Indices & Variables Reference

Contents

Indices & Variables Reference#

Complete catalog of the variables supported by ndvi2gif, organized by category and satellite platform.

Note

Many of the reference DOIs listed for the spectral indices below were sourced from the Awesome Spectral Indices catalogue (Montero et al., A standardized catalogue of spectral indices to advance the use of remote sensing in Earth system research, Scientific Data, 2023). We gratefully acknowledge this open community resource.

Overview by Category#

Category

Count

Platforms

Description

Optical Vegetation

40

S2, S3, Landsat, MODIS

NDVI, EVI, SAVI, and derivatives

SAR Vegetation

7

Sentinel-1

Radar-based vegetation indices

ERA5 Climate

40

ERA5-Land

Temperature, precipitation, soil, radiation

CHIRPS

1

CHIRPS

High-resolution precipitation

Total

88

7 platforms

Complete variable library

Optical Vegetation Indices (40)#

Compatible with: Sentinel-2, Sentinel-3, Landsat 4-9, MODIS

Core Vegetation Indices (7)#

NDVI - Normalized Difference Vegetation Index#

index='ndvi'

Formula: (NIR - Red) / (NIR + Red)

Range: -1 to +1

Description: Most widely used vegetation index. Measures greenness and photosynthetic activity.

Interpretation:

  • < 0: Water, clouds, snow

  • 0 - 0.2: Bare soil, rock

  • 0.2 - 0.5: Sparse vegetation, grassland

  • 0.5 - 0.8: Dense vegetation, crops

  • 0.8: Very dense vegetation, forests

Reference: Rouse et al. (1974)

EVI - Enhanced Vegetation Index#

index='evi'

Formula: 2.5 * (NIR - Red) / (NIR + 6*Red - 7.5*Blue + 1)

Range: -1 to +1

Description: Improved vegetation index with atmospheric and soil corrections. Less sensitive to atmospheric conditions than NDVI.

Advantages: Better in high biomass areas, reduced soil brightness influence

Reference: Huete et al. (2002)

SAVI - Soil Adjusted Vegetation Index#

index='savi'

Formula: ((NIR - Red) / (NIR + Red + L)) * (1 + L) where L=0.5

Range: -1 to +1

Description: Minimizes soil brightness influence in areas with sparse vegetation.

Use Cases: Arid/semi-arid regions, early crop growth

Reference: Huete (1988)

GNDVI - Green Normalized Difference Vegetation Index#

index='gndvi'

Formula: (NIR - Green) / (NIR + Green)

Range: -1 to +1

Description: More sensitive to chlorophyll content than NDVI. Better for later growth stages.

Use Cases: Nitrogen assessment, crop health monitoring

Reference: Original reference

NDMI - Normalized Difference Moisture Index#

index='ndmi'

Formula: (NIR - SWIR1) / (NIR + SWIR1)

Range: -1 to +1

Description: Sensitive to vegetation water content. Useful for drought monitoring.

Use Cases: Irrigation management, drought stress detection, fire risk

Reference: Original reference

EVI2 - Two-Band Enhanced Vegetation Index#

index='evi2'

Formula: 2.5 * (NIR - Red) / (NIR + 2.4*Red + 1)

Description: EVI without blue band requirement. Compatible with more sensors.

Advantages: Works with Landsat TM/ETM+ without blue band

Reference: Original reference

ARVI - Atmospherically Resistant Vegetation Index#

index='arvi'

Formula: (NIR - (2*Red - Blue)) / (NIR + (2*Red - Blue))

Description: Reduces atmospheric effects (aerosols, haze) using blue band.

Use Cases: Areas with high atmospheric contamination

Reference: Kaufman & Tanré (1992)

Water Indices (5)#

NDWI - Normalized Difference Water Index#

index='ndwi'

Formula: (Green - NIR) / (Green + NIR)

Range: -1 to +1

Description: Delineates open water features. Opposite of NDVI pattern.

Interpretation:

  • 0.3: Water bodies

  • 0 - 0.3: Mixed pixels

  • < 0: Land

Reference: McFeeters (1996)

MNDWI - Modified Normalized Difference Water Index#

index='mndwi'

Formula: (Green - SWIR1) / (Green + SWIR1)

Description: Improved water index that suppresses built-up areas better than NDWI.

