Satlas vs DATAKU

Satlas is an open geospatial platform from the Allen Institute for AI (Ai2) that uses computer vision models to analyze public Sentinel-2 satellite imagery and produce global, monthly-updated datasets. It lets researchers, environmental scientists, and geospatial analysts explore how the planet is changing through an interactive map covering marine infrastructure, renewable energy infrastructure, and tree cover.

The platform processes freely available satellite images with AI models pre-trained on SatlasPretrain, a remote sensing dataset with over 30 TB of imagery and 302 million labels. Users can compare side-by-side or timelapse views of offshore wind farms, solar installations, deforestation, and other land-use changes dating back to January 2016.

All geospatial data products, model weights, and training labels are freely downloadable under the ODC-BY license. Satlas also includes a super-resolution module that enhances low-resolution Sentinel-2 imagery to produce higher-detail global views, with open-source code available on GitHub.

DATAKU is a data science site that tracks AI benchmarks, API pricing, and model releases, then packages the numbers into free calculators and downloadable datasets. The homepage archives articles on inference costs, funding rounds, and head-to-head model comparisons, while the Tools section hosts eight utilities such as an LLM cost calculator, benchmark decoder, and model graveyard.

Most AI news sites summarize press releases. DATAKU cross-references provider docs, leaderboard scores, and its own pricing tables, which is why the downloadable datasets page lists 48-row pricing histories and 62-row benchmark score tables under CC BY 4.0 licenses.

Data analysts, ML engineers, and buyers use DATAKU when they need cost-per-token math, benchmark context, or CSV exports instead of marketing claims. The About page describes the project as benchmark and pricing tracking run by a former Tokyo data analyst.