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LiDAR Data Compression Explained: Reduce File Size Without Losing Quality

  • Writer: Anvita Shrivastava
    Anvita Shrivastava
  • 3 days ago
  • 4 min read

Updated: 1 hour ago

LiDAR (Light Detection and Ranging) technology is widely utilized through very different industries, including geospatial mapping, forestry, urban planning, and autonomy. As LiDAR sensors have improved in accuracy and sophistication over time, they have produced increasingly large quantities of data—single LiDAR projects can generate multiple terabytes of data.


Effectively managing, storing, and sharing the enormous volume of data present in a LiDAR project can be very challenging. That’s where LiDAR data compression comes into play.


LiDAR Data Compression
LiDAR Data Compression

What Causes LiDAR Data to Be So Large


A typical LiDAR dataset contains millions, and in some cases, billions of points. Each point will generally contain the following attributes:


  • X, Y, & Z Coordinate

  • Intensity Value (i.e., strength of return signal)

  • Return Number

  • Classification Information (i.e., "ground," "building," "tree," etc.)

  • RGB Color (in some cases)


Raw LiDAR data (i.e., LAS files) tend to be very large due to the amount of information contained within them.


For example, a 100 sq. km. survey will commonly generate raw LiDAR files that contain approximately 50-500 GB of data.


What Is LiDAR Compression?


LiDAR compression reduces file size while preserving as much of the original information as possible. There are two main types:



  • No data is lost

  • Original data can be perfectly reconstructed.

  • Ideal for archival and analysis



  • Some data is simplified or removed.

  • Much higher compression ratios

  • Suitable for visualization and web delivery


The key is choosing the right balance between file size and fidelity.


LiDAR Data Compression Explained: Reduce File Size Without Losing Quality


Benefits of Compressing LiDAR Data


  • Reduced storage costs

  • Faster data transfer and sharing

  • Improved performance in GIS and visualization tools

  • Better scalability for cloud workflows


Popular LiDAR Compression Formats


Below are the most widely used LiDAR formats, including both open standards and advanced proprietary solutions.


  1. Multi-resolution Seamless Image Database - MrSID


Best To Use: Visualization With High Throughput & Workflows That Can Be Scaled


MrSID is a very high-quality compression format that was created to accommodate the growing size of large geospatial data, which includes LiDAR data.


Key Features:


  • Very High Compression Ratio With Minimal Loss In Quality

  • Supports Fast Zooming And Panning With A Multi-Resolution Architecture

  • Designed To Be Efficient For Both Streaming And Cloud Based Delivery

  • Designed To Allow For The Effective Visualization Of Huge Data Sets


Why Use MrSID For Storing And Streaming LiDAR Data?


MrSID Allows Users To Efficiently Store And Stream Massive Point Cloud Data Making It The Optimal Format For Enterprise Level Geospatial Applications


  1. Compressed LAS (LAZ)


Best To Use: Lossless Compression And Interoperability


LAZ Format (LAZ) Is A Compressed Version Of The LAS Format That Is Widely Used In The Geospatial Community.


Key Features:


  • Compression With No Data Loss (Lossless)

  • Typically Reduces The Size Of Files By 70–90 Percent

  • Open Format That Attracts Many Development Community Tools


Limitations:


  • Not Designed For Streaming Very Large Data Sets

  • Accessing Compressed Data Is Slower Than Multi-Resolution Formats


  1. Entwine Point Tile (EPT)


Best To Use: Cloud-Based and Web-Based Workflow


EPT (Entwine Point Tile) Provides Access To LiDAR Data Organized In A Multi-Level Hierarchical Way That Increases Access Speed.


Key Features:


  • Designed For Storage In The Cloud (AWS & Azure)

  • Supports Streaming Data And Loading Only Portions

  • Compatible With Many Web Visualization Tools


  1. COPC (Cloud Optimized Point Cloud)


When to use it: When you need to get data from the cloud easily, but use the LAS format to do this.


The COPC format is a new way of representing a point cloud that uses a combination of LAS/LAZ data in a method that makes it possible to optimize for use in the cloud.


Key Features:


  • Spatial indexing to allow for quick searches

  • Compatible with all existing LAS/LAZ workflows

  • Optimized for range request via HTTP


  1. Draco (developed by Google)


When to use it: When you need to visualize data in a web application or use 3D files in web/mobile applications


Draco is a way to compress and create 3D models/geometry, including point clouds.


Key Features:


  • Very high compression ratios

  • Ideal for displaying 3D data in a browser

  • Commonly used with 3D tiles and mobile/web applications.


Limitations:


  • Not recommended for analytical workflows

  • May result in loss of geometry data


Best Practices for LiDAR Compression


To decrease the amount of storage space taken up by your files while still keeping them high-quality, follow these best practices:


  1. Select the Best Compression Format


  • Use LAZ for archival and accuracy (because it's a lossless format).

  • Use MrSID (Multi-Resolution Seamless Image Database) for visualization and enterprise delivery.

  • Use EPT (Entwine Point Tile) and COPC (Cloud Optimized Point Cloud) for workflows based in the cloud.


  1. Optimize Point Density


  • Remove redundant and unnecessary points from the point cloud dataset.

  • Use thinning techniques when appropriate.


  1. Leverage Tiling and Indexing


  • Break larger datasets into smaller tiles to make them easier to work with.

  • Improve the speed of access and performance of the compressed data.


  1. Use Multi-Resolution Formats


  • Enable fast zooming by using multi-resolution formats.

  • Enable progressive loading of the data as it is displayed.

  • Multi-resolution formats are critical for web and mobile applications.


  1. Validate Quality of Your Data


  • Always verify the accuracy of the data after compression and before use.

  • Ensure all classifications and metadata stay the same.


When to Use MrSID for LiDAR


You should consider MrSID when:


  • Streaming large amounts of LiDAR data is the desired workflow.

  • Want to use interactive visualization as part of your workflow.

  • Want to drastically reduce the size (costs) of storing large sets of LiDAR data.

  • Plan to deploy enterprise-level geospatial solutions and systems.


LiDAR data compression is no longer optional—it’s essential for managing modern geospatial workflows. By choosing the right format, you can dramatically reduce file size while preserving the accuracy and usability of your data.


While formats like LAZ and COPC are excellent for lossless storage and cloud access, MrSID stands out for its ability to deliver high-performance visualization and scalable data access.


If your goal is to balance compression, speed, and usability, combining multiple formats—especially with MrSID—can provide the most efficient and flexible solution.


For more information or any questions regarding the LizardTech suite of products, please don't hesitate to contact us at:



USA (HQ): (720) 702–4849


(A GeoWGS84 Corp Company)

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