Advantages: Better separation of water from urban areas

Reference: Xu (2006)

NDMI (Water Content)#

index='ndmi'

See Moisture section above - dual use for vegetation water content and water body detection

LSWI - Land Surface Water Index#

index='lswi'

Formula: (NIR - SWIR1) / (NIR + SWIR1)

Description: Detects surface water and soil moisture. Similar to NDMI.

Reference: Original reference

AWEInsh - Automated Water Extraction Index (no shadow)#

index='aweinsh'

Formula: 4 * (Green - SWIR1) - (0.25*NIR + 2.75*SWIR2)

Description: Eliminates shadow pixels that contaminate water extraction.

Advantages: Robust in urban and mountainous areas

Reference: Feyisa et al. (2014)

Advanced Vegetation Indices (10)#

OSAVI - Optimized Soil Adjusted Vegetation Index#

index='osavi'

Formula: (NIR - Red) / (NIR + Red + 0.16)

Description: Optimized L parameter for SAVI. Works across wider vegetation range.

Reference: Original reference

MSAVI - Modified Soil Adjusted Vegetation Index#

index='msavi'

Formula: (2*NIR + 1 - sqrt((2*NIR+1)^2 - 8*(NIR-Red))) / 2

Description: Self-adjusting L parameter based on NIR-Red relationship.

Reference: Original reference

VARI - Visible Atmospherically Resistant Index#

index='vari'

Formula: (Green - Red) / (Green + Red - Blue)

Description: Uses only visible bands. Good for RGB sensors without NIR.

Reference: Original reference

GCI - Green Chlorophyll Index#

index='gci'

Formula: (NIR / Green) - 1

Description: Sensitive to leaf chlorophyll content variations.

Use Cases: Nitrogen status, crop health assessment

Reference: Original reference

SIPI - Structure Insensitive Pigment Index#

index='sipi'

Formula: (NIR - Blue) / (NIR - Red)

Description: Ratio of carotenoids to chlorophyll. Stress indicator.

Reference: Original reference

NBR - Normalized Burn Ratio#

index='nbr'

Formula: (NIR - SWIR2) / (NIR + SWIR2)

Description: Highlights burned areas and fire severity.

Use Cases: Post-fire assessment, burn scar mapping

Reference: Original reference

BAIS2 - Burned Area Index for Sentinel-2#

index='bais2'

Formula: Complex formula using Red, NIR, SWIR1, SWIR2

Description: Optimized for Sentinel-2 burn severity mapping.

Platform: Sentinel-2 only (requires specific bands)

Reference: Original reference

BSI - Bare Soil Index#

index='bsi'

Formula: ((SWIR1 + Red) - (NIR + Blue)) / ((SWIR1 + Red) + (NIR + Blue))

Description: Identifies bare soil and unvegetated areas.

Reference: Original reference

NDSI - Normalized Difference Snow Index#

index='ndsi'

Formula: (Green - SWIR1) / (Green + SWIR1)

Description: Identifies snow cover vs clouds.

Interpretation: > 0.4 typically indicates snow

Reference: Original reference

CIG - Chlorophyll Index Green#

index='cig'

Formula: (NIR / Green) - 1

Description: Chlorophyll content using green band. Similar to GCI.

Reference: Original reference

Sentinel-2 Exclusive Indices (Red Edge) (12)#

These indices require Sentinel-2’s red edge bands (B5, B6, B7).

NDRE - Normalized Difference Red Edge#

index='ndre'  # Sentinel-2 only

Formula: (NIR - RedEdge1) / (NIR + RedEdge1)

Description: Uses red edge for detailed vegetation assessment.

Advantages: More sensitive to chlorophyll variations than NDVI

MCARI - Modified Chlorophyll Absorption Ratio Index#

index='mcari'  # Sentinel-2 only

Formula: ((RedEdge1 - Red) - 0.2*(RedEdge1 - Green)) * (RedEdge1 / Red)

Description: Chlorophyll content with reduced soil/atmospheric effects.

Reference: Original reference

CIre - Chlorophyll Index Red Edge#

index='cire'  # Sentinel-2 only

Formula: (NIR / RedEdge1) - 1

Description: Chlorophyll-sensitive index using red edge.

