"},{"ID":5781,"user_firstname":"Lee","user_lastname":"Brinton","nickname":"LB","user_nicename":"lbrinton","display_name":"Lee Brinton","user_email":"lbrinton@esri.com","user_url":"https:\/\/www.esri.com\/en-us\/arcgis\/3d-gis\/overview","user_registered":"2018-03-02 00:17:36","user_description":"Lee Brinton is a Product Manager with a proven track record of delivering 3D GIS solutions to various industries. With over 16 years of experience, Lee has supported customers in different 3D roles, including 3D Technical Lead, leading a team of GIS consultants focused on 3D software project delivery and product management. Lee's passion lies in creating innovative solutions and ensuring customer success. Beyond Esri, Lee cherishes building memories with his family, indulging in outdoor activities, and woodworking.","user_avatar":"
"}],"short_description":"Lidar workflows have changed and compressed lidar is built for how data is delivered today.","flexible_content":[{"acf_fc_layout":"content","content":"Lidar workflows have changed, and compressed lidar is built for how data is delivered today.<\/p>\n"},{"acf_fc_layout":"content","content":"
What was once an occasional, high-cost data collection step has become a routine part of how organizations capture and understand the world. Sensors are more accessible, data collection is more frequent, and datasets are larger than ever. As a result,\u00a0<\/span>compressed lidar formats have become a standard for delivery.\u00a0 ArcGIS Pro supports both zLAS and LAZ compression workflows.\u00a0 zLAS is Esri\u2019s optimized compressed lidar format, designed specifically for ArcGIS workflows.<\/span> While Esri has supported zLAZ, as its own version of compressed LAS, for many years now, we know the lidar community relies upon LAZ as a more open solution that is supported across various ecosystems and compression based workflows.\u00a0<\/span><\/p>\n ArcGIS Pro has been evolving alongside these changes, offering new tools and visualization techniques to best gain insight from your point clouds. With ArcGIS Pro 3.6, LAZ compressed lidar is no longer just an ingestion concern; it\u2019s a first-class workflow that supports visualization, analysis, and surface creation directly from compressed data. And with <\/span>ArcGIS Pro 3.7, we have taken another step forward with additional performance improvements for LAZ compressed lidar at scale.<\/span>\u00a0<\/span><\/p>\n"},{"acf_fc_layout":"content","content":" Today, most lidar data is delivered in\u00a0<\/span>LAZ<\/span><\/b>, an open-source, compressed format based on\u00a0the\u00a0<\/span>ASPRS LAS specification<\/span><\/a>. LAZ\u00a0significantly\u00a0reduces file size, often by around 80 percent,\u00a0making it easier to store, transfer, and manage large point cloud collections.<\/span>\u00a0<\/span><\/p>\n Compression is no longer a convenience;\u00a0it\u2019s\u00a0a necessity.<\/span>\u00a0<\/span><\/p>\n Modern lidar programs need to move data quickly, share it broadly, and work with it\u00a0immediately, even\u00a0before a project reaches later stages. That means GIS software must be able to\u00a0<\/span>work directly with compressed data<\/span><\/b>,\u00a0rather than treating\u00a0compression as a temporary state that requires extra steps to\u00a0uncompress.<\/span>\u00a0<\/span><\/p>\n"},{"acf_fc_layout":"content","content":" ArcGIS Pro 3.6 introduced support for LAZ files<\/a> within LAS datasets<\/a>, allowing users to visualize, analyze, and derive products directly from compressed lidar data without first decompressing it to LAS format. This reduces storage requirements and simplifies data management while maintaining access to core lidar workflows. ArcGIS Pro treats LAZ as a first-class lidar format within the LAS dataset framework, providing a consistent experience across LAS, LAZ, and zLAS data sources. <\/span>\u00a0<\/span><\/p>\n While LAS, LAZ, and zLAS are optimized for desktop analysis and data management, I3S Point Cloud Scene Layers are optimized for scalable distribution and visualization. When point cloud data is published as a scene layer, ArcGIS converts the source data into a multi-resolution, streamable structure that efficiently delivers only the level of detail required for the current view. This enables organizations to share massive lidar datasets across the web without requiring users to download or manage the original source files. Point Cloud Scene Layers serve as the primary cloud-scale dissemination format within the ArcGIS platform, complementing LAS datasets for analysis workflows and providing a streamlined way to share large point cloud collections across organizations and with the public.