SuperView-2 Spectral Indices

Vegetation index that minimizes atmospheric effects by incorporating blue band correction. More resistant to atmospheric scattering than NDVI, particularly useful in areas with atmospheric haze or high aerosol content.

Simple vegetation index calculating the ratio of near-infrared to red reflectance. One of the earliest vegetation indices, useful for biomass estimation and vegetation analysis.

Improved vegetation index that reduces atmospheric and soil background effects. More sensitive to vegetation changes than NDVI.

Geological index for detecting ferric iron (Fe3+) concentrations in rocks and soils. Useful for lithologic mapping and identifying iron-rich mineral formations.

Simple vegetation index that calculates the difference between near-infrared and green spectral bands. Useful for assessing vegetation health and density with straightforward band arithmetic.

Non-linear vegetation index designed for global vegetation monitoring from satellites. Less sensitive to soil background variations compared to NDVI and provides enhanced discrimination of vegetation states.

Vegetation index that uses green wavelengths instead of red to assess vegetation characteristics. More sensitive to chlorophyll content and can be useful for detecting stress in dense vegetation canopies.

Soil-adjusted vegetation index that uses green wavelengths and incorporates a soil adjustment factor to minimize soil background influences. Optimized for vegetation monitoring in areas with varying soil conditions.

Simple vegetation index that calculates the ratio of near-infrared to green band reflectance. Useful for vegetation fraction estimation and assessing plant health using green wavelengths.

Soil-adjusted vegetation index using green wavelengths to minimize soil background interference. Incorporates a soil adjustment factor (L=0.5) to improve vegetation signal extraction.

Color index representing the dominant wavelength in visible spectrum. Used for color analysis and classification of materials based on their spectral hue characteristics.

Color brightness measure representing the total reflectance across visible bands. Used for overall brightness analysis and intensity-based classification.

Enhanced vegetation index that combines simple ratio and NDVI approaches. Provides improved sensitivity to vegetation changes and reduced soil background effects.

Self-adjusting vegetation index that minimizes soil background influence without requiring soil line parameters. Automatically adjusts for varying soil conditions.

Most commonly used vegetation index to assess plant health and density. Values range from -1 to 1, with higher values indicating healthier vegetation.

The most widely used vegetation index for assessing vegetation health, density, and photosynthetic activity. Classic formulation using standard red and near-infrared bands.

Used to detect water bodies and monitor water content in vegetation. Positive values typically indicate water presence.

Normalized green reflectance component for vegetation analysis. Provides relative contribution of green band reflectance in visible-NIR spectrum.

Normalized near-infrared reflectance component for vegetation analysis. Highlights vegetation structural properties and biomass distribution.

Normalized red reflectance component for vegetation analysis. Useful for analyzing chlorophyll absorption and vegetation stress indicators.

Vegetation index that minimizes soil brightness influences. The L factor is typically set to 0.5 for moderate vegetation cover.

The Anthocyanin Reflectance Index (ARI) was developed by Gitelson et al. to non-destructively estimate anthocyanin content in plant leaves. It isolates the anthocyanin absorption peak around 550nm by subtracting the 700nm band that reflects only chlorophyll. ARI is particularly useful for monitoring plant stress, senescence, and physiological status.

The Modified Anthocyanin Reflectance Index (mARI or ARI2) is an enhanced version of ARI that corrects for leaf density and thickness by incorporating a near-infrared band. This modification improves the accuracy of anthocyanin estimation by accounting for leaf scattering properties.

ARVI2 is an enhanced version of the Atmospherically Resistant Vegetation Index designed to be resistant to atmospheric effects while being more sensitive to a wide range of chlorophyll concentrations. It builds upon the original ARVI concept by Kaufman and Tanré, providing improved vegetation monitoring capabilities under varying atmospheric conditions.

The Burn Area Index (BAI) was developed by Chuvieco et al. (2002) to identify burned areas using the red and NIR spectral bands. BAI emphasizes the charcoal signal in post-fire images by considering the spectral distance from each pixel to a reference spectral point where recently burned areas tend to converge.

Blue Green Pigment Index (BGI) is a simple ratio index that compares reflectance in the blue (450nm) and green (550nm) regions of the spectrum. It is used to assess plant pigment content, particularly useful for detecting changes in chlorophyll and carotenoid concentrations that affect blue and green light absorption.

