Create and visualize a lidar point cloud

In this tutorial, the City of Copenhagen, Denmark is redeveloping the district of Tuborg Havn, and they want to use a lidar point cloud for modeling the neighborhood in 3D. This will support further urban planning activities. As a remote sensing analyst for the city, you will create and visualize a lidar point cloud dataset with ArcGIS Pro. First, you'll create a LAS dataset from several LAS data files and display it in a 3D scene. Then, you'll examine it, learn about its properties, and style it based on elevation, intensity, and number of returns. This is the first tutorial in the growing series Get started with lidar in ArcGIS Pro.

This tutorial was last tested on January 16, 2026, using ArcGIS Pro 3.6. If you're using a different version of ArcGIS Pro, you may encounter different functionality and results.

Requirements

• ArcGIS Pro Advanced (see options for software access)
• ArcGIS 3D Analyst extension

Create and visualize a lidar point cloud

Learn about lidar point clouds

First, you'll learn about lidar point clouds. Lidar (light detection and ranging) is a remote-sensing technique that uses laser light to densely sample the surface of the earth, producing highly accurate x, y, z point measurements. A set of those points is called a point cloud. Laser pulses emitted from a lidar sensor reflect from objects both on and above the ground surface: vegetation, buildings, bridges, and so on.

A lidar point cloud.

One emitted laser pulse can be reflected back a single time (single return), usually when it hits a solid surface, such as a building roof or the ground. It can also be reflected several times (multiple returns) as it encounters multiple reflection surfaces while traveling toward the ground. For instance, for a tree, the pulse might reflect off several tree leaves and small branches at different heights, and finally the ground. All these returns are represented as points in the point cloud, providing rich and detailed information about the landscape.

(1) Single return on a hard ground surface, (2) multiple returns on a tree's leaves and branches, and finally the ground.

Note:

To learn more about lidar, see What is Lidar data?

Download and open the project

You'll download the project containing all the data needed for the tutorial and open it in ArcGIS Pro.

1. Download the Tuborg_Havn_Neighborhood .zip file.

   The .zip file downloads to your computer.

2. Locate the downloaded Tuborg_Havn_Neighborhood.zip file on your computer.

   Note:

   Most browsers download to your computer's Downloads folder by default.

3. Right-click the Tuborg_Havn_Neighborhood.zip file and extract it to a location you can easily find, such as a folder on your C: drive.

   

4. Open the extracted Tuborg_Havn_Neighborhood folder. Double-click Tuborg_Havn_Neighborhood.aprx to open the project in ArcGIS Pro.

   

5. If prompted, sign in with your ArcGIS account.

   Note:

   If you don't have access to ArcGIS Pro or an ArcGIS organizational account, see options for software access.

   The project opens.

   

   The project contains a 3D-enabled local scene centered on the neighborhood of Tuborg Havn in Copenhagen, Denmark. This is a redeveloped mixed-use neighborhood located on the former industrial site of the Tuborg Breweries. Currently, the scene contains Tuborg_Havn_Ortho_Photo.tif, a 2D aerial photograph of the area, which you'll use as a reference to become familiar with the neighborhood.

   Note:

   In ArcGIS Pro, local scenes are useful to display 2D and 3D datasets that have a limited spatial extent, such as a city, or, in the case of this tutorial, a city neighborhood. The data displayed in a local scene must use a projected coordinate system. Learn more about local scenes and how they are different from global scenes in the Scenes documentation page.

6. Zoom in using the mouse wheel button and drag the scene to pan. Observe the Tuborg Havn neighborhood on the aerial photograph.

   The neighborhood includes various modern buildings, a marina with boats, smaller buildings on the western and northern edges, and an area still in development on the southeast side.

Create a LAS dataset

Next, you'll create a point cloud dataset for this area using lidar data that was provided with the project. Lidar point cloud data is often stored in the LAS file format. In this tutorial, the Tuborg Havn area is spread across two LAS files. You'll gather them into a single LAS dataset.

Note:

It is common to use several LAS files to cover your entire area of interest. A LAS dataset can contain as many LAS files as necessary for your study area.

First, you'll locate the two LAS files.

1. On the ribbon at the top of the window, click the View tab. In the Windows group, click Catalog Pane.

   

   The Catalog pane appears.

2. In the Catalog pane, expand Folders, Tuborg_Havn_Neighborhood, Tuborg_Havn_data, and LAS_data.

   

   PUNKTSKY_1km_6181_724.las and PUNKTSKY_1km_6181_725.las are the two LAS files that cover the Tuborg Havn neighborhood.

   Note:

   These two LAS files come from a project managed by the government of Denmark that produced lidar coverage for the entire country.

   Next, you'll create a LAS dataset.

