Point cloud file settings
🕐 Read time: 5 min
Written By Clark Yuan
Last updated 4 days ago
Overview
Every file in Stitch3D has its own set of file settings that controls how the data is colored, displayed, and visualized in the viewer. These settings are global: any change you make affects how that file appears for all users viewing the Project. This is different from personal viewer settings, which are private to your account.
File settings open in the File Information Panel, which extends from the right side of the viewer. This article focuses specifically on point cloud file settings.
ℹ️ Note: File settings are global to the Project. Changes you make are visible to all users — including shared link recipients — the next time they open the viewer.
How to open the File Information Panel
Open a Project and enter the viewer.
Locate the Layers Panel on the left side of the viewer.
Click on a point cloud file name in the Layers Panel.
✅ The File Information Panel opens on the right side of the viewer with all settings for that file.
Point cloud attributes
Point cloud attributes control how your data is colored and visualized in the viewer. Stitch3D supports seven attributes. The available attributes for any given file depend on what data was captured and stored during the original scan or processing workflow.
Color (RGB)
Displays the point cloud using the real-world color values captured by the sensor or camera. RGB colors are automatically assigned by photogrammetry software from input imagery, or captured directly by sensors with integrated cameras.
Controls:
Brightness — slider from min to max. Increase to brighten a dark dataset; decrease to reduce overexposed colors.
Contrast — slider from min to max. Increase to make colors more distinct; decrease for a softer appearance.
ℹ️ Note: RGB data is available on photogrammetry-derived point clouds and LiDAR datasets captured with an integrated RGB camera. It is not available on LiDAR-only scans without a co-registered camera.
Intensity
Displays the point cloud using the intensity of the laser return signal captured by the LiDAR sensor. Each point is colored on a grayscale ramp based on how strongly the laser reflected off the surface. Highly reflective surfaces (metal, road markings, water) appear bright, while absorbent surfaces (vegetation, dark asphalt) appear darker.
Controls:
Intensity range — min/max range slider. Adjust to stretch or compress the grayscale range across your dataset's actual intensity distribution.
Intensity gradient — choose from preset gradient color ramps or create your own.
💡 Tip: Intensity is particularly useful for identifying surface materials and features that are difficult to distinguish in RGB such as ground control points, road markings, utility infrastructure, and metallic objects stand out clearly in intensity view.
ℹ️ Note: Intensity data is only available on LiDAR point clouds. Photogrammetry-derived point clouds do not contain intensity values.
Elevation
Colors the point cloud using an elevation ramp. This makes terrain features, height differences, and topographic relief immediately visible.
Controls:
Elevation range — min/max range slider. The default values are the actual minimum and maximum elevations in your dataset. Adjust to focus the color ramp on a specific elevation band within your data.
Elevation gradient — Choose from preset gradient color ramps or create your own.
💡 Tip: Narrow the elevation range to focus on a specific height band. For example, setting min and max to a narrow range around ground level will highlight subtle terrain variation that is invisible at the full range. This is useful for detecting drainage features, berms, and low relief earthworks.
Classification
Colors each point according to its classification value which are categories assigned to each point during post-processing that describes what type of surface or object it represents. Stitch3D displays all classification classes present in your file.
Common classification classes:
Individual classes can be toggled on or off in the panel to isolate specific features. For example, turning off vegetation to inspect the bare ground surface beneath.
💡 Tip: Turning off all classes except Ground gives you a clean bare-earth terrain surface which are useful for volume calculations, drainage analysis, and comparing against design surfaces.
ℹ️ Note: Classification data requires post-processing after data capture. If your point cloud has not been classified, all points will appear as Unclassified. Classification is performed in software such as LAStools, TerraSolid, or your drone processing platform before upload.
GPS Time
Colors the point cloud based on the GPS timestamp recorded for each point at the moment it was captured by the sensor. Points captured earlier in the flight are colored at one end of the ramp; later captures at the other end.
💡 Tip: GPS Time is particularly useful for diagnosing flight patterns and scan coverage. The color gradient reveals the flight path of the drone, which areas were scanned first and last, and whether any areas were missed or scanned multiple times. It's also useful for troubleshooting strip adjustment issues in corridor surveys.
ℹ️ Note: GPS Time data is only available on LiDAR datasets where timestamps were recorded during capture. It is not available on photogrammetry-derived point clouds.
Scan Angle
Colors each point based on the angle at which the laser pulse was emitted from the sensor at the time of capture. The range slider runs from a negative maximum angle (left side of the scan swath) through 0° (nadir — directly below the sensor) to a positive maximum angle (right side of the scan swath).
Controls:
Scan angle range — min/max range slider spanning the full angular range of your sensor. Adjust to isolate points captured within a specific angle range.
💡 Tip: Points captured at extreme scan angles (far from nadir) are generally less accurate than points captured near nadir. Filtering to a narrow range around 0° isolates the highest-accuracy points in your dataset — useful for generating precise ground models or checking accuracy in critical areas.
Point ID
Colors points based on a user-defined identifier stored in the point cloud file. This attribute is only present if a custom ID field was assigned during processing or export.
ℹ️ Note: Point ID is a dataset-specific attribute. It will only appear in the panel if your point cloud file contains a defined Point ID field. Most standard LAS/LAZ exports do not include this attribute unless explicitly configured in your processing software.
Point size
The Point Size slider controls the display size of individual points in the viewer. It is available regardless of which attribute is active.
💡 Tip: Increase point size when working with a sparse or undersampled point cloud to make the data look more complete in the viewer. Decrease point size on very dense datasets to preserve fine surface detail and edge definition.
Layer Info
At the bottom of the File Information Panel, the Layer Info section displays metadata about the point cloud file:
Attaching reports
You can attach or link an accuracy report or other supporting document directly to a point cloud layer. Once attached, the report is available for download to any user with access to the Project, subject to their permission level.
In the File Information Panel, scroll to the Reports section.
Click Attach report.
Select a PDF or document file from your computer.
💡 Tip: Attaching an accuracy report directly to the point cloud layer — rather than uploading it as a separate file — keeps the documentation tied to the specific dataset it describes. Any user viewing the layer can access the report in context without having to search through the Project's file list.