What Are All These Attributes In My Lidar Data?

Not only can Global Mapper Pro import and export lidar data, this data can be visualized in 2D and 3D viewers by a number of the data attributes. These visualization options allow you to easily explore the data and understand the characteristics of it, but more importantly some of the attributes are used in key analysis processes in Global Mapper Pro. Come along on this journey to learn all about the attributes you may see in your lidar data.

Lidar vs. Point Cloud

The terms lidar and point cloud are often used interchangeably, but they are different. Lidar is a point cloud collected with a specific method. The relationship between these terms is similar to how a square is always a rectangle, but a rectangle isn’t always a square. Lidar is the square and point cloud is the rectangle.

Formerly an acronym for Light Detection And Ranging, lidar data is actively collected with a specialized scanner. The scanner sends out a light pulse that bounces off the earth’s surface or an object, whatever it encounters and returns to the sensor. On return, the equipment measures the pulse and from that information a point is placed in 3D space. Various pieces of information from the pulse return, known as attributes, are stored with the point.

The more general term, point cloud, refers to a collection of points where each point represents part of a surface and/or object. As a collection, this cloud of points provides a model of an area that can be visualized and analyzed. As you may see, lidar is just a point cloud collected using a particular method. Point clouds can also be generated by sampling terrain data, creating points from the vertices of 3D topographic vector features, or via photogrammetry from drone-collected images, like with Global Mapper Pro’s Pixels to Points tool.

For more information see: What’s the Difference Between Lidar and Photogrammetric Point Clouds in Global Mapper?

The Attributes of Lidar

The most common file formats for storing point cloud data are LAS, and the zipped version LAZ. These formats store the 3D position of each point in the cloud, but also contain fields for additional attributes, some of which are specific to lidar data.

Position

The XYZ position of a point return in lidar data will always be present. This is the one essential attribute as it places each point in space. With thousands, millions, or even billions of points placed in 3D space, the scene of the data becomes clear. Position is always considered in the analysis of a point cloud whether classifying, thinning, creating a terrain surface, or any other process. In Global Mapper’s Feature Info tool and Attribute editor the Z value is shown as the Elevation attribute. Elevation is also the default visualization option for lidar data in Global Mapper.

Intensity

The intensity value of a point in a point cloud is the strength of the pulse returned to the sensor. Values for intensity range between 1 and 256 and provide information about the surface that reflected the light pulse. A higher value means more of the light was reflected.

Return Number

When a light pulse is sent out from the lidar scanner, it can have multiple returns to the sensor. This happens in situations where the pulse partially bounces from an object back to the scanner, but part of the laser pulse continues to hit another object or surface. Nor all scanners record multiple returns. The maximum number of returns that can be recorded is five, but with some hardware that could be lower, at a value of two or even one.

Thinking about how multiple returns are recorded, it most often happens in areas where there are overlapping layers of objects or structures, like vegetation. It is very common to see multiple returns where there is vegetation. In areas with a single solid structure, such as a building, or open ground, all points may be only single returns.

Number of Returns

In addition to recording the return number, lidar data records the total number of returns for a given pulse. This value for the number of returns gives some context to the return number value. Combining these two attributes, designations such as single return, first-of-many, last-of-many can be derived.

Scan Direction

As a lidar scanner is flown over an area it oscillates back and forth on the mount in order to capture a wider area of data. Scan direction is a value that notes the direction the scanner is moving when the pulse for that return was emitted. This value can be with one, a positive direction of movement, or zero, a negative direction of movement. In this application positive is left to right movement while negative is the opposite.

Edge of Flight Line

With options for zero or one, shown as N or Y in Global Mapper, this value simply flags the returns that are at the edge of the scan line. This flag allows the flight lines to be identified in a point cloud.

Classification

The numeric classification value in lidar data categorizes the points into what surface or object type they represent. A meaningful value for this attribute is not gathered during the data collection process, but added in post processing. Raw lidar that has just been collected will have a classification value of zero for all points. This corresponds to Collected, Never Classified.

When lidar data is loaded into Global Mapper, existing classifications can be viewed and explored with visualization options and statistics found in the layer metadata. Classifications can then be corrected or applied to the lidar data with the Automatic Point Cloud Analysis tool in Global Mapper Pro. Classifications can also be applied with manual selection and editing in Global Mapper.

Scan Angle

The scan angle is a degree value describing the angle from the aircraft the pulse was emitted. Values for scan angle are rounded to the nearest integer with zero being nadir to the aircraft and sensor, positive values being to the right in respect to the direction of travel, and negative values to the left.

GPS Time

This value is recorded from the onboard GPS system at the moment the pulse was emitted from the sensor. Depending on the Global Encoding value in the layer metadata, GPS time is stored in reference to the beginning of the GPS week or the GPS epoch, midnight on January 6, 1980.

Point Source ID

The point source identifier groups consistent data together. This could be a group of returns from a single flight line, or an overall flight route. In datasets covering large areas that are created by the combination of multiple flights or data collection episodes, point source ID shows the areas of data that were collected together. This can be helpful in determining sources of error that may need to be corrected for certain sections of data.

More Attributes of Lidar — Calculated or Applied

Density

The density of a point cloud is shown as the number of samples per square meter. For each point this value is calculated for the local area around the point and shown as an attribute in Global Mapper. An average point density for the layer of data can be found in the layer metadata accessible from the Control Center in Global Mapper.

These density values in Global Mapper are dynamic. This means that as the point cloud is edited and points are removed, by filtering out noise or other classifications, the density values will change to reflect the displayed points.

Height Above Ground

Calculated on the fly in Global Mapper, height above ground is a relative elevation value to the approximate ground surface represented in the point cloud. This calculation of height above ground is done when the Height Above Ground option is selected for visualization of the point cloud. If ground is classified when this option is selected the ground points are used as a reference for the ground surface, if classified ground points are not present, the lowest local elevation points are used as the ground reference.

Color (RGB)

Color values, usually true color stored as RGB (red, green, blue) values, are applied after the lidar data is collected. In some situations, colors are applied to points from imagery collected at the same time as the lidar scan. If no color values are present for a lidar dataset they can be added with the Apply Color option in Global Mapper Pro. This tool samples the color value from a loaded image and applies it to each return in a point cloud.

If you have ever used Global Mapper’s Pixels to Points tool to generate a point cloud you will see that RGB values appear by default. This is because the point cloud generated from that tool is photogrammetrically derived, so the source data contains the color values from the drone-collected images. Remember, a photogrammetrically derived point cloud is not true lidar data. They both have benefits and drawbacks, but it is good to keep in mind that not all the attributes discussed in this article apply to photogrammetrically derived point clouds.

Many of the attributes discussed in this article can be explored visually in Global Mapper Pro. Using the Color by dropdown in the primary lidar toolbar many different options for drawing the point cloud in the main 2D view, 3D view, and Path Profile view are available. All these visualization options, combined with exploring the layer metadata and using the Feature Info tool and Attribute Editor.

To explore the attributes and characteristics of your point cloud datasets in Global Mapper Pro, download a 14-day free trial today! If you have any questions, please contact us.