Reference: Original reference

IRECI - Inverted Red Edge Chlorophyll Index#

index='ireci'  # Sentinel-2 only

Formula: (RedEdge3 - Red) / (RedEdge2 / RedEdge1)

Description: ESA’s chlorophyll index for Sentinel-2.

Reference: Original reference

RECI - Red Edge Chlorophyll Index#

index='reci'  # Sentinel-2 only

Formula: (NIR / RedEdge1) - 1

Description: Alternative formulation for chlorophyll content.

Reference: Original reference

S2REP - Sentinel-2 Red Edge Position#

index='s2rep'  # Sentinel-2 only

Formula: 705 + 35 * ((((NIR + Red) / 2) - RedEdge1) / (RedEdge2 - RedEdge1))

Description: Estimates position of red edge inflection point (nm).

Use Cases: Nitrogen status, crop health

Reference: Original reference

NDVI_re1, NDVI_re2, NDVI_re3#

index='ndvi_re1'  # (NIR - RedEdge1) / (NIR + RedEdge1)
index='ndvi_re2'  # (NIR - RedEdge2) / (NIR + RedEdge2)
index='ndvi_re3'  # (NIR - RedEdge3) / (NIR + RedEdge3)

Description: NDVI variants using each of the 3 red edge bands.

MTCI - MERIS Terrestrial Chlorophyll Index#

index='mtci'  # Sentinel-2 compatible

Formula: (RedEdge2 - RedEdge1) / (RedEdge1 - Red)

Description: Chlorophyll concentration in dense canopies.

Reference: Original reference

MSAVI_re - Modified SAVI with Red Edge#

index='msavi_re'  # Sentinel-2 only

Description: MSAVI using red edge band instead of red.

PSRI - Plant Senescence Reflectance Index#

index='psri'  # Sentinel-2 only

Formula: (Red - Green) / RedEdge2

Description: Detects plant senescence and maturity stages.

Reference: Original reference

Water Quality Indices (6)#

NDTI - Normalized Difference Turbidity Index#

index='ndti'

Formula: (Red - Green) / (Red + Green)

Description: Estimates water turbidity and suspended sediment.

Reference: Original reference

Chlorophyll-a (Simple Ratio)#

index='chlorophyll'

Formula: (Blue / Green)

Description: Estimates chlorophyll-a concentration in water.

Use Cases: Lake/reservoir monitoring, eutrophication

KIVU - Water Clarity Index#

index='kivu'

Description: Specific index for lake water clarity assessment.

NDCI - Normalized Difference Chlorophyll Index#

index='ndci'

Formula: (RedEdge1 - Red) / (RedEdge1 + Red)

Description: Chlorophyll concentration in turbid waters.

Platform: Sentinel-2 (requires red edge)

Reference: Original reference

Turbidity#

index='turbidity'

Formula: Empirical formula using Red band

Description: Direct turbidity estimation from red reflectance.

Cyanobacteria#

index='cyanobacteria'

Formula: Uses Red and NIR bands

Description: Detects harmful algal blooms (cyanobacteria).

SAR Indices (7)#

Compatible with: Sentinel-1 (VV + VH polarizations)

RVI - Radar Vegetation Index#

sat='S1', index='rvi'

Formula: (4 * VH) / (VV + VH)

Range: 0 to ~4

Description: Most common SAR vegetation index. Sensitive to vegetation structure.

Interpretation:

  • < 0.5: Bare soil, water

  • 0.5 - 1.5: Sparse vegetation

  • 1.5: Dense vegetation

Reference: Original reference

DPSVI - Dual Polarization SAR Vegetation Index#

sat='S1', index='dpsvi'

Formula: VV + VH

Description: Simple combination sensitive to total vegetation biomass.

RFDI - Radar Forest Degradation Index#

sat='S1', index='rfdi'

Formula: (VV - VH) / (VV + VH)

Description: Detects forest degradation and deforestation.

Reference: Original reference

VSDI - Vegetation Scattering Difference Index#

sat='S1', index='vsdi'

Formula: VV - VH

Description: Difference between polarizations. Vegetation structure indicator.

VV - Vertical-Vertical Polarization#

sat='S1', index='vv'

Description: Single VV polarization backscatter. Sensitive to surface roughness.

VH - Vertical-Horizontal Polarization#

sat='S1', index='vh'

Description: Cross-polarization. Sensitive to volume scattering (vegetation canopy).

