## 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

Warning to the new remote sensing users

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. If you are in this situation please read the following

Satellite imagery is often stored in Digital Number (DN) for storage purpose, Landsat is stored in 8bit values (ranging from 0 to 255), other satellites maybe stored in 10 or 16 bits. Get to know about your satellite data. Once you covered this knowledge and that you are sure the data is in DN, this implies that your imagery is not corrected. What this means is that the image is what the satellite sees at its position and altitude in space. This is not the ground reality yet. We call this data at the satellite. 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). If you are using Landsat imagery, look at the i.landsat.toar for an easy way to transform DN to radiance-at-sensor. If you are using Aster data, try i.aster.toar module.

Finally, once you have the radiance at sensor, you still have the atmosphere between the sensor and the surface vagetation. You need to correct 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 within i.landsat.toar, look for DOS correction. The more accurate way is by using i.atcorr (which works for many satellite sensors). Get to know this last one if you intend to stay around remote sensing some time. Once you have completed the use of an atmospheric correction on the energy sensed by the satellite, you can call your data by the name of 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 this Vegetation Index module.

    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., vanLeeuwen 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

    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))
    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).
    msavi( redchan, nirchan )

    NDVI: Normalized Difference Vegetation Index

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

    PVI: Perpendicular Vegetation Index

    PVI = sin(a)NIR-cos(a)red
    for a isovegetation lines (lines of equal vegetation)
    would all be parallel to the soil line therefore a=1
    pvi( redchan, nirchan )

    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 = (green - red ) / (green + red - blue)
    it 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.

    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 )

## NOTES

Originally from kepler.gps.caltech.edu

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

## AUTHORS

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

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