Runnable notebook vignettes

These are real Jupyter .ipynb files tracked in the SpectralBridge repository. Each link opens the notebook in GitHub's repository viewer so you can read its Markdown and code cells on the web. GitHub does not execute the cells; clone or download the notebook when you are ready to run it locally.

The notebooks mirror the learning modules and call existing SpectralBridge functions. They contain configuration cells, explanations of inputs and outputs, and validation checkpoints. Copy a notebook into your own analysis directory before changing scientific assumptions.

Their code and narrative follow the two active research notebooks at the repository root: Raster_processing.ipynb and Drone_processing.ipynb. The full-pipeline vignettes use the same public orchestrators, while the focused vignettes expose one stage at a time. Output checks use the same practical patterns—printed result summaries, file inventories, DuckDB or pandas table previews, and ENVI/QA plots—but omit machine-specific transfer commands and saved outputs so the files remain portable.

Order	Notebook	Use it when
00	Full NEON pipeline	You want download through QA in one restart-safe call
01	Acquire NEON HDF5	You only want to obtain or reuse the source HDF5
02	Correct NEON reflectance	You want raw ENVI plus standard topo/BRDF outputs
03	Harmonize to Landsat	You already have corrected hyperspectral ENVI and want target-sensor products
04	Build and inspect analysis tables	You want Parquet/CSV inspection and output checks
05	Review QA and validation	You want to render QA and inspect machine-readable diagnostics
06	Process drone imagery	You have local drone HDF5 inputs
07	Extract polygon spectra	You want polygon-indexed spectra from a completed flightline
08	Insert a custom correction	You are developing a reviewed correction after topo/BRDF and before convolution

Opening them

From a clone:

python -m pip install -e ".[notebooks]"
jupyter lab docs/vignettes/notebooks/

The notebooks use repository-relative paths and begin with an editable configuration cell. Large runs can take substantial memory and storage. Start with one flightline, engine="thread", and max_workers=1.

What “runnable” means

The notebooks have valid kernels, importable code, and no saved outputs. Data processing cells are guarded by RUN = False so opening or running all cells does not unexpectedly download tens of gigabytes. Set RUN = True only after editing the paths and identifiers in the configuration cell.