Cloud Optimized Point Clouds
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Point clouds are 3D representations of the world created through photogrammetry or LiDAR scanning. Point clouds typically consist of thousands to millions of points arranged in a 3D coordinate system with the hope that they represent true dimensions of real world objects and landscapes. They are a digital twin of the physical world that allows us the measure and manipulate with software. Point clouds are typically stored in a .las format and can be viewed in many programs such as CloudCompare, QGIS, and ArcGIS.
The Cloud Optimized Point Cloud developed by HOBU is similar in concept to the COG. It is an .laz(lasZip) format with additional point data organized in a clustered octree. This is similar to how a COG uses overviews and tiles. The octree organization allows for http streaming of point cloud data from cloud storage (AWS S3, Google Cloud Storage, Azure Blob Storage, etc.) to a web browser or other applications. Just like a COG, it enables you to stream portions of point cloud and eliminates the need to download large datasets to a local machine for visualization and analysis.
COPC is based on the open source compression file format, *.LAZ, which was developed by Martin Isenburg and is licensed by his company RapidLASso
For technical information on the formats, see the COPC Specification and the LAS Standard.
Here is a drone-based point cloud in the COPC format. It is 686 mb and stored in Cyverse Data Store here. You can view it here using the COPC Viewer.
Here is another COPC example. It is 3DEP lidar data over Prescott, AZ. It is also stored in the Cyverse Data Store here.