<\/span><\/p>\n"},{"acf_fc_layout":"content","content":" ArcGIS Pro 3.6 laid the foundation for LAZ based lidar workflows. ArcGIS Pro 3.7 builds on that experience with additional performance enhancements focused on how compressed datasets are accessed and processed.<\/span> Overall performance was improved for compressed LAS files ( Although LAZ remains the primary delivery format in the industry, zLAS holds a significant role within the ArcGIS Pro ecosystem.<\/span>\u00a0<\/span><\/p>\n zLAS is Esri\u2019s optimized compressed lidar format, designed specifically for ArcGIS workflows. Like LAZ, it delivers significant size reduction, often around 80 percent compared with LAS, and is tuned for seamless use across ArcGIS tools and environments.\u00a0 Within ArcGIS Pro y<\/span>ou can edit class codes and class flags from a LAS dataset referencing ZLAS files or on individual zLAS files, which is not supported with LAZ files.<\/p>\n Both formats share an important characteristic in ArcGIS Pro: <\/span>They\u00a0remain\u00a0compressed throughout analysis and processing.<\/p>\n You can visualize point clouds, generate surfaces, and run analysis tools without decompressing the data. This compression-preserving approach reduces storage overhead, improves data management efficiency, and makes it practical to work with very large lidar collections, both in geographic extent and in disk space.<\/span>\u00a0<\/span><\/p>\n"},{"acf_fc_layout":"content","content":" Cloud Optimized Point Cloud (COPC) is an open format created for storing and streaming lidar data directly from cloud platforms. Built on the popular LAZ standard, COPC structures point cloud data using a hierarchical spatial index, allowing applications to access only the points relevant to a specific area of interest. This method minimizes data transfer, enhances performance when handling large datasets, and allows for more efficient access to cloud-hosted point clouds. As more organizations handle lidar data in the cloud, COPC is becoming a popular, scalable, and interoperable format for distributing point clouds.<\/span>\u00a0<\/span><\/p>\n ArcGIS Pro supports industry-standard point cloud formats such as LAS, LAZ, and zLAS, as well as point cloud scene layers. Since COPC files are valid LAZ files, they can be included in a LAS datasets and utilized in many current ArcGIS Pro workflows. However, ArcGIS currently treats COPC files as standard LAZ files and does not leverage the embedded COPC spatial hierarchy or cloud-streaming capabilities. As demand for cloud-native lidar workflows grows, Esri continues to evaluate expanded support for emerging formats such as COPC.\u00a0\u00a0<\/span><\/p>\n \u00a0<\/span><\/p>\n"},{"acf_fc_layout":"content","content":" As lidar collection becomes more frequent, organizations want to work with their data sooner, sometimes immediately after acquisition. Compressed delivery formats make this possible, and ArcGIS Pro naturally adopts these workflows and transitions.<\/span>\u00a0<\/span>Whether data comes from airborne lidar, echosounders, mobile mapping systems, or image-based point clouds, ArcGIS Pro lets users bring compressed datasets directly into their projects and start working without additional preprocessing immediately.<\/span>\u00a0<\/span>This keeps GIS workflows aligned with how data is <\/span>collected\u00a0and\u00a0<\/span>delivered\u00a0today.<\/span>\u00a0<\/span><\/p>\n"}],"related_articles":"","show_article_image":false,"card_image":false,"wide_image":false},"yoast_head":"\nWhy compressed lidar matters<\/span><\/span>\u00a0<\/span><\/h2>\n"},{"acf_fc_layout":"content","content":"
Compressed Lidar in ArcGIS Pro 3.6<\/span><\/span>\u00a0<\/span><\/h2>\n"},{"acf_fc_layout":"content","content":"
Compressed Lidar in ArcGIS Pro 3.7<\/span><\/span><\/h2>\n"},{"acf_fc_layout":"content","content":"
.laz<\/code>) during decompression. A spatial index is now created when statistics are calculated.\u00a0\u00a0<\/span>These improvements are designed to make it even more efficient to work with large collections of LAZ files. As lidar datasets continue to grow in size and frequency, these optimizations help ensure performance keeps pace.<\/span>\u00a0<\/span><\/p>\n"},{"acf_fc_layout":"content","content":"LAZ and\u00a0<\/span>zLAS<\/span>: two compressed paths, one workflow<\/span><\/span>\u00a0<\/span><\/h2>\n
<\/h2>\n"},{"acf_fc_layout":"content","content":"
Emerging trends in lidar compression<\/span><\/span> (COPC)<\/span><\/h2>\n"},{"acf_fc_layout":"content","content":"
Designed for modern acquisition workflows<\/span><\/span>\u00a0<\/span><\/h2>\n"},{"acf_fc_layout":"content","content":"