Julia Data Cubes

Overview

Storage and analysis of large geospatial raster data e.g. Satellite imagery
Focus on high throughput computing (HTC) limited by data loading
Array with dimensions e.g. lon, lat, and time, instead of a list of points in vector data
Cloud optimized to access particular slices of the data (e.g. Bounding box or timespans)
Importance of data compression for cloud-optimized workflows
Workflow specific optimization using chunking
Lazy computations on large data and making data cubes AI-ready