Spectral Index¶

The plantcv.spectral_index subpackage contains functions that calculate indices from multi-channel image data, typically from a hyperspectral datacube, which is a Spectral_data class instance created while reading in with the pcv.readimage function with mode='envi'. For certain indices RGB images are valid input. There is also a parameter to allow some flexibility if the required wavelengths for a specific index are not available.

ARI¶

Calculates the Anthocyanin Reflectance Index using reflectance values (Gitelson et al., 2001):

ARI = (1 / R550) - (1 / R700)

Index range: -Inf, Inf

plantcv.spectral_index.ari(hsi, distance=20)

returns calculated index array (instance of the Spectral_data class)

• Parameters:
  • hsi - Hyperspectral image object, an instance of the Spectral_data class in plantcv (read in using pcv.readimage with mode='envi')
  • distance - Amount of flexibility (in nanometers) regarding the bands used to calculate an index.

CI_REDEDGE¶

Calculates the Chlorophyll Index Rededge using reflectance values (Gitelson et al., 2003):

CI_REDEDGE = (R800 / R700) - 1

Index range: -1.0, Inf

plantcv.spectral_index.ci_rededge(hsi, distance=20)

returns calculated index array (instance of the Spectral_data class)

• Parameters:
  • hsi - Hyperspectral image object, an instance of the Spectral_data class in plantcv (read in using pcv.readimage with mode='envi')
  • distance - Amount of flexibility (in nanometers) regarding the bands used to calculate an index.

CRI550¶

Calculates the Carotenoid Reflectance Index 550 using reflectance values (Gitelson et al., 2002a):

CRI550 = (1 / R510) - (1 / R550)

Index range: -Inf, Inf

plantcv.spectral_index.cri550(hsi, distance=20)

returns calculated index array (instance of the Spectral_data class)

• Parameters:
  • hsi - Hyperspectral image object, an instance of the Spectral_data class in plantcv (read in using pcv.readimage with mode='envi')
  • distance - Amount of flexibility (in nanometers) regarding the bands used to calculate an index.

CRI700¶

Calculates the Carotenoid Reflectance Index 700 using reflectance values (Gitelson et al., 2002a):

CRI700 = (1 / R510) - (1 / R700)

Index range: -Inf, Inf

plantcv.spectral_index.cri700(hsi, distance=20)

returns calculated index array (instance of the Spectral_data class)

• Parameters:
  • hsi - Hyperspectral image object, an instance of the Spectral_data class in plantcv (read in using pcv.readimage with mode='envi')
  • distance - Amount of flexibility (in nanometers) regarding the bands used to calculate an index.

EGI¶

Calculates the Excess Green Index using RGB values (Woebbecke et al., 1995):

r = R / (R + G + B)
g = G / (R + G + B)
b = B / (R + G + B)
EGI = 2g - r - b

Index range: -1, 2

plantcv.spectral_index.egi(rgb_img)

returns calculated index array (instance of the Spectral_data class)

• Parameters:
  • rgb_img - Color image.

EVI¶

Calculates the Enhanced Vegetation index using reflectance values (Huete et al., 1997):

EVI = (2.5 * (NIR - RED)) / (1 + NIR + (6 * RED) - (7.5 * BLUE))

Here, we use ~R800 for NIR, ~R670 for RED, and ~R480 for BLUE:

EVI = (2.5 * (R800 - R670)) / (1 + R800 + (6 * R670) - (7.5 * R480))

Index range: -Inf, Inf

plantcv.spectral_index.evi(hsi, distance=20)

returns calculated index array (instance of the Spectral_data class)

• Parameters:
  • hsi - Hyperspectral image object, an instance of the Spectral_data class in plantcv (read in using pcv.readimage with mode='envi')
  • distance - Amount of flexibility (in nanometers) regarding the bands used to calculate an index.

GDVI¶

Calculates the Green Difference Vegetation Index using reflectance values (Sripada et al., 2006):

GDVI = (NIR - GREEN) / (NIR + GREEN)

Here, we use ~R800 for NIR and ~R550 for GREEN:

GDVI = (R800 - R550) / (R800 + R550)

Index range: -2.0, 2.0

plantcv.spectral_index.gdvi(hsi, distance=20)

returns calculated index array (instance of the Spectral_data class)

• Parameters:
  • hsi - Hyperspectral image object, an instance of the Spectral_data class in plantcv (read in using pcv.readimage with mode='envi')
  • distance - Amount of flexibility (in nanometers) regarding the bands used to calculate an index.

