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SRVISymbolic Regression Vegetation Index

VegetationMultispectralCitation Rank #308

Summary

The Symbolic Regression Vegetation Index (SRVI) is a vegetation spectral index intended for multispectral sensing. It was introduced in 2026; its source is cited as Charalambos Chrysostomou, Stelios P. Neophytides, Michalis Mavrovouniotis, & Diofantos G. Hadjimitsis (2026). Optimized spectral indices for global vegetation and water mapping using Sentinel-2. Scientific Reports, 16(1). https://doi.org/10.1038/s41598-025-34720-x .

Based on the latest citation data, this index is in the 3.15th percentile overall, ranking 308 out of 317 indices with citation data. Among the 19 indices published within two years of 2026, it ranks 11 (47.37th percentile). Within the vegetation application domain, it is in the 2.35th percentile and ranks 209 out of 213 indices with citation data. Among the 13 similarly aged vegetation indices, it ranks 9 (38.46th percentile).

Other indices from the same source

These catalogue entries share this index's scientific source and citation.

Formula

(2.0 * N - 3.0 * R) / (N + R + 0.5 * (G + S1))

Bands

N

Near-Infrared (NIR).

R

Red.

G

Green.

S1

Short-wave Infrared (SWIR) 1.

Polarizations

No radar polarizations are used in this index.

Constants

No constants are used in this index.

Reductions

No contextual reductions are used in this index.

Released under the MIT License.