plaknit 0.2.3

Processing Large-Scale PlanetScope Data

🧶 plaknit

Processing Large-Scale PlanetScope Data

Note: plaknit is in active early-stage development. Expect frequent updates, and please share feedback or ideas through the GitHub Issues tab.

PlanetScope Scene (PSS) data are reveared for its quality and distinct ability to balance spatial and temporal resolution in Earth Observation data. While PSS has proven itself a valuable asset in monitoring small-scale areas, the literature has pointed out the shortcomings when creating a single image from individual tiles (Frazier & Hemingway, 2021).

plaknit bundles the workflow I use to operationalize large-area mosaics so you can run the same process locally or in an HPC environment. The goal is to spend time answering big questions, not making a big mess of your data.

• Free software: MIT License
• Documentation: https://dzfinch.github.io/plaknit

Features

• CLI + Python API that scale from local experimentation to HPC batch runs.
• Planning workflow that searches Planet's STAC/Data API, scores scenes, and (optionally) submits Orders API requests for clipped SR bundles.
• GDAL-powered parallel masking of Planet strips with their UDM rasters.
• Tuned Orfeo Toolbox mosaicking pipeline with RAM hints for large jobs.
• Random Forest training + inference utilities for classifying Planet stacks.