Add NDSI, NDBI, BAI, MSAVI2, and OSAVI spectral indices#1044
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brendancol merged 5 commits intomasterfrom Mar 21, 2026
Merged
Add NDSI, NDBI, BAI, MSAVI2, and OSAVI spectral indices#1044brendancol merged 5 commits intomasterfrom
brendancol merged 5 commits intomasterfrom
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Five new indices in xrspatial/multispectral.py with all four backends (numpy, cupy, dask+numpy, dask+cupy): - NDSI: normalized difference snow index (green vs SWIR1) - NDBI: normalized difference built-up index (SWIR1 vs NIR) - BAI: burn area index (spectral distance to charcoal point) - MSAVI2: modified SAVI with self-adjusting soil line - OSAVI: optimized SAVI with fixed L=0.16 NDSI and NDBI reuse existing _normalized_ratio kernels. BAI, MSAVI2, and OSAVI have dedicated kernels.
Tests cover CPU (numpy), Dask+numpy, CuPy, and Dask+CuPy backends for all five indices. Includes uint dtype tests and cross-index consistency checks (NDBI = -NDMI, OSAVI ≈ NDVI for large DN values).
Add BAI, MSAVI2, NDBI, NDSI, OSAVI to multispectral.rst reference docs and README feature matrix (18 indices total, up from 13).
Notebook 35_Spectral_Indices.ipynb with synthetic 5-class scene (snow, urban, burned, vegetation, bare soil) demonstrating all five new spectral indices. Self-contained, no external data.
Keep write-performance benchmark table from master, add 5 new spectral index rows to the Multispectral feature matrix.
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Summary
Five new spectral indices in the multispectral module (13 → 18). All four backends.
Also adds 32 tests (CPU, Dask, GPU backends plus uint dtype and cross-index consistency checks), API reference docs, README feature matrix entries,
__init__.pyexports, and a user guide notebook with synthetic data.Closes #1037
Test plan