enhanced_vegetation_index¶

Enhanced Vegetation Index (EVI)¶

enhanced_vegetation_index computes the MODIS-style Enhanced Vegetation Index providing improved sensitivity in high biomass regions and partial resistance to atmospheric and soil background effects.

Formula¶

\[\mathrm{EVI} = G \cdot \frac{NIR - Red}{NIR + C_1 \cdot Red - C_2 \cdot Blue + L}\]

Default constants (MODIS convention): - \(G = 2.5\) - \(C_1 = 6.0\) - \(C_2 = 7.5\) - \(L = 1.0\)

Parameters¶

See autodoc for the full signature. Core arguments:

nir : Near-infrared reflectance array
red : Red reflectance array
blue : Blue reflectance array
G : Gain factor (default 2.5)
C1 : Atmospheric resistance coefficient for red band (default 6.0)
C2 : Atmospheric resistance coefficient for blue band (default 7.5)
L : Canopy background adjustment (default 1.0)

All three band arrays must have identical shape. Any numeric dtype is accepted; values are coerced to float64 internally for stable arithmetic.

Dimensional Support¶

Documented public contract: 1D and 2D arrays - 1D: (pixels,) - 2D: (rows, cols)

Higher ranks (e.g. (time, y, x) or (time, band, y, x)) may work via internal generalized kernels but are not formally guaranteed; future versions may expand documented support.

Numerical Stability¶

A near-zero safeguard (epsilon ~1e-10) is applied to the denominator (NIR + C1*Red - C2*Blue + L). Elements where |denominator| < epsilon yield 0.0 to avoid extreme magnitudes.

Usage¶

import numpy as np
from eo_processor import enhanced_vegetation_index

nir  = np.array([0.60, 0.70, 0.65])
red  = np.array([0.30, 0.25, 0.28])
blue = np.array([0.10, 0.05, 0.07])

evi_vals = enhanced_vegetation_index(nir, red, blue)
print(evi_vals)

Custom constants (e.g., tuning for sensor-specific calibration):

evi_custom = enhanced_vegetation_index(nir, red, blue, G=2.4, C1=5.5, C2=7.0, L=1.0)

Alias¶

evi is provided as a direct alias of enhanced_vegetation_index for convenience and parity with common remote sensing nomenclature.

Performance Notes¶

Rust implementation: - Single fused loop (no intermediate temporary arrays) - GIL released during computation - Conditional parallelism on large arrays (multi-core speedup) - Early shape validation produces clear ValueError on mismatch

Interpretation (Typical)¶

Higher EVI values indicate vigorous, healthy vegetation. Compared to NDVI, EVI reduces saturation in dense canopy areas and mitigates some atmospheric / soil background effects through the added coefficients and blue band term.

Error Handling¶

Shape mismatch raises ValueError
Unsupported dimensionality raises TypeError
Negative or non-physical constant values (if validated in future) will raise appropriate errors

Autodoc¶

enhanced_vegetation_index(nir, red, blue)[source]¶: Compute EVI = 2.5 * (NIR - Red) / (NIR + 6*Red - 7.5*Blue + 1) via Rust core (1D or 2D).

End of enhanced_vegetation_index documentation.

enhanced_vegetation_index¶