Stitch3D

Have you ever searched for something, couldn't find it and only when you stop searching is when you found it? Because that is exactly what happened to me. I struggled, and then others came to help, whether they knew it or not. Since I got into the LiDAR and reality capture world 4 years ago, I have been looking for a simple way to show the point cloud data to our clients. Most LiDAR manufacturers have their own propitiatory software that makes it difficult to view the data unless you download their software. Even if you are able to download it, the interface is complex and not user friendly for those who are not using it every day. I gave up searching in August of 2025 and then in October of 2025, there it was, Stitch3D. If it wasn't for Dylan G. for posting a video about how unbelievable this cloud-based viewer was, I would have lost 5 months of being able to use this platform. Brian Cass mentioned that he met Clark Yuan at Reality Capture Network's conference R-CON and I couldn't send a LinkedIn invite fast enough. Clark and his team have truly made an incredible product that the industry really needed. It has been a game-changer for us to be able to share, view, and download our point clouds and orthomosaic images with our clients. The easy-to-use interface makes it straightforward for anyone to use regardless of their experience level. I have sent numerous feature requests which they have been extremely open to receiving in order to help build their platform based on the needs of the users. If I didn't have a network of industry professionals on LinkedIn and now through Reality Capture Network, I would be struggling for no reason. The ones that share knowledge and insight are the ones you want to stick by. Even if you offer basically the same service, if you treat them like competition, then that is all they will ever be to you. If you treat them like a colleague and a resource, then together, everyone will grow and learn from one another and pass that on to the next person who is struggling to find the answer. If you are like me and struggled to find a way to show your point cloud and raster image data with your clients and haven't tried Stitch3D, I strongly encourage you to do so. If I can help one person, I will call that a win. Mitchell Goldberg DronePoint, LLC Professional Drafting Service Pilotbyte

It was on my to-do list to try out maplibre-gl-lidar after its launch. This npm package allows you to visualize large-scale LiDAR point clouds directly in the browser using MapLibre GL JS. I had been postponing it for weeks, assuming the setup would take hours, if not a full day. Turns out, it took 2 minutes. I was genuinely impressed by how quick the entire setup was. No complex pipeline. No preprocessing headaches. Just plug, load, and render. It was so quick that I immediately ran a comparison against our Stitch3D viewer to understand the tradeoffs. For the test, I loaded a 7.44 GB COPC file in both viewers from Stitch3D’s CloudFront. A few observations around the MapLibre viewer: • I didn’t run a formal performance benchmark, but it felt lightweight. The tiles loaded incrementally and progressively. • It took me some time to get used to the mouse controls. Left click pans and right click rotates, following MapLibre’s default navigation pattern. I’m not sure yet how customizable the mouse controls are. • Tile loading appeared to stop at a certain level of detail. It didn’t continue loading deeper nodes of the point cloud. In comparison, Stitch3D continued refining detail at depth. I’ll experiment more to better understand how MapLibre handles deeper LOD rendering. • Overall, it’s a very accessible entry point for WebGIS and browser-based point cloud exploration. It’s exciting to see new momentum in LiDAR visualization on the web. Open-source LiDAR keeps getting better 🚀 Here is link to the open source maplibre-gl-lidar project https://lnkd.in/gK8xaqGS by Dr. Qiusheng Wu. #MapLibre #LiDAR #WebGIS #PointCloud #3DMapping #OpenSource