RVI (Ratio Vegetation Index)

Definition

The Ratio Vegetation Index (RVI) is one of the earliest and simplest vegetation indices, calculated as the ratio of near-infrared (NIR) to red reflectance. It leverages the fundamental spectral property of healthy vegetation: high reflectance in the NIR and low reflectance in the red due to chlorophyll absorption.

Application

RVI is used for basic vegetation detection, biomass estimation, and as a component in more complex indices. Due to its simplicity, it's valuable for educational purposes, historical data analysis (particularly with early Landsat data), and in systems with limited processing capabilities. It's also used in forestry for biomass mapping and in agriculture for crop monitoring.

FAQ

What is the formula for RVI?

RVI = NIR / Red. Unlike normalized indices, RVI has no upper bound; values typically range from 0 to over 20, with higher values indicating denser, healthier vegetation. Bare soil usually has values around 1, while water can have values less than 1.

How does RVI compare to NDVI in terms of sensitivity?

Key differences include:

1) RVI has a wider dynamic range and is less prone to saturation at high biomass levels compared to NDVI;

2) RVI is more sensitive to atmospheric effects and soil background variations;

3) RVI's unbounded range makes it less intuitive for direct interpretation and requires scene-specific thresholds;

4) RVI shows a non-linear relationship with vegetation parameters, while NDVI is more linear.

What are the advantages of using RVI despite its simplicity?

Advantages include:

1) Extreme simplicity and computational efficiency;

2) Historical continuity with early remote sensing studies;

3) Good sensitivity to high biomass where ratio-based indices like NDVI saturate;

4) Direct physical interpretation as the contrast between chlorophyll absorption and leaf scattering.

What are the main limitations of RVI?

Main limitations include:

1) High sensitivity to soil background, especially in sparse vegetation;

2) Strong influence from atmospheric scattering and absorption;

3) Unbounded range requiring scene-specific analysis;

4) Non-normalized nature makes cross-scene comparisons difficult.

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