/tags/getting-started/ Recent content in Getting-Started on EORST Blog Hugo en-us Mon, 11 May 2026 00:00:00 +0000 /posts/welcome/ Thu, 19 Mar 2026 00:00:00 +0000 /posts/welcome/ <p>Welcome to the EORST blog!</p> <p><a href="https://gitlab.com/jrsrp/sys/eors_workspace">EORST</a> is an open-source Rust library for processing geospatial raster data. Inspired by Python libraries like rasterio and rioxarray, it enables efficient parallel processing of large-scale raster datasets.</p> <blockquote> <p><strong>New to remote sensing?</strong> Start with <a href="/posts/001-introduction-geospatial-rust/">Getting Started with Geospatial Rust</a> for foundational concepts.</p> <p><strong>Want a complete workflow?</strong> See <a href="/posts/002-end-to-end-workflow/">End-to-End Geospatial Processing with EORST</a> for a code-heavy tutorial.</p> <p><strong>Benchmarking eorst vs Python+Dask?</strong> See <a href="/posts/003-benchmark-rust-vs-python-dask/">Rust vs Python+Dask for NDVI: 23× Faster</a> — real numbers with FMask cloud masking and carbon impact analysis.</p> </blockquote>