i.vi(1)

NAME
i.vi - Calculates different types of vegetation indices.
Uses red and nir bands mostly, and some indices require additional bands.

KEYWORDS
imagery, vegetation index, biophysical parameters

SYNOPSIS
i.vi
i.vi --help
i.vi red=name output=name viname=type [nir=name] [green=name] [blue=name] [band5=name] [band7=name] [soil_line_slope=float] [soil_line_intercept=float] [soil_noise_reduction=float] [storage_bit=integer] [--overwrite] [--help] [--verbose] [--quiet] [--ui]

  Flags:

--overwrite
    Allow output files to overwrite existing files

--help
    Print usage summary

--verbose
    Verbose module output

--quiet
    Quiet module output

--ui
    Force launching GUI dialog

  Parameters:

red=name [required]
    Name of input red channel surface reflectance map
    Range: [0.0;1.0]

output=name [required]
    Name for output raster map

viname=type [required]
    Type of vegetation index
    Options: arvi, dvi, evi, evi2, gvi, gari, gemi, ipvi, msavi, msavi2, ndvi, pvi, savi, sr, vari, wdvi
    Default: ndvi
    arvi: Atmospherically Resistant Vegetation Indices
    dvi: Difference Vegetation Index
    evi: Enhanced Vegetation Index
    evi2: Enhanced Vegetation Index 2
    gvi: Green Vegetation Index
    gari: Green Atmospherically Resistant Vegetation Index
    gemi: Global Environmental Monitoring Index
    ipvi: Infrared Percentage Vegetation Index
    msavi: Modified Soil Adjusted Vegetation Index
    msavi2: second Modified Soil Adjusted Vegetation Index
    ndvi: Normalized Difference Vegetation Index
    pvi: Perpendicular Vegetation Index
    savi: Soil Adjusted Vegetation Index
    sr: Simple Ratio
    vari: Visible Atmospherically Resistant Index
    wdvi: Weighted Difference Vegetation Index

nir=name
    Name of input nir channel surface reflectance map
    Range: [0.0;1.0]

green=name
    Name of input green channel surface reflectance map
    Range: [0.0;1.0]

blue=name
    Name of input blue channel surface reflectance map
    Range: [0.0;1.0]

band5=name
    Name of input 5th channel surface reflectance map
    Range: [0.0;1.0]

band7=name
    Name of input 7th channel surface reflectance map
    Range: [0.0;1.0]

soil_line_slope=float
    Value of the slope of the soil line (MSAVI2 only)

soil_line_intercept=float
    Value of the intercept of the soil line (MSAVI2 only)

soil_noise_reduction=float
    Value of the factor of reduction of soil noise (MSAVI2 only)

storage_bit=integer
    Maximum bits for digital numbers
    If data is in Digital Numbers (i.e. integer type), give the max bits (i.e. 8 for Landsat -> [0-255])
    Options: 7, 8, 10, 16
    Default: 8

DESCRIPTION
i.vi calculates vegetation indices based on biophysical parameters.

    •   ARVI: atmospherically resistant vegetation indices

    •   DVI: Difference Vegetation Index

    •   EVI: Enhanced Vegetation Index

    •   EVI2: Enhanced Vegetation Index 2

    •   GARI: Green atmospherically resistant vegetation index

    •   GEMI: Global Environmental Monitoring Index

    •   GVI: Green Vegetation Index

    •   IPVI: Infrared Percentage Vegetation Index

    •   MSAVI2: second Modified Soil Adjusted Vegetation Index

    •   MSAVI: Modified Soil Adjusted Vegetation Index

    •   NDVI: Normalized Difference Vegetation Index

    •   PVI: Perpendicular Vegetation Index

    •   RVI: ratio vegetation index

    •   SAVI: Soil Adjusted Vegetation Index

    •   SR: Simple Vegetation ratio

    •   WDVI: Weighted Difference Vegetation Index

  Background for users new to remote sensing
Vegetation Indices are often considered the entry point of remote sensing for Earth land monitoring. They are suffering from their success, in terms that often people tend to harvest satellite images from online sources and use them directly in this module.

