Processing LiDAR Data at Scale: Lessons from LiDAR Atlas
From re-processing Magellan SAR imagery of Venus on a 30-day Mac Pro run at JPL, to running 4,000-CPU LiDAR pipelines on Kubernetes — the hard-won lessons in data design, indexing, and validation that make geospatial processing work at scale, and why GPUs are the next frontier.