VV/VH Ratio#

sat='S1', index='vv_vh_ratio'

Formula: VV / VH

Description: Ratio between polarizations. Discriminates land cover types.

ERA5-Land Climate Variables (40)#

Compatible with: ERA5-Land (ECMWF reanalysis, 1950-present)

Temperature Variables (18)#

Core Temperature (Kelvin)#

sat='ERA5', index='temperature_2m'

Units: Kelvin

Description: Air temperature at 2 meters height (daily mean).

Coverage: 1950-present, ~11km resolution

Core Temperature (Celsius) - Auto-converted#

sat='ERA5', index='temperature_2m_celsius'

Units: °C (automatically converted from Kelvin)

Description: Same as above but in Celsius. Recommended for user-friendly output.

Daily Temperature Minimum#

sat='ERA5', index='temperature_2m_min'  # Kelvin
sat='ERA5', index='temperature_2m_min_celsius'  # °C

Description: Daily minimum temperature. Use key='min' for coldest day of period.

Daily Temperature Maximum#

sat='ERA5', index='temperature_2m_max'  # Kelvin
sat='ERA5', index='temperature_2m_max_celsius'  # °C

Description: Daily maximum temperature. Use key='max' for hottest day of period.

Dewpoint Temperature#

sat='ERA5', index='dewpoint_temperature_2m'  # Kelvin
sat='ERA5', index='dewpoint_temperature_2m_celsius'  # °C
sat='ERA5', index='dewpoint_temperature_2m_min'  # Daily min
sat='ERA5', index='dewpoint_temperature_2m_max'  # Daily max

Description: Dewpoint temperature at 2m. Humidity indicator.

Skin Temperature#

sat='ERA5', index='skin_temperature'  # Kelvin
sat='ERA5', index='skin_temperature_celsius'  # °C
sat='ERA5', index='skin_temperature_min'  # Daily min
sat='ERA5', index='skin_temperature_max'  # Daily max

Description: Land surface temperature.

Soil Temperature (Layer 1: 0-7cm)#

sat='ERA5', index='soil_temperature_level_1'  # Kelvin
sat='ERA5', index='soil_temperature_level_1_celsius'  # °C
sat='ERA5', index='soil_temperature_level_1_min'  # Daily min
sat='ERA5', index='soil_temperature_level_1_max'  # Daily max

Description: Soil temperature at 0-7cm depth.

Precipitation & Water Balance (10)#

Total Precipitation#

sat='ERA5', index='total_precipitation_sum'  # meters
sat='ERA5', index='total_precipitation_sum_lm2'  # L/m² (mm)

Units: meters or L/m² (1 L/m² = 1 mm)

Description: Daily accumulated precipitation (rain + snow).

Recommended: Use key='sum' for monthly/seasonal totals.

Total Evaporation#

sat='ERA5', index='total_evaporation_sum'  # meters
sat='ERA5', index='total_evaporation_sum_lm2'  # L/m²

Description: Daily evaporation from surface (negative values = upward flux).

Note: Negative in original data; absolute value recommended.

Potential Evaporation#

sat='ERA5', index='potential_evaporation_sum'  # meters
sat='ERA5', index='potential_evaporation_sum_lm2'  # L/m²

Description: Potential evapotranspiration (atmospheric demand).

Total Runoff#

sat='ERA5', index='runoff_sum'  # meters
sat='ERA5', index='runoff_sum_lm2'  # L/m²

Description: Total runoff (surface + subsurface).

Surface Runoff#

sat='ERA5', index='surface_runoff_sum'  # meters
sat='ERA5', index='surface_runoff_sum_lm2'  # L/m²

Description: Surface runoff only (excludes subsurface drainage).

Snowfall#

sat='ERA5', index='snowfall_sum'  # meters water equivalent
sat='ERA5', index='snowfall_sum_lm2'  # L/m²

Description: Daily snowfall in water equivalent.

Soil Moisture (4 layers)#

sat='ERA5', index='volumetric_soil_water_layer_1'  # 0-7 cm
sat='ERA5', index='volumetric_soil_water_layer_2'  # 7-28 cm
sat='ERA5', index='volumetric_soil_water_layer_3'  # 28-100 cm
sat='ERA5', index='volumetric_soil_water_layer_4'  # 100-289 cm

Units: m³/m³ (volumetric water content)

Range: 0-1

Description: Soil moisture at different depths.