MARI¶

Calculates the Modified Anthocyanin Reflectance Index using reflectance values (Gitelson et al., 2006):

MARI = ((1 / R550) - (1 / R700)) * R800

Index range: -Inf, Inf

plantcv.spectral_index.mari(hsi, distance=20)

returns calculated index array (instance of the Spectral_data class)

• Parameters:
  • hsi - Hyperspectral image object, an instance of the Spectral_data class in plantcv (read in using pcv.readimage with mode='envi')
  • distance - Amount of flexibility (in nanometers) regarding the bands used to calculate an index.

MCARI¶

Calculates the Modified Chlorophyll Absorption Reflectance Index using reflectance values (Daughtry et al., 2000):

MCARI = ((R700 - R670) - 0.2 * (R700 - R550)) * (R700 / R670)

Index range: -Inf, Inf

plantcv.spectral_index.mcari(hsi, distance=20)

returns calculated index array (instance of the Spectral_data class)

• Parameters:
  • hsi - Hyperspectral image object, an instance of the Spectral_data class in plantcv (read in using pcv.readimage with mode='envi')
  • distance - Amount of flexibility (in nanometers) regarding the bands used to calculate an index.

MTCI¶

Calculates the MERIS Terrestrial Chlorophyll Index using reflectance values (Dash and Curran 2004):

MTCI = (R753.75 - R708.75) / (R708.75 - R681.25)

Index range: -Inf, Inf

plantcv.spectral_index.mtci(hsi, distance=20)

returns calculated index array (instance of the Spectral_data class)

• Parameters:
  • hsi - Hyperspectral image object, an instance of the Spectral_data class in plantcv (read in using pcv.readimage with mode='envi')
  • distance - Amount of flexibility (in nanometers) regarding the bands used to calculate an index.

NDRE¶

Calculates the Normalized Difference Red Edge index using reflectance values (Barnes et al., 2000):

NDRE = (R790 - R720) / (R790 + R720)

Index range: -1.0, 1.0

plantcv.spectral_index.ndre(hsi, distance=20)

returns calculated index array (instance of the Spectral_data class)

• Parameters:
  • hsi - Hyperspectral image object, an instance of the Spectral_data class in plantcv (read in using pcv.readimage with mode='envi')
  • distance - Amount of flexibility (in nanometers) regarding the bands used to calculate an index.

NDVI¶

Calculates the Normalized Difference Vegetation Index using reflectance values (Rouse et al., 1974):

NDVI = (NIR - RED) / (NIR + RED)

Here, we use ~R800 for NIR and ~R670 for RED:

NDVI = (R800 - R670) / (R800 + R670)

Index range: -1.0, 1.0

plantcv.spectral_index.ndvi(hsi, distance=20)

returns calculated index array (instance of the Spectral_data class)

• Parameters:
  • hsi - Hyperspectral image object, an instance of the Spectral_data class in plantcv (read in using pcv.readimage with mode='envi')
  • distance - Amount of flexibility (in nanometers) regarding the bands used to calculate an index.

PRI¶

Calculates the Photochemical Reflectance Index using reflectance values (Penuelas et al., 1995a):

PRI = (R531 - R570) / (R531 + R570)

Index range: -1.0, 1.0

plantcv.spectral_index.pri(hsi, distance=20)

returns calculated index array (instance of the Spectral_data class)

• Parameters:
  • hsi - Hyperspectral image object, an instance of the Spectral_data class in plantcv (read in using pcv.readimage with mode='envi')
  • distance - Amount of flexibility (in nanometers) regarding the bands used to calculate an index.

PSND-Chlorophyll a¶

Calculates the Pigment Specific Normalized Difference for Chlorophyll a using reflectance values (Blackburn 1998):

PSND_CHLA = (R800 - R680) / (R800 + R680)

Index range: -1.0, 1.0

plantcv.spectral_index.psnd_chla(hsi, distance=20)

returns calculated index array (instance of the Spectral_data class)

• Parameters:
  • hsi - Hyperspectral image object, an instance of the Spectral_data class in plantcv (read in using pcv.readimage with mode='envi')
  • distance - Amount of flexibility (in nanometers) regarding the bands used to calculate an index.