The Brightness Index (BI) is a remote sensing index used to assess soil brightness, which is highly correlated with soil moisture, salt content, and organic matter. Developed by Mathieu and Escadafal, it provides valuable information about soil properties and fertility. As brightness increases, soil fertility typically decreases.

The Second Brightness Index (BI2) is an enhanced version of the Brightness Index that includes the near-infrared band in addition to red and green bands. Developed by Escadafal and Huete, it provides improved assessment of soil properties, particularly soil organic carbon content and moisture levels.

A vegetation index that uses blue instead of red bands. BNDVI can be useful in situations where the red band is saturated or when assessing vegetation in water bodies where blue light penetrates better.

Blue Near-Infrared Reflectance of Vegetation - A spectral index for vegetation applications.

Blue Red Pigment Index (BRI) is a simple ratio index that compares reflectance in the blue (450nm) and red (690nm) regions of the spectrum. It is designed to assess plant pigment content and is sensitive to changes in chlorophyll and carotenoid concentrations, making it useful for stress detection and pigment analysis.

A blue-based variant of WDRVI that uses blue instead of red bands. This index maintains sensitivity at high biomass levels while using the blue spectral region, which can be advantageous in certain applications.

Carter2 (Ctr2) is a plant stress index that uses the ratio of reflectance at 695nm (red-edge) to 760nm (near-infrared). This index is particularly effective at detecting stress because it combines the stress-sensitive red-edge region with the NIR region where healthy vegetation shows high reflectance.

A simple chlorophyll index using the ratio of NIR to red edge reflectance minus 1. This index is sensitive to chlorophyll content variations and is useful for LAI estimation.

The Coloration Index (CI) was developed by Pouget et al. (1990) to characterize soil color properties in arid and semi-arid regions. Low CI values correlate with high concentrations of carbonates or sulfates, while higher values correlate with crusted soils and sands. The index helps monitor surface degradation and infiltrability variations.

The Carotenoid Reflectance Index 550 (CRI550) was developed by Gitelson et al. (2002) to assess carotenoid content in plant leaves. It uses reciprocal reflectance at 510nm (sensitive to carotenoids) and 550nm (to remove chlorophyll effects), providing a non-destructive method for carotenoid estimation.

The Carotenoid Reflectance Index 700 (CRI700) is an alternative formulation to CRI550 that uses the 700nm band instead of 550nm to minimize chlorophyll effects. This index provides better performance in leaves with high chlorophyll content and is particularly useful for mature vegetation.

A vegetation stress index using the ratio of red edge (710nm) to NIR (760nm) reflectance. This index is particularly sensitive to changes in chlorophyll content and plant stress.

Geological index for detecting ferric oxide concentrations in rocks and soils. Useful for identifying iron-rich minerals and oxide formations in geological mapping and mineral exploration.

The Green Atmospherically Resistant Vegetation Index (GARI) is tailored on the concept of ARVI but uses the green band instead of red. It is expected to be as resistant to atmospheric effects as ARVI but more sensitive to a wide range of chlorophyll-a concentrations. GARI has a wider dynamic range than NDVI and is, on average, at least five times more sensitive to chlorophyll concentration.

The Global Environmental Monitoring Index (GEMI) is a non-linear vegetation index developed by Pinty and Verstraete (1992) specifically designed to reduce atmospheric effects without requiring detailed atmospheric correction. Unlike NDVI, GEMI maintains information about vegetation cover while being more resistant to atmospheric perturbations.

Geological index for detecting gossan formations - weathered, oxidized iron-bearing rocks that form at the surface above sulfide mineral deposits. Essential for mineral exploration and identifying potential ore deposits.

An index specifically designed to estimate leaf chlorophyll content using red edge bands. LCI is sensitive to chlorophyll variations while being less affected by leaf structure and canopy architecture.

The Land Surface Water Index (LSWI) was developed by Xiao et al. to monitor vegetation and soil water content. LSWI is sensitive to liquid water in vegetation due to strong SWIR absorption by water. It is widely used for drought monitoring, water stress detection, and integration into vegetation productivity models.

Enhanced vegetation chlorophyll index with improved sensitivity and reduced soil background effects. Modified version of MCARI using standard satellite bands.

Advanced vegetation chlorophyll index with enhanced sensitivity and reduced soil background effects. Improved version of MCARI for better leaf area index prediction.