From Digital number to Radiance:
Satellite imagery is commonly stored in Digital Number (DN) for storage purposes; e.g., Landsat5 data is stored in 8bit values (ranging from 0 to 255), other satellites maybe stored in 10 or 16 bits. If the data is provided in DN, this implies that this imagery is "uncorrected". What this means is that the image is what the satellite sees at its position and altitude in space (stored in DN). This is not the signal at ground yet. We call this data at-satellite or at-sensor. Encoded in the 8bits (or more) is the amount of energy sensed by the sensor inside the satellite platform. This energy is called radiance-at-sensor. Generally, satellites image providers encode the radiance-at-sensor into 8bit (or more) through an affine transform equation (y=ax+b). In case of using Landsat imagery, look at the i.landsat.toar for an easy way to transform DN to radiance-at-sensor. If using Aster data, try the i.aster.toar module.

From Radiance to Reflectance:
Finally, once having obtained the radiance at sensor values, still the atmosphere is between sensor and Earth’s surface. This fact needs to be corrected to account for the atmospheric interaction with the sun energy that the vegetation reflects back into space. This can be done in two ways for Landsat. The simple way is through i.landsat.toar, use e.g. the DOS correction. The more accurate way is by using i.atcorr (which works for many satellite sensors). Once the atmospheric correction has been applied to the satellite data, data vales are called surface reflectance. Surface reflectance is ranging from 0.0 to 1.0 theoretically (and absolutely). This level of data correction is the proper level of correction to use with i.vi.

  Vegetation Indices
ARVI: Atmospheric Resistant Vegetation Index

ARVI is resistant to atmospheric effects (in comparison to the NDVI) and is accomplished by a self correcting process for the atmospheric effect in the red channel, using the difference in the radiance between the blue and the red channels (Kaufman and Tanre 1996).

ARVI = (nirchan - (2.0*redchan - bluechan)) /
    ( nirchan + (2.0*redchan - bluechan))
arvi( redchan, nirchan, bluechan )

DVI: Difference Vegetation Index

DVI = ( nirchan - redchan )
dvi( redchan, nirchan )

EVI: Enhanced Vegetation Index

The enhanced vegetation index (EVI) is an optimized index designed to enhance the vegetation signal with improved sensitivity in high biomass regions and improved vegetation monitoring through a de-coupling of the canopy background signal and a reduction in atmosphere influences (Huete A.R., Liu H.Q., Batchily K., van Leeuwen W. (1997). A comparison of vegetation indices global set of TM images for EOS-MODIS. Remote Sensing of Environment, 59:440-451).

EVI = 2.5 * ( nirchan - redchan ) /
    ( nirchan + 6.0 * redchan - 7.5 * bluechan + 1.0 )
evi( bluechan, redchan, nirchan )

EVI2: Enhanced Vegetation Index 2

A 2-band EVI (EVI2), without a blue band, which has the best similarity with the 3-band EVI, particularly when atmospheric effects are insignificant and data quality is good (Zhangyan Jiang ; Alfredo R. Huete ; Youngwook Kim and Kamel Didan 2-band enhanced vegetation index without a blue band and its application to AVHRR data. Proc. SPIE 6679, Remote Sensing and Modeling of Ecosystems for Sustainability IV, 667905 (october 09, 2007) doi:10.1117/12.734933).

EVI2 = 2.5 * ( nirchan - redchan ) /
    ( nirchan + 2.4 * redchan + 1.0 )
evi2( redchan, nirchan )

GARI: green atmospherically resistant vegetation index

The formula was actually defined: Gitelson, Anatoly A.; Kaufman, Yoram J.; Merzlyak, Mark N. (1996) Use of a green channel in remote sensing of global vegetation from EOS- MODIS, Remote Sensing of Environment 58 (3), 289-298. doi:10.1016/s0034-4257(96)00072-7

GARI = ( nirchan - (greenchan - (bluechan - redchan))) /
( nirchan + (greenchan - (bluechan - redchan)))
gari( redchan, nirchan, bluechan, greenchan )

GEMI: Global Environmental Monitoring Index

GEMI = (( (2*((nirchan * nirchan)-(redchan * redchan))+
1.5*nirchan+0.5*redchan) / (nirchan + redchan + 0.5)) *
(1 - 0.25 * (2*((nirchan * nirchan)-(redchan * redchan))
+1.5*nirchan+0.5*redchan) /(nirchan + redchan + 0.5)))-
( (redchan - 0.125) / (1 - redchan))
gemi( redchan, nirchan )