3. Right-click the LAS_data folder, point to New, and choose LAS Dataset.

   

   A new LAS dataset is added to the LAS_Data folder in the Catalog pane. The name of the dataset is currently in edit mode.

4. In the LAS dataset name box, type Tuborg_Havn and press Enter.

   The extension is automatically added and the name Tuborg_Havn.lasd appears in the list.

   Tuborg_Havn.lasd is a LAS dataset, but for now it is empty. Next, you'll populate it.

5. Right-click Tuborg_Havn.lasd and choose Properties.

   

6. In the LAS Dataset Properties window, click the LAS Files tab. Under Files, click Add Files.

   

7. In the Open window, browse to the Tuborg_Havn_data folder and double-click the LAS_data folder to open it.
8. Press the Shift key and click PUNKTSKY_1km_6181_724.las and PUNKTSKY_1km_6181_725.las to select both of the files. Click Open.

   

   The two files are added to the list. According to the Point Count values, each LAS file has between 3 million and 5 million points. The Point Spacing values show that there is about 0.3 meters between points.

   

9. Click the General tab.

   This tab summarizes the overall information for the new LAS dataset. It indicates that it contains two LAS files, for a total of 8,127,305 LAS points. The Extent values of the data are also mentioned, as well as the horizontal (XY) and vertical (Z) units, which are in meters.

   

10. Click the Statistics tab.

    

    On this tab, under Classification Codes, there would be a list of classification codes that were assigned to the LAS points—such as ground, buildings, low vegetation, high vegetation, and so on. For now, none of the points have received a classification, so the only classification code listed is Unassigned. You'll learn how to classify the points in a later tutorial.

11. Click the Coordinate System tab.

    The projected coordinate system is ETRS 1989 UTM Zone 32N. This is the coordinate system of the original LAS files. It was passed on to the Tuborg_Havn.lasd dataset.

    

    Note:

    Learn more about the information in the LAS Dataset Properties window.

12. Click OK to close the LAS Dataset Properties window.

Display and explore the LAS dataset

Next, you'll add the LAS dataset to the scene and explore it. You'll also build a LAS dataset pyramid to improve the 3D display performance. First, you'll turn off the ortho photo to declutter the scene.

1. In the Contents pane, uncheck the box next to Tuborg_Havn_Ortho_Photo.tif to turn the layer off.

   

2. In the Catalog pane, right-click the Tuborg_Havn.lasd dataset and choose Add To Current Map.

   

3. When prompted to build a LAS dataset pyramid, click Yes.

   

   A LAS dataset pyramid structure is used to improve the 3D display performance of a LAS dataset by creating and displaying the ideal level of detail (LOD) for the scale of the scene.

   Note:

   Learn more about LAS dataset pyramids.

   The Build LAS Dataset Pyramid tool appears. You'll run it.

4. In the Geoprocessing pane, accept the default Build LAS Dataset Pyramid tool parameters and click Run.

   

   The tool takes a few moments to run. Next, you'll turn your attention to the Tuborg_Havn.lasd dataset displayed in the scene.

   

5. In the Contents pane, expand the Tuborg_Havn.lasd layer.

   

   The LAS dataset is symbolized according to the height of the points or elevation. As you can see in the legend, the lowest points are dark purple and the highest points are bright red. Next, you'll explore the point cloud in 3D.

6. In the scene, above the Navigator wheel, click Show full control.

   

   The Navigator wheel expands to include 3D navigation functionality.

7. Use the middle Navigator wheel to tilt and rotate the scene.

   

   Tip:

   Learn more about 3D navigation on the Use the on-screen navigator page.

   You can also press C while dragging the scene to pan, or press V and drag the scene to tilt.

8. Zoom in until you can see the individual LAS points.

   

9. Zoom out until you see the LAS dataset represented as red wireframes.

   

   The wireframes indicate the extent of both files, each one represented as a red box, and the maximum height of the points they contain.

10. Click the taller wireframe box to display the informational pop-up window.

    

    The pop-up summarizes useful information about the LAS file corresponding to the taller wireframe box (PUNKTSKY_1km_6181_724.las); you already saw some of this information in the Properties window earlier.

11. Continue to explore the point cloud dataset. Zoom in and out, tilt, rotate, and pan, and try to recognize buildings, trees, ground, and other elements from the landscape.
12. On the Quick Access Toolbar, click the Save Project button to save the project.

    

    Tip:

    If you get a warning indicating that the project was created with a previous version of ArcGIS Pro, click Yes to proceed.

Symbolize the LAS dataset based on intensity

Next, you'll change the symbology (styling) of your LAS dataset to visualize it in a new way. As you learned earlier, by default, the LAS dataset is symbolized according to the elevation information. You'll symbolize it by intensity.

