toolsrtm.indices

~75 VNIR + ~18 SWIR spectral vegetation indices from a reflectance spectrum. Direct port of ToolsRTM/R/getIndices.R.

Spectral vegetation indices, direct port of ToolsRTM::getIndices.

The R function takes a dataframe with named reflectance columns (R.400, R.670, …) and a regex pattern to find them; the Python port instead takes wavelengths/reflectance arrays directly (the numerically load-bearing part – linear interpolation onto an integer nm grid, then per-index algebra on named wavelengths – is unchanged, only the dataframe-column-parsing convenience layer is dropped, since it doesn’t change any numbers).

A handful of formulas below are reproduced as literally written in the R source, bugs included, rather than “fixed” – see the inline notes at CIgreen and TCARI/OSAVI.1510, and the GnyLi/CI2 overwrite sequences – so results match R exactly for anyone cross-checking against the original package.

toolsrtm.indices.get_indices(wavelengths, reflectance, spectral_domain='VNIR', factor=None)[source]

Common spectral vegetation indices from reflectance spectra.

Direct port of ToolsRTM::getIndices (the reflectance-column parsing via pattern.rfl is replaced by passing wavelengths/ reflectance directly – see module docstring).

Parameters:

  • wavelengths (array_like, shape (nwl,)) – Wavelengths (nm) of the reflectance columns.

  • reflectance (array_like, shape (nwl,) or (nsamples, nwl)) – Reflectance spectra (0-1), one or more rows.

  • spectral_domain ({'VNIR', 'SWIR', 'VNIR-SWIR'}) – ‘VNIR’: indices using 400-850 nm bands. ‘SWIR’: indices using 800-2550 nm bands. ‘VNIR-SWIR’: both.

  • factor (float, optional) – Scaling factor applied to reflectance (e.g. 1/10000 for digital numbers). Default 1 (no scaling).

Returns:

{index_name: numpy.ndarray of shape (nsamples,)}.

Return type:

dict