Pyxccd: An Efficient Python Package for Break-aware Time Series Analysis of Earth Observation Data

Su Ye , Yingchu Hu

Pyxccd is an open-source, cross-platform Python package (installable via PyPI) for break-aware analysis of Earth observation time series, supporting retrospective disturbance mapping and near-real-time (NRT) monitoring. It implements the two CCDC-like algorithms: COLD (the latest version) and S-CCD 2.0 (state-space formulation to enable NRT application). Additionally, S-CCD 2.0 adds an anomaly-break hierarchical decision rule that improves robustness for coarse-resolution products and can output latent states for interpretable decomposition. A hybrid C/Python architecture provides high performance with a user-friendly API, plus pixel- and tile-based workflows and utilities for large-area orchestration. On 6,488 independently interpreted Landsat disturbance plots, COLD and S-CCD 2.0 achieve comparable accuracy (maximum F1=0.664 vs 0.653). S-CCD 2.0 is 1.4–1.9× faster for retrospective processing and 3–6× faster for NRT updating, with increasing gains as band numbers grow. Overall, pyxccd lowers the barrier to reproducible, efficient, and operational continuous change detection from Earth observation time series.