Use Cases:

  • Layer 1: Surface moisture, infiltration

  • Layer 3: Root zone (crops)

  • Layer 4: Deep groundwater interaction

Radiation (3)#

Surface Solar Radiation Downwards#

sat='ERA5', index='surface_solar_radiation_downwards_sum'

Units: J/m²

Description: Solar energy reaching surface. Use key='sum'.

Surface Net Solar Radiation#

sat='ERA5', index='surface_net_solar_radiation_sum'

Units: J/m²

Description: Net solar radiation (incoming - outgoing).

Surface Latent Heat Flux#

sat='ERA5', index='surface_latent_heat_flux_sum'

Units: J/m²

Description: Energy used for evaporation.

Wind (2)#

sat='ERA5', index='u_component_of_wind_10m'  # East-West
sat='ERA5', index='v_component_of_wind_10m'  # North-South

Units: m/s

Description: Wind velocity components at 10m height.

Calculate wind speed: sqrt(u² + v²)

Pressure (1)#

sat='ERA5', index='surface_pressure'

Units: Pa

Description: Atmospheric pressure at surface.

Snow (2)#

Snow Depth (Water Equivalent)#

sat='ERA5', index='snow_depth_water_equivalent'

Units: meters of water

Description: Snow pack water content.

Snowfall (Daily)#

sat='ERA5', index='snowfall_sum'

Units: meters of water

Description: Daily snowfall accumulation.

CHIRPS Precipitation (1)#

Compatible with: CHIRPS (1981-present, ~5.5km, 50°S-50°N)

Precipitation#

sat='CHIRPS', index='precipitation'

Units: mm/day

Description: Satellite + station blended precipitation.

Recommended: Use key='sum' for monthly/seasonal totals.

Advantages: Higher resolution (~5.5km) and station-calibrated vs ERA5 precipitation.

Usage Examples#

Optical Vegetation#

from ndvi2gif import NdviSeasonality

# Basic NDVI
ndvi = NdviSeasonality(roi=roi, sat='S2', index='ndvi')

# Advanced Sentinel-2 chlorophyll
chlorophyll = NdviSeasonality(roi=roi, sat='S2', index='ndre')

# Water bodies
water = NdviSeasonality(roi=roi, sat='S2', index='mndwi')

SAR Vegetation#

# All-weather vegetation monitoring
sar_veg = NdviSeasonality(
    roi=roi,
    sat='S1',
    index='rvi',
    key='median'  # Reduces speckle
)

Climate Variables#

# Temperature analysis (Celsius)
temp = NdviSeasonality(
    roi=roi,
    sat='ERA5',
    index='temperature_2m_celsius',
    start_year=1980,
    end_year=2023,
    key='mean'
)

# Precipitation totals
precip = NdviSeasonality(
    roi=roi,
    sat='ERA5',
    index='total_precipitation_sum_lm2',
    key='sum'  # Monthly/seasonal totals
)

# High-resolution precipitation
precip_chirps = NdviSeasonality(
    roi=roi,
    sat='CHIRPS',
    index='precipitation',
    key='sum'
)

# Soil moisture (root zone)
soil = NdviSeasonality(
    roi=roi,
    sat='ERA5',
    index='volumetric_soil_water_layer_3',  # 28-100cm
    key='mean'
)

Platform Compatibility Matrix#

Index Type

S2

S3

Landsat

MODIS

S1

ERA5

CHIRPS

Optical (basic)

✓

✓

✓

✓

✗

✗

✗

Red Edge

✓

✗

✗

✗

✗

✗

✗

SAR

✗

✗

✗

✗

✓

✗

✗

Climate

✗

✗

✗

✗

✗

✓

✓

References#

Vegetation Indices:

  • Rouse et al. (1974) - NDVI

  • Huete et al. (2002) - EVI

  • McFeeters (1996) - NDWI

  • Xu (2006) - MNDWI

  • Feyisa et al. (2014) - AWEInsh

Climate Datasets:

  • Muñoz-Sabater, J. (2019) - ERA5-Land [DOI:10.24381/cds.e2161bac]

  • Funk et al. (2015) - CHIRPS [DOI:10.1038/sdata.2015.66]

See Also#

Contents