PSND-Chlorophyll b¶

Calculates the Pigment Specific Normalized Difference for Chlorophyll b using reflectance values (Blackburn 1998):

PSND_CHLB = (R800 - R635) / (R800 + R635)

Index range: -1.0, 1.0

plantcv.spectral_index.psnd_chlb(hsi, distance=20)

returns calculated index array (instance of the Spectral_data class)

• Parameters:
  • hsi - Hyperspectral image object, an instance of the Spectral_data class in plantcv (read in using pcv.readimage with mode='envi')
  • distance - Amount of flexibility (in nanometers) regarding the bands used to calculate an index.

PSND-Caroteniods¶

Calculates the Pigment Specific Normalized Difference for Caroteniods using reflectance values (Blackburn 1998):

PSND_CAR = (R800 - R470) / (R800 + R470)

Index range: -1.0, 1.0

plantcv.spectral_index.psnd_car(hsi, distance=20)

returns calculated index array (instance of the Spectral_data class)

• Parameters:
  • hsi - Hyperspectral image object, an instance of the Spectral_data class in plantcv (read in using pcv.readimage with mode='envi')
  • distance - Amount of flexibility (in nanometers) regarding the bands used to calculate an index.

PSRI¶

Calculates the Plant Senescence Reflectance Index using reflectance values (Merzlyak et al., 1999):

PSRI = (R678 - R500) / R750

Index range: -Inf, Inf

plantcv.spectral_index.psri(hsi, distance=20)

returns calculated index array (instance of the Spectral_data class)

• Parameters:
  • hsi - Hyperspectral image object, an instance of the Spectral_data class in plantcv (read in using pcv.readimage with mode='envi')
  • distance - Amount of flexibility (in nanometers) regarding the bands used to calculate an index.

PSSR-Chlorophyll a¶

Calculates the Pigment Specific Simple Ratio for Chlorophyll a using reflectance values (Blackburn 1998):

PSSR_CHLA = R800 / R680

Index range: -1.0, 1.0

plantcv.spectral_index.pssr_chla(hsi, distance=20)

returns calculated index array (instance of the Spectral_data class)

• Parameters:
  • hsi - Hyperspectral image object, an instance of the Spectral_data class in plantcv (read in using pcv.readimage with mode='envi')
  • distance - Amount of flexibility (in nanometers) regarding the bands used to calculate an index.

PSSR-Chlorophyll b¶

Calculates the Pigment Specific Simple Ratio for Chlorophyll b using reflectance values (Blackburn 1998):

PSSR_CHLB = R800 / R635

Index range: -1.0, 1.0

plantcv.spectral_index.pssr_chlb(hsi, distance=20)

returns calculated index array (instance of the Spectral_data class)

• Parameters:
  • hsi - Hyperspectral image object, an instance of the Spectral_data class in plantcv (read in using pcv.readimage with mode='envi')
  • distance - Amount of flexibility (in nanometers) regarding the bands used to calculate an index.

PSSR-Caroteniods¶

Calculates the Pigment Specific Simple Ratio for Caroteniods using reflectance values (Blackburn 1998):

PSSR_CAR = R800 / R470

Index range: -1.0, 1.0

plantcv.spectral_index.pssr_car(hsi, distance=20)

returns calculated index array (instance of the Spectral_data class)

• Parameters:
  • hsi - Hyperspectral image object, an instance of the Spectral_data class in plantcv (read in using pcv.readimage with mode='envi')
  • distance - Amount of flexibility (in nanometers) regarding the bands used to calculate an index.

RGRI¶

Calculates the Red:Green Ratio Index for anthocyanin using reflectance values (Gamon and Surfus 1999):

RGRI = RED / GREEN

Here, we use ~R670 for RED and ~R560 for GREEN:

RGRI = R670 / R560

Index range: 0.0, Inf

plantcv.spectral_index.rgri(hsi, distance=20)

returns calculated index array (instance of the Spectral_data class)

• Parameters:
  • hsi - Hyperspectral image object, an instance of the Spectral_data class in plantcv (read in using pcv.readimage with mode='envi')
  • distance - Amount of flexibility (in nanometers) regarding the bands used to calculate an index.

RVSI¶

Calculates the Red-Edge Vegetation Stress Index using reflectance values (Merton and Huntington 1999):

RVSI = ((R714 + R752) / 2) - R733

Index range: -1.0, 1.0

plantcv.spectral_index.rvsi(hsi, distance=20)

returns calculated index array (instance of the Spectral_data class)

• Parameters:
  • hsi - Hyperspectral image object, an instance of the Spectral_data class in plantcv (read in using pcv.readimage with mode='envi')
  • distance - Amount of flexibility (in nanometers) regarding the bands used to calculate an index.

