plaknit 0.0.2

Processing Large-Scale PlanetScope Data

plaknit

Processing Large-Scale PlanetScope Data

• Planet data is phenomenal for tracking change, but the current acquisition strategy sprays dozens of narrow strips across a scene. Without careful masking and mosaicking, even "cloud free" searches still include haze, seams, and nodata gaps.

• PlanetScope scenes are also huge. Building clean, analysis-ready products requires an automated workflow that can run on laptops or HPC clusters where GDAL, rasterio, and Orfeo Toolbox are already available.

• plaknit packages the masking + mosaicking flow I rely on for regional mapping so the Planet community can stitch together reliable time series without copying shell scripts from old notebooks.

• Free software: MIT License

• Documentation: https://dzfinch.github.io/plaknit

Features

• GDAL-powered parallel masking of Planet strips with their UDM rasters.
• Tuned Orfeo Toolbox mosaicking pipeline with RAM hints for large jobs.
• CLI + Python API that scale from local experimentation to HPC batch runs.
• Raster analysis helpers (e.g., normalized difference indices) built on rasterio.
• Random Forest training + inference utilities for classifying Planet stacks.