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Package Architecture

This page describes how cross-sensor-cal is organized internally. Understanding this structure helps contributors extend the pipeline or integrate new sensors.

High-level design

The package is built around a stage-based pipeline. Each stage:

  • consumes well-defined inputs
  • writes ENVI/Parquet outputs
  • logs metadata to JSON sidecar files
  • is restart-safe

Stages are orchestrated by the main CLI driver.

Directory structure (Python package)

cross_sensor_cal/ pipeline/ download.py export_envi.py topo.py brdf.py convolution.py parquet.py qa.py utils/ data/ srf/ regression/

Pipeline modules

download.py

Fetches NEON HDF5 tiles.

export_envi.py

Extracts directional reflectance and writes ENVI + metadata.

topo.py

Applies DEM-based topographic correction.

brdf.py

Computes BRDF coefficients and corrects reflectance.

convolution.py

Performs sensor bandpass integration.

parquet.py

Extracts pixel-level data and merges tables.

qa.py

Generates PNG, PDF, and JSON QA outputs.

Data assets

Stored under cross_sensor_cal/data/:

  • spectral response functions (SRFs)
  • MicaSense → Landsat regression tables
  • wavelength lookup and metadata reference files

Adding a new sensor

  1. Add SRF tables under data/srf/
  2. Update convolution stage mappings
  3. Add tests and metadata checks
  4. Document the new sensor in tutorials and reference pages

Next steps