SAVI¶

Calculates the Soil Adjusted Vegetation Index using reflectance values (Huete 1988):

SAVI = (1.5 * (NIR - RED)) / (NIR + RED + 0.5)

Here, we use ~R800 for NIR and ~R680 for RED:

SAVI = (1.5 * (R800 - R680)) / (R800 + R680 + 0.5)

Index range: -1.2, 1.2

plantcv.spectral_index.savi(hsi, distance=20)

returns calculated index array (instance of the Spectral_data class)

• Parameters:
  • hsi - Hyperspectral image object, an instance of the Spectral_data class in plantcv (read in using pcv.readimage with mode='envi')
  • distance - Amount of flexibility (in nanometers) regarding the bands used to calculate an index.

SIPI¶

Calculates the Structure-Independent Pigment Index using reflectance values (Penuelas et al., 1995b):

SIPI = (NIR - RED) / (NIR - BLUE)

Here, we use ~R800 for NIR, ~670 for RED and ~R480 for BLUE:

SIPI = (R800 - R680) / (R800 - R480)

Index range: -Inf, Inf

plantcv.spectral_index.sipi(hsi, distance=20)

returns calculated index array (instance of the Spectral_data class)

• Parameters:
  • hsi - Hyperspectral image object, an instance of the Spectral_data class in plantcv (read in using pcv.readimage with mode='envi')
  • distance - Amount of flexibility (in nanometers) regarding the bands used to calculate an index.

SR¶

Calculates the Simple Ratio using reflectance values (Jordan 1969):

SR = NIR / RED

Here, we use ~R800 for NIR and ~R670 for RED:

SR = R800 / R670

Index range: 0.0, Inf

plantcv.spectral_index.sr(hsi, distance=20)

returns calculated index array (instance of the Spectral_data class)

• Parameters:
  • hsi - Hyperspectral image object, an instance of the Spectral_data class in plantcv (read in using pcv.readimage with mode='envi')
  • distance - Amount of flexibility (in nanometers) regarding the bands used to calculate an index.

VARI¶

Calculates the Visible Atmospherically Resistant Index using reflectance values (Gitelson et al., 2002b):

VARI = (GREEN - RED) / (GREEN + RED - BLUE)

Here, we use ~R480 for BLUE, ~R550 for GREEN, and ~R670 for RED:

VARI = (R550 - R670) / (R550 + R670 - R480)

Index range: -Inf, Inf

plantcv.spectral_index.vari(hsi, distance=20)

returns calculated index array (instance of the Spectral_data class)

• Parameters:
  • hsi - Hyperspectral image object, an instance of the Spectral_data class in plantcv (read in using pcv.readimage with mode='envi')
  • distance - Amount of flexibility (in nanometers) regarding the bands used to calculate an index.

VI_GREEN¶

Calculates the Vegetation Index using green bands using reflectance values (Gitelson et al., 2002b):

VIgreen = (GREEN - RED) / (GREEN + RED)

Here, we use ~R550 for GREEN and ~R670 for RED:

VIgreen = (R550 - R670) / (R550 + R670)

Index range: -1.0, 1.0

plantcv.spectral_index.vi_green(hsi, distance=20)

returns calculated index array (instance of the Spectral_data class)

• Parameters:
  • hsi - Hyperspectral image object, an instance of the Spectral_data class in plantcv (read in using pcv.readimage with mode='envi')
  • distance - Amount of flexibility (in nanometers) regarding the bands used to calculate an index.

WI¶

Calculates the Water Index using reflectance values (Penuelas et al., 1997):

WI = R900 / R970

Index range: 0.0, Inf

plantcv.spectral_index.wi(hsi, distance=20)

returns calculated index array (instance of the Spectral_data class)

• Parameters:
  • hsi - Hyperspectral image object, an instance of the Spectral_data class in plantcv (read in using pcv.readimage with mode='envi')
  • distance - Amount of flexibility (in nanometers) regarding the bands used to calculate an index.

