Efficient Cloud-Native Raster Data Access: An Alternative to Rasterio/GDAL
The exponential growth of Earth observation data in cloud storage necessitates efficient access and analysis of satellite imagery. This article introduces an alternative cloud-native raster data access approach to Rasterio/GDAL. Traditional GeoTIFFs are inefficient, while Cloud-Optimized GeoTIFFs (COGs) improve efficiency through tiling and multi-resolution access. However, even with COGs, tasks like time-series NDVI analysis suffer from latency. The authors leverage STAC GeoParquet, combined with pre-calculated byte ranges, to reduce HTTP requests, significantly speeding up data access. Initial tests show this approach drastically reduces time-to-first-tile for Sentinel-2 data and lowers costs. A future open-source library, "Rasteret," will implement these techniques.
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