The LAS dataset provides immediate access to lidar data and surface constraints without the need for data conversion or importing in ArcGIS Pro. LAS datasets allow you to reference multiple LAS files as one logical dataset. This is useful because the data for a project is often a tiled collection of files. There isn't a fixed limit to the size or number of LAS or ZLAS files that are referenced by a LAS dataset. This doesn't mean they’re infinitely scalable though. Rather, they’re intended to be used for projects.
Even though you can work with LAS data directly in ArcGIS Pro, there are factors that need to be considered to optimize the performance of a LAS dataset.
The following will help you create an optimized performance environment for your LAS dataset:
- Reference data on a local solid state drive
- Use a projected coordinate system
- Use orthometric height
- Tile LAS points
- Thin LAS points
- Rearrange LAS points
- Calculate LAS dataset statistics
- Build LAS dataset pyramids
- Display in views that have the same projection as the data
- Square rendering of points
Reference data on a local solid state drive
For best performance, the client machine should have direct access to data on a local internal drive, not across a network or slower external drives.
Use a projected coordinate system
It is recommended that LAS data be delivered and consumed in a projected coordinate system, for example, UTM or NAD83 State Plane. LAS data that is captured in geographic coordinates can be displayed but requires on-the-fly projection, which is too slow. Additionally, some forms of analysis require the data to be projected.
It is recommended that you add an accompanying projection file (.prj) file along with a LAS file referenced by the LAS dataset if no spatial reference is present or if the LAS file has an incorrect spatial reference. It is important for subsequent analysis and visualization in ArcGIS Pro if the spatial reference information is known for each LAS file. The Create LAS Dataset geoprocessing tool or the Extract LAS geoprocessing tool both can add the .prj file to accompany a LAS file.
Use orthometric height
Use orthometric heights, not ellipsoidal heights. While lidar is often collected using ellipsoidal height, the data should be modified by the provider to use orthometric height since that is what's typically used in GIS applications.
Tile LAS points
Working directly on a very large LAS file is not recommended. Data in separate files that overlap in XY extent, such as swath-based aerial lidar, should be flattened or merged through tiling. ArcGIS Pro includes the Tile LAS geoprocessing tool that will tile the data referenced by a LAS dataset into manageable sizes. Subdividing large LAS files that exceed 500 MB will improve the performance of any operation that relies on reading the data in spatial clusters for analysis or data visualization operations.
Thin LAS points
Oftentimes, lidar data is oversampled in certain areas—for example, if you are working with lidar data from a vehicle scanner where the data will be oversampled in locations where the vehicle has stopped for a period of time. ArcGIS Pro includes the Thin LAS geoprocessing tool to reduce unnecessary oversampled areas. This will increase overall performance of a LAS dataset.
Rearrange LAS points
Rearranging LAS points adjusts the order of point records in a LAS file and creates a spatial index for those points. This will improve performance. The effectiveness of spatial indexing is dependent on several factors, including file size, data location (local drive or network), and the spatial distribution of points in a .las file. The more random the point distribution, the less effective the spatial index. Generally, if the points in a file are sorted so that those that are close to one another in physical record order are also close in spatial proximity, the index works more efficiently. The Rearrange points parameter for the Extract LAS tool performs this sorting. The tool creates .las files with this sorting completed.
Calculate LAS dataset statistics
A number of LAS-related geoprocessing tools allow you to calculate statistics. This creates a spatial index per file, along with simple statistics that include, among other things, what classes are present and the number of points per class. The spatial index and statistics are placed in an auxiliary file that is named using the same prefix as the LAS file along with the extension *.lasx. The spatial index improves the overall performance of a LAS dataset. See LAS dataset statistics for more information about understanding LAS dataset statistics in ArcGIS Pro.
Build LAS dataset pyramids
A LAS dataset pyramid is used to improve both 2D and 3D display performance and quality for a LAS dataset in ArcGIS Pro. It does this by organizing and indexing the points in a way that optimizes 3D display queries. You can use the Build LAS Dataset Pyramid geoprocessing tool to build a pyramid for your LAS dataset. You cannot build a pyramid on individual LAS files. When a pyramid is built for a LAS dataset, a folder of files is created in the same folder where the LAS dataset is stored. The naming convention for the pyramid folder is the .lasd name plus the suffix .slas.
Display in views that have the same projection as the data
Display in map or local scene views set to the same projection as the data to avoid on-the-fly projection.
Square rendering of points
You can switch the shape in which points from a point cloud are being rendered from circles to squares to improve overall performance in a 3D scene. Depending on the capabilities of your computer and graphics card, the default shape of circles can be slower to render when large amounts of point cloud data are being loaded into your scene. Consider switching to squares to render the point cloud faster.