Intensity is a measure, collected for every point, of the return strength from the laser pulse that generated the point. It is based, in part, on the reflectivity of the object struck by the laser pulse. For instance, vegetation will reflect very little, and in contrast, metal A/C systems on rooftops reflect very strongly.

You'll focus on a portion of the scene that offers a variety of features.

1. On the ribbon, click the Map tab. In the Navigate group, click Bookmarks and choose Buildings and trees.

   

   The scene updates to that specific extent.

2. In the Contents pane, confirm that the Tuborg_Havn.lasd layer is selected.

   

3. On the ribbon, click the LAS Dataset Layer tab. In the Drawing group, click the Symbology down arrow.

   For now, the active symbology is Elevation. You'll switch to Intensity.

4. Click the Intensity button.

   

   The scene updates, showing each cloud point symbolized by its intensity value on a grayscale. The darker areas represent lower intensity, and the lighter areas represent higher intensity.

   

   This way of visualizing a point cloud highlights features with many details and gives a sense of the surface types. For a striking example, look at the round square in the lower right corner, where the intensity rendering shows a wealth of details, including the crosswalk markings.

   

   View of a square with elevation symbology (left) versus intensity symbology (right).

   In fact, you can use intensity visualization to make images that approximate a black-and-white aerial photo. This can be particularly useful in cases when no optical imagery is available. You'll look at the same extent from above (in 2D).

5. On the ribbon, click the Map tab. Click Bookmarks and choose 2D detail.

   

   The scene updates to a 2D view.

   

6. When you are done examining the 2D view, click Bookmarks and choose Buildings and trees to go back to a 3D view.

Symbolize the LAS dataset based on number of returns

You'll explore one more LAS dataset symbolization: by number of returns. As you learned at the beginning of the tutorial, an emitted laser pulse can be reflected back a single time (single return) or several times (multiple returns), based on the type of objects it encounters, and all these returns are represented by points.

(1) Single return on a hard ground surface, (2) multiple returns on a tree's leaves and branches, and finally the ground.

Note:

To learn more about returns, see the Lidar laser returns section in the What is Lidar data? documentation page.

This total number of returns value for each pulse is stored in the LAS dataset in the Number of returns attribute. For instance, a given point in the dataset might be return number 2 out of a total of 5 returns. In that case, value 2 will be stored in the Return number attribute for that point, and value 5 in its Number of returns attribute.

You'll set the symbology to the Number of returns attribute.

1. In the Contents pane, confirm that the Tuborg_Havn.lasd layer is selected.
2. If necessary, on the ribbon, on the LAS Dataset Layer tab, click the Symbology button to display the Symbology pane.

   

3. In the Symbology pane, for Draw using, choose Number of returns.

   

   The scene updates to the new styling.

   

   The blue areas correspond to pulses with a single return. These are usually flat, solid surfaces. The areas with a mix of gray, yellow, orange, and red correspond to pulses with several returns. These are most often trees or bushes. Vertical walls with many glass panes can also show several returns, because the light reflects off the glass surfaces. Edges of buildings or other human-made objects often correspond to two-return pulses (gray), because the pulses may reflect once from the building edge and once from the ground, or from another lower surface.

4. In the Contents pane, review the Number of returns legend for more details.

   

   Note:

   To learn about more symbolization options, see the LAS dataset symbology page.

   To learn more about the attributes available in a LAS dataset, see the Lidar point attributes section in the What is Lidar data? documentation page.

   Another important visualization type is to classify lidar points into several categories, such as ground, buildings, low vegetation, tree, and so on, and to symbolize the point cloud according to these categories. This will be the focus of an upcoming tutorial.

5. Press Ctrl+S to save the project.

In this tutorial, you discovered how to create and visualize point clouds with ArcGIS Pro. You created a LAS dataset from individual LAS files and displayed it in a 3D scene. You then examined it, learned about its properties, and styled it based on elevation, intensity, and number of returns.

You can find more tutorials like this one in the growing Get started with lidar in ArcGIS Pro series.

Acknowledgements

• Tuborg_Havn_Ortho_Photo.tif and the lidar data used in this tutorial come from the Danish government website Styrelsen for Dataforsyning og Effektivisering.
• World Topographic Map sources: Esri, TomTom, Garmin, FAO, NOAA, USGS, OpenStreetMap contributors, and the GIS User Community
• World Hillshade layer sources: Esri, Maxar, Airbus DS, USGS, NGA, NASA, CGIAR, N Robinson, NCEAS, NLS, OS, NMA, Geodatastyrelsen, Rijkswaterstaat, GSA, Geoland, FEMA, Intermap, and the GIS user community