Z Value.

Point Position

The x value indicates the position on the horizontal plane. The Y value indicates the position on the vertical plane. The Z value indicates the depth or height of the point.

Point Placement

Each point contains information about the distance it has travelled. Aswell the points position in relation to other points. By measuring the distance between these points, a 3D image of the object or area is created.

Point Colour

Also, each point in a point cloud has an RGB (red, green, blue) colour code of the surface it has hit. This assigns a specific colour to each point in the scan, creating an accurate coloured scan.

Point Brightness

Point clouds can also have an intensity rating. This is the brightness of the laser at the point. This is measured in milliwatts (mW). The brighter the laser, the higher the intensity rating.

photogrammetry

How to Process Point Clouds

When you combine these points you get Point Cloud Data.

Point cloud processing is a means of turning point cloud data into usable 3D models. This is done in many ways, but most software generates a mesh or surface model. Mesh models are used to create 3D printing files, while surface models are better for visualization and analysis.

 

When creating a 3D model from a point cloud, there are a few important things to keep in mind:

– The resolution of the point cloud will affect the quality of the final model. The higher the resolution, the better the quality of the model.

Not all points in the point cloud will be used in the final model. Only those points that lie on the surface of the object or area being scanned will be used.

– The point cloud data will need to be cleaned before it can be used to create a model. This includes removing any points that are not on the surface of the scanned object.

 

Once the point cloud data is cleaned, it can create a mesh or surface model. The data is fed into special software that generates a model. This software has many options to control the quality and appearance of the final model.

After the model has been generated, it can be exported to a variety of different file formats.

Processing point cloud data can be a very resource-intensive task. In order to create a usable 3D model from the data, a powerful computer is needed to visualize them. A high-end graphics card and plenty of RAM are essential for handling large point clouds.

Processing a point cloud involves converting the raw data into a usable format. This can be done in a number of ways, depending on the software used.

Point cloud software

Point cloud software is essential for creating usable outputs from point cloud data. There are many software packages available, each with its own advantages and disadvantages.

Cloud Compare

Cloud Compare is a free and open-source software package that is used for processing point cloud data. It is available for Windows, Mac, and Linux and can be used to create polygon meshes, 3D models, and textured surfaces from point cloud data.

Cloud Compare is a powerful tool that can be used for a variety of purposes, including construction planning, land surveying, and accident investigation. It is easy to use and can process large point clouds quickly and easily

Although Cloud Compare is a powerful tool, it does not have many advanced features. For more advanced processing, you may need to use a different software package.

Meshlab

Meshlab is a great software for working with point clouds. It has a wide range of features and can be used to clean up and process point cloud data, as well as create 3D meshes from them.

However, it can be quite complex to use and can take some time to learn how to get the most out of it. Additionally, it can be quite resource-intensive, so it may not be suitable for everyone.

Gom Inspect

Gom Inspect is a cloud-based software platform that allows users to inspect and analyse point clouds. It has a wide range of features. Including the ability to view, measure, and annotate point clouds. Extract building footprints, walls, and roofs. and generate 2D and 3D drawings from point clouds.

One of the advantages of Gom Inspect is that it is easy to use. The interface is simple and intuitive, and the tutorials are helpful. It also has a wide range of features, which makes it versatile.

How Long Does a Point Cloud Take to Process?

It can take a significant amount of time to process a point cloud, depending on the size and complexity of the data. It all depends on how many scans are needed and what exactly needs scanning.

Point clouds can be huge! They usually contain a few million points, with the largest ones having up to 100 million. As you can imagine, processing all that data is no small feat. In fact, it often takes many hours, or even days, to create a point cloud from scratch.

Point cloud file formats

There are many point cloud file formats due to the number of manufacturers and tools.

There are many point cloud file formats due to the number of manufacturers and tools. Each format has its own advantages and disadvantages. It is important to choose the right format for your needs.

Some of the more common formats include:

.xyz

.ply

.las

.e57

.pts

Point Cloud Uses

Point clouds have a wide range of uses, from construction planning to accident investigation.

Here are some of the most common uses for point clouds:

 

Point Cloud Data

Construction Planning

Point clouds are often used for construction planning. This involves creating 3D models of buildings and other structures from the point cloud data. This can be used to plan construction projects, assess the condition of a structure, and more.

Additionally, point clouds can be used to create 2D drawings of buildings and other structures. This can be helpful for planning purposes or for creating documentation of a structure.

Point clouds can be used to create 2D and 3D drawings that can be used by architects and engineers. This allows them to see a realistic representation of the object that they are planning to build.

Additionally, point clouds can be used to measure distances and angles, which is useful for ensuring that objects are correctly aligned.

Accident Investigation

Point clouds are often used in accident investigations. This involves creating a point cloud of the accident scene and analyzing it to determine what happened.

This can be used to reconstruct the accident scene, identify potential causes, and more. Point clouds can also be used to identify skid marks and other damage to the vehicles involved in the accident.

Overall, point clouds provide a comprehensive view of the accident scene that can help investigators determine what happened. By creating a point cloud of the scene and analyzing it, investigators can reconstruct the accident and identify potential causes. Additionally, point clouds can be used to identify skid marks and other damage to the vehicles involved in the accident.

Land surveying

Land surveying can benefit the use of point clouds. This entails creating a point cloud of the land that can be used to measure distances, angles, and other parameters. Point clouds can also be used to create contour maps of the land.

This is useful for land planning and assessing the condition of the land. Furthermore, point clouds can generate digital terrain models (DTMs). DTM’s are useful for project planning.

Point clouds can also be used to generate three-dimensional (DTM) land models. These models can be used to plan construction projects or to assess the land’s condition.

Construction planning

For construction planning, point clouds are frequently used. This entails using point cloud data to create models of buildings and other structures. Point clouds can also be used to create drawings of buildings and other structures. This can be useful for structure documentation or for planning purposes.

Point clouds can measure distances and angles. Ensuring that objects are aligned. Architects and engineers can see a realistic representation of the object. Prototyping the building by using point clouds.

3D modelling and printing

Three-dimensional printing can be done with point clouds. Creating a point cloud of an object. Then using it to create a three-dimensional model of the object is what this entails. This can be useful for creating object models or for prototyping.

Architects and engineers can see a realistic representation of the object they are planning to build by using point clouds. Point clouds are used to calculate distances and angles. This is helpful in ensuring that objects are properly aligned. Point clouds can also be used to create contour maps of the land.

BIM Models

Point clouds can be used to create Building Information Models (BIM models). This involves creating a point cloud to create a 3D model of the building.

This can be helpful for planning construction projects or for assessing the condition of the building. Additionally, BIM models can be used to create drawings of buildings and other structures.

As you can see, point clouds have many uses. They are often used in accident investigations, construction planning, land surveying, and more. Point clouds provide a comprehensive view of an object or scene and can be very helpful in various applications.

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Skykam is Scotland’s leading drone survey service. We have been providing point clouds to businesses of all sizes for years. We’re passionate about helping clients get the most out of this technology.

Our mission is to make aerial surveying more accessible and affordable for everyone. Our vision is to be the go-to source for reliable, accurate, and cost-effective drone surveys in Scotland.

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