Examples¶

from plantcv import plantcv as pcv

# Set global debug behavior to None (default), "print" (to file), 
# or "plot" (Jupyter Notebooks or X11)
pcv.params.debug = "print"

# Extract NDVI index from the datacube 
ndvi_array  = pcv.spectral_index.ndvi(hsi=spectral_data, distance=20)

# Extract GDVI index from the datacube
gdvi_array  = pcv.spectral_index.gdvi(hsi=spectral_data, distance=20)

# Extract SAVI index from the datacube
savi_array  = pcv.spectral_index.savi(hsi=spectral_data, distance=20)

# Extract ARI index from the datacube
ari_array  = pcv.spectral_index.ari(hsi=spectral_data, distance=20)

# Extract CI_REDEDGE index from the datacube 
ci_rededge_array  = pcv.spectral_index.ci_rededge(hsi=spectral_data, distance=20)

# Extract CRI550 index from the datacube 
cri550_array  = pcv.hyperspectral.extract_index.cri550(hsi=spectral_data, distance=20)

# Extract CRI700 index from the datacube 
cri700_array  = pcv.spectral_index.cri700(hsi=spectral_data, distance=20)

# Extract EVI index from the datacube 
evi_array  = pcv.spectral_index.evi(hsi=spectral_data, distance=20)

# Extract MARI index from the datacube 
mari_array  = pcv.spectral_index.mari(hsi=spectral_data, distance=20)

# Extract MCARI index from the datacube 
mcari_array  = pcv.spectral_index.mcari(hsi=spectral_data, distance=20)

# Extract MTCI index from the datacube 
mtci_array  = pcv.spectral_index.mtci(hsi=spectral_data, distance=20)

# Extract NDRE index from the datacube 
ndre_array  = pcv.spectral_index.ndre(hsi=spectral_data, distance=20)

# Extract PSND_CHLA index from the datacube 
psnd_chla_array  = pcv.spectral_index.psnd_chla(hsi=spectral_data, distance=20)

# Extract PSND_CHLB index from the datacube 
psnd_chlb_array  = pcv.spectral_index.psnd_chlb(hsi=spectral_data, distance=20)

# Extract PSND_CAR index from the datacube 
psnd_car_array  = pcv.spectral_index.psnd_car(hsi=spectral_data, distance=20)

# Extract PSRI index from the datacube 
psri_array  = pcv.spectral_index.psri(hsi=spectral_data, distance=20)

# Extract PSSR_CHLA index from the datacube 
pssr_chla_array  = pcv.spectral_index.pssr_chla(hsi=spectral_data, distance=20)

# Extract PSSR_CHLB index from the datacube 
pssr_chlb_array  = pcv.spectral_index.pssr_chlb(hsi=spectral_data, distance=20)

# Extract PSSR_CAR index from the datacube 
pssr_car_array  = pcv.spectral_index.pssr_car(hsi=spectral_data, distance=20)

# Extract RGRI index from the datacube 
rgri_array  = pcv.spectral_index.rgri(hsi=spectral_data, distance=20)

# Extract RVSI index from the datacube 
rvsi_array  = pcv.spectral_index.rvsi(hsi=spectral_data, distance=20)

# Extract SIPI index from the datacube 
sipi_array  = pcv.spectral_index.sipi(hsi=spectral_data, distance=20)

# Extract SR index from the datacube 
sr_array  = pcv.spectral_index.sr(hsi=spectral_data, distance=20)

# Extract VARI index from the datacube 
vari_array  = pcv.spectral_index.vari(hsi=spectral_data, distance=20)

# Extract VI_GREEN index from the datacube 
vi_green_array  = pcv.spectral_index.vi_green(hsi=spectral_data, distance=20)

# Extract WI index from the datacube 
wi_array  = pcv.spectral_index.wi(hsi=spectral_data, distance=20)

egi_array = pcv.spectral_index.egi(rgb_img=img)

NDVI array image

GDVI array image

SAVI array image

ARI array image

NDRE array image

PSND_CHLA array image

PSND_CHLB array image

WI array image

Source Code: Here

References¶

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Blackburn GA. 1998. Quantifying chlorophylls and caroteniods at leaf and canopy scales: An evaluation of some hyperspectral approaches. Remote Sensing of Environment 66:273–285. DOI: 10.1016/S0034-4257(98)00059-5.

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Merzlyak MN, Gitelson AA, Chivkunova OB, Rakitin VYU. 1999. Non-destructive optical detection of pigment changes during leaf senescence and fruit ripening. Physiologia Plantarum 106:135–141. DOI: 10.1034/j.1399-3054.1999.106119.x.

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Penuelas J, Pinol J, Ogaya R, Filella I. 1997. Estimation of plant water concentration by the reflectance Water Index WI (R900/R970). International Journal of Remote Sensing 18:2869–2875. DOI: 10.1080/014311697217396.

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