MCARI/MTVI2 is a ratio index that combines the Modified Chlorophyll Absorption Ratio Index (MCARI) with the Modified Triangular Vegetation Index 2 (MTVI2). This combination provides improved sensitivity to leaf chlorophyll content while reducing the influence of leaf area index variations, making it particularly useful for agricultural applications.

MCARI/OSAVI combines the Modified Chlorophyll Absorption Ratio Index (MCARI) with the Optimized Soil-Adjusted Vegetation Index (OSAVI). This ratio index is designed to estimate leaf chlorophyll content while minimizing the confounding effects of leaf area index and soil background reflectance.

The Modified Normalized Difference Water Index (MNDWI) was developed by Xu (2006) as an improvement over the original NDWI. By substituting the NIR band with SWIR, MNDWI can enhance open water features while efficiently suppressing noise from built-up areas, vegetation, and soil. This makes it particularly suitable for water detection in urban environments.

A modified version of the Nonlinear vegetation index that uses SWIR bands. This index is designed to improve vegetation monitoring in areas with high biomass by incorporating SWIR reflectance.

Hyperspectral version of MSAVI optimized for precise wavelength bands. Provides enhanced vegetation monitoring with reduced soil background effects.

Simple ratio index for detecting vegetation water stress and moisture content. Higher values indicate greater water stress in vegetation.

A modified simple ratio vegetation index optimized for boreal forest applications. It normalizes the difference between NIR and red reflectance, providing improved LAI estimation in forest environments.

Modified Simple Ratio (705 and 445 nm) - A spectral index for vegetation applications.

Enhanced vegetation index combining green, red, and near-infrared reflectance for improved leaf area index estimation and vegetation monitoring.

Advanced triangular vegetation index with enhanced sensitivity to vegetation chlorophyll content and reduced soil background interference.

Burn severity index for detecting and monitoring fire damage in vegetation. Higher values indicate healthy vegetation, lower values indicate burned areas.

Specialized vegetation index using mid-infrared and near-infrared bands. Particularly effective during strong atmospheric disturbances and for vegetation vitality assessment.

Highlights built-up areas and urban development. Higher values indicate more built-up surfaces.

Vegetation water content index sensitive to changes in vegetation moisture and canopy water stress. Useful for drought monitoring and irrigation management.

Vegetation moisture index sensitive to changes in vegetation water content. Useful for drought monitoring, irrigation management, and fire risk assessment.

The Normalized Difference Moisture Index (NDMI) was utilized by Wilson and Sader (2002) to detect moisture levels in vegetation. NDMI is sensitive to vegetation water content using NIR and SWIR bands, making it useful for drought monitoring, water stress detection, and forest disturbance mapping.

Normalized Difference Red-Edge (NDRE) is a vegetation index that uses the red-edge band instead of the red band used in NDVI. It is particularly sensitive to chlorophyll content in leaves and can detect variations in crop health and nitrogen status more effectively than NDVI, especially in moderate to high biomass conditions.

NDVIc is a corrected version of NDVI that incorporates SWIR bands to account for atmospheric and canopy background effects. The correction factor using SWIR bands helps improve the accuracy of vegetation assessments, particularly in areas with varying atmospheric conditions or soil backgrounds.

The Normalized Difference Water Index (NDWI) proposed by McFeeters (1996) is designed to delineate open water features and enhance their presence in remotely-sensed digital imagery. It uses reflected near-infrared radiation and visible green light to enhance water features while eliminating soil and terrestrial vegetation features.

Normalized Green Red Difference Index for vegetation applications

Non-Homogeneous Feature Difference for urban applications

Near-Infrared Reflectance of Vegetation for vegetation applications

Hyperspectral Near-Infrared Reflectance of Vegetation for vegetation applications

Near-Infrared Reflectance of Vegetation and Incoming PAR for vegetation applications

A vegetation index that uses a nonlinear relationship between NIR and red bands to reduce the saturation effect at high biomass levels. The squared NIR term helps maintain sensitivity to vegetation changes in dense canopies.

Normalized Green for vegetation applications

Normalized NIR for vegetation applications

Normalized Red for vegetation applications

Optimized Chlorophyll Vegetation Index for vegetation applications

Oil Spill Index for water applications

Plastic Index for water applications

Perpendicular Impervious Surface Index for urban applications

Pan NDVI is designed for vegetation analysis, calculating vegetation health and density by comparing near-infrared and visible light reflectance. It provides a normalized method to assess vegetation health across multiple spectral bands.