GVI: Green Vegetation Index

GVI = ( -0.2848 * bluechan - 0.2435 * greenchan -
0.5436 * redchan + 0.7243 * nirchan + 0.0840 * chan5chan-
0.1800 * chan7chan)
gvi( bluechan, greenchan, redchan, nirchan, chan5chan, chan7chan)

IPVI: Infrared Percentage Vegetation Index

IPVI = nirchan/(nirchan+redchan)
ipvi( redchan, nirchan )

MSAVI2: second Modified Soil Adjusted Vegetation Index

MSAVI2 = (1/2)*(2(NIR+1)-sqrt((2*NIR+1)^2-8(NIR-red)))
msavi2( redchan, nirchan )

MSAVI: Modified Soil Adjusted Vegetation Index

MSAVI = s(NIR-s*red-a) / (a*NIR+red-a*s+X*(1+s*s))
msavi( redchan, nirchan )

where a is the soil line intercept, s is the
soil line slope, and X     is an adjustment factor
which is set to minimize soil noise (0.08 in original papers).

NDVI: Normalized Difference Vegetation Index

Data Type Band Numbers ([NIR, Red])
MSS Bands = [7, 5]
TM1-5,7 Bands= [4,3]
TM8 Bands= [5,4]
AVHRR Bands = [2, 1]
SPOT XS Bands = [3, 2]
AVIRIS Bands = [51, 29]
NDVI = (NIR - Red) / (NIR + Red)

PVI: Perpendicular Vegetation Index

PVI = sin(a)NIR-cos(a)red
pvi( redchan, nirchan )

for a isovegetation lines (lines of equal vegetation) would all be parallel to the soil line therefore a=1.

SAVI: Soil Adjusted Vegetation Index

SAVI = ((1.0+0.5)*(nirchan - redchan)) / (nirchan + redchan +0.5)
savi( redchan, nirchan )

SR: Simple Vegetation ratio

SR = (nirchan/redchan)
sr( redchan, nirchan )

VARI: Visible Atmospherically Resistant Index VARI was designed to introduce an atmospheric self-correction (Gitelson A.A., Kaufman Y.J., Stark R., Rundquist D., 2002. Novel algorithms for estimation of vegetation fraction Remote Sensing of Environment (80), pp76-87.)

VARI = (green - red ) / (green + red - blue)

WDVI: Weighted Difference Vegetation Index

WDVI = nirchan - a * redchan
if(soil_weight_line == None):
   a = 1.0 #slope of soil line
wdvi( redchan, nirchan, soil_line_weight )

EXAMPLE
This example uses a LANDSAT TM5 scene included in the North Carolina sample dataset.

g.region raster=lsat5_1987_30 -p
i.vi red=lsat5_1987_30 viname=ndvi output=lsat5_1987.ndvi nir=lsat5_1987_40
r.colors lsat5_1987.ndvi color=ndvi

NOTES
Originally from kepler.gps.caltech.edu (FAQ):

A FAQ on Vegetation in Remote Sensing
Written by Terrill W. Ray, Div. of Geological and Planetary Sciences, California Institute of Technology, email: terrill@mars1.gps.caltech.edu

Snail Mail: Terrill Ray
Division of Geological and Planetary Sciences
Caltech, Mail Code 170-25
Pasadena, CA 91125

SEE ALSO
i.albedo, i.aster.toar, i.landsat.toar, i.atcorr, i.tasscap

REFERENCES
AVHRR, Landsat TM5:

    •   Bastiaanssen, W.G.M., 1995. Regionalization of surface flux densities and moisture indicators in composite terrain; a remote sensing approach under clear skies in mediterranean climates. PhD thesis, Wageningen Agricultural Univ., The Netherland, 271 pp. (PDF)

    •   Index DataBase: List of available Indices

AUTHORS
Baburao Kamble, Asian Institute of Technology, Thailand
Yann Chemin, Asian Institute of Technology, Thailand

Last changed: $Date: 2014-12-19 22:55:37 +0100 (pÃ¡, 19 12 2014) $

Main index | Imagery index | Topics index | Keywords index | Full index

© 2003-2015 GRASS Development Team, GRASS GIS 7.0.1 Reference Manual