Google has officially launched AlphaEarth Foundations, a PB-scale AI model for integrating satellite data, accompanied by a groundbreaking 64-dimensional Satellite Embedding Dataset. This innovation distills multi-year, multi-satellite observations into a single 10m × 10m pixel, compressing dozens of data sources – including satellite imagery, radar, elevation, and climate data – into unified 64-dimensional "information capsules". This fundamentally redefines geospatial analysis methodologies.
This article contrasts the core technical specifications of Landsat 9 and Sentinel-2, key Earth observation satellites for environmental monitoring.
Landsat 9
While browsing NASA resources, I discovered an intriguing tool called "Your Name In Landsat". This creative application transforms text into satellite imagery mosaics - a perfect diversion as we approach the Mid-Autumn Festival.
Example output: "malagis" spelled with Landsat imagery
Following our previous article 《「GIS Tutorial」Visualizing Global Satellites Online》, many readers inquired about accessing raw satellite data for custom visualizations. After extensive research, we've identified a reliable method to obtain comprehensive satellite orbital data.
Reference visualization from the original platform
Following our previous article 《A WMTS Service for Historical Chinese Maps: How to Load in QGIS》, colleagues inquired about websites for querying global satellite parameters. Coincidentally, I recently discovered such a platform through video recommendations. The website remains operational and is shared here for relevant needs.
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