A water stress index that quantifies relative water content at the leaf level. The ratio of 970nm to 900nm reflectance is sensitive to water absorption features and provides information about plant water status.

Red Chromatic Coordinate for vegetation applications

Red-Edge Disease Stress Index for vegetation applications

Red Green Blue Vegetation Index for vegetation applications

Red-Green Ratio Index for vegetation applications

SPOT HRV XS-based Redness Index 4 for soil applications

Reversed Normalized Difference Vegetation Index for water applications

S3 Snow Index for snow applications

Soil Adjusted and Atmospherically Resistant Vegetation Index for vegetation applications

A spectral index that calculates the color saturation by comparing the maximum and minimum RGB values. Used for analyzing vegetation characteristics and spectral indices for degradation of natural environments.

Soil-Adjusted Vegetation Index 2 for vegetation applications

Soil-Adjusted Vegetation Index Thermal for burn applications

Sentinel-2 LAI Green Index for vegetation applications

Shadow-Eliminated Vegetation Index for vegetation applications

Shadow Index for vegetation applications

Structure Insensitive Pigment Index for vegetation applications

The Structure Insensitive Pigment Index (SIPI) was developed by Peñuelas et al. (1995) to assess the ratio of carotenoids to chlorophyll-a while minimizing the effects of canopy structure variation. SIPI is particularly useful for detecting plant stress and senescence, as chlorophylls tend to decline more rapidly than carotenoids under stress conditions.

Simple Ratio for vegetation applications

Simple Ratio (800 and 550 nm) for vegetation applications

Simple Ratio (860, 550 and 708 nm) for vegetation applications

Simple Ratio (555 and 750 nm) for vegetation applications

Snow Water Index for snow applications

Sentinel Water Mask for water applications

An index designed to estimate vegetation chlorophyll content while minimizing the effects of leaf area index. TCARI is particularly useful for precision agriculture and crop health monitoring.

TCARI/OSAVI is a combined vegetation index that integrates the Transformed Chlorophyll Absorption in Reflectance Index (TCARI) with the Optimized Soil-Adjusted Vegetation Index (OSAVI). It is designed for accurate estimation of crop chlorophyll content while minimizing the effects of soil background and leaf area index variations.

TCARI/OSAVI Ratio for vegetation applications

Triangular Chlorophyll Index - A spectral index for vegetation applications.

Transformed Difference Vegetation Index - A spectral index for vegetation applications.

Triangular Greenness Index - A spectral index for vegetation applications.

Triangular Vegetation Index - A spectral index for vegetation applications.

Transformed Red Range Vegetation Index - A spectral index for vegetation applications.

A vegetation index designed to minimize soil brightness effects on vegetation measurements. TSAVI requires knowledge of the soil line parameters (slope and intercept) for optimal performance.

A simple transformation of NDVI that shifts values to avoid negative numbers. TVI ranges from 0 to 1, making it easier to interpret and use in some applications.

Visible Atmospherically Resistant Index - A spectral index for vegetation applications.

Visible Atmospherically Resistant Index (700 nm) - A spectral index for vegetation applications.

A red edge variant of VARI that uses red edge bands instead of green. This index is designed to estimate vegetation fraction with reduced atmospheric effects.

The Visible Atmospherically Resistant Index (VARI) is designed to emphasize vegetation in the visible portion of the spectrum while mitigating illumination differences and atmospheric effects. It evaluates the 'greenness' in plants using only visible light bands, making it ideal for standard RGB cameras without requiring specialized multispectral sensors.

Visible Green-Based Built-Up Index - A spectral index for urban applications.

VI6T Index - A spectral index for burn applications.

Vegetation Index (700 nm) - A spectral index for vegetation applications.

Vegetation Index Built-up Index - A spectral index for urban applications.

Vegetation Index Green - A spectral index for vegetation applications.

Visible Red-Based Built-Up Index - A spectral index for urban applications.

A vegetation index designed to improve sensitivity for moderate to high biomass conditions where traditional NDVI saturates. The weighting factor (0.1) enhances the dynamic range of the vegetation signal.

A vegetation index that accounts for soil background by using a weighted difference between NIR and red bands. The weight parameter 'a' is the slope of the soil line, typically derived from bare soil measurements.

Water Ratio Index - A spectral index for water applications.