|
NAMEi.vi - Calculates different types of vegetation indices.Uses red and nir bands mostly, and some indices require additional bands. KEYWORDSimagery, vegetation index, biophysical parameters, NDVISYNOPSISi.vii.vi --help i.vi output=name viname=type [red=name] [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:
Parameters:
DESCRIPTIONi.vi calculates vegetation indices based on biophysical parameters.
Background for users new to remote sensingVegetation 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:
From Radiance to Reflectance:
Vegetation IndicesARVI: Atmospheric Resistant Vegetation IndexARVI 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( redchan, nirchan, bluechan ) ARVI = (nirchan - (2.0*redchan - bluechan)) / ( nirchan + (2.0*redchan - bluechan)) DVI: Difference Vegetation Index
dvi( redchan, nirchan ) DVI = ( nirchan - redchan ) 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( bluechan, redchan, nirchan ) EVI = 2.5 * ( nirchan - redchan ) / ( nirchan + 6.0 * redchan - 7.5 * bluechan + 1.0 ) 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( redchan, nirchan ) EVI2 = 2.5 * ( nirchan - redchan ) / ( nirchan + 2.4 * redchan + 1.0 ) 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( redchan, nirchan, bluechan, greenchan ) GARI = ( nirchan - (greenchan - (bluechan - redchan))) / ( nirchan + (greenchan - (bluechan - redchan))) GEMI: Global Environmental Monitoring Index
gemi( redchan, nirchan ) 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)) GVI: Green Vegetation Index
gvi( bluechan, greenchan, redchan, nirchan, chan5chan, chan7chan) GVI = ( -0.2848 * bluechan - 0.2435 * greenchan - 0.5436 * redchan + 0.7243 * nirchan + 0.0840 * chan5chan- 0.1800 * chan7chan) IPVI: Infrared Percentage Vegetation Index
ipvi( redchan, nirchan ) IPVI = nirchan/(nirchan+redchan) MSAVI2: second Modified Soil Adjusted Vegetation Index
msavi2( redchan, nirchan ) MSAVI2 = (1/2)*(2*NIR+1-sqrt((2*NIR+1)^2-8*(NIR-red))) MSAVI: Modified Soil Adjusted Vegetation Index
msavi( redchan, nirchan ) 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). NDVI: Normalized Difference Vegetation Index
ndvi( redchan, nirchan ) Satellite specific band numbers ([NIR, Red]): MSS Bands = [ 7, 5] TM1-5,7 Bands = [ 4, 3] TM8 Bands = [ 5, 4] Sentinel-2 Bands = [ 8, 4] AVHRR Bands = [ 2, 1] SPOT XS Bands = [ 3, 2] AVIRIS Bands = [51, 29] NDVI = (NIR - Red) / (NIR + Red) NDWI: Normalized Difference Water Index (after McFeeters, 1996) This index is suitable to detect water bodies.
ndwi( greenchan, nirchan ) NDWI = (green - NIR) / (green + NIR) The water content of leaves can be estimated with another NDWI
(after Gao, 1996):
ndwi( greenchan, nirchan ) NDWI = (NIR - SWIR) / (NIR + SWIR)This index is important for monitoring vegetation health (not implemented). PVI: Perpendicular Vegetation Index
pvi( redchan, nirchan ) PVI = sin(a)NIR-cos(a)redfor a isovegetation lines (lines of equal vegetation) would all be parallel to the soil line therefore a=1. SAVI: Soil Adjusted Vegetation Index
savi( redchan, nirchan ) SAVI = ((1.0+0.5)*(nirchan - redchan)) / (nirchan + redchan +0.5) SR: Simple Vegetation ratio
sr( redchan, nirchan ) SR = (nirchan/redchan) 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 = ( bluechan, greenchan, redchan ) VARI = (green - red ) / (green + red - blue) WDVI: Weighted Difference Vegetation Index
wdvi( redchan, nirchan, soil_line_weight ) WDVI = nirchan - a * redchan if(soil_weight_line == None): a = 1.0 #slope of soil line EXAMPLESCalculation of DVIThe calculation of DVI from the reflectance values is done as follows:g.region raster=band.1 -p i.vi blue=band.1 red=band.3 nir=band.4 viname=dvi output=dvi r.univar -e dvi Calculation of EVIThe calculation of EVI from the reflectance values is done as follows:g.region raster=band.1 -p i.vi blue=band.1 red=band.3 nir=band.4 viname=evi output=evi r.univar -e evi Calculation of EVI2The calculation of EVI2 from the reflectance values is done as follows:g.region raster=band.3 -p i.vi red=band.3 nir=band.4 viname=evi2 output=evi2 r.univar -e evi2 Calculation of GARIThe calculation of GARI from the reflectance values is done as follows:g.region raster=band.1 -p i.vi blue=band.1 green=band.2 red=band.3 nir=band.4 viname=gari output=gari r.univar -e gari Calculation of GEMIThe calculation of GEMI from the reflectance values is done as follows:g.region raster=band.3 -p i.vi red=band.3 nir=band.4 viname=gemi output=gemi r.univar -e gemi Calculation of GVIThe calculation of GVI (Green Vegetation Index - Tasseled Cap) from the reflectance values is done as follows:g.region raster=band.3 -p # assuming Landsat-7 i.vi blue=band.1 green=band.2 red=band.3 nir=band.4 band5=band.5 band7=band.7 viname=gvi output=gvi r.univar -e gvi Calculation of IPVIThe calculation of IPVI from the reflectance values is done as follows:g.region raster=band.3 -p i.vi red=band.3 nir=band.4 viname=ipvi output=ipvi r.univar -e ipvi Calculation of MSAVIThe calculation of MSAVI from the reflectance values is done as follows:g.region raster=band.3 -p i.vi red=band.3 nir=band.4 viname=msavi output=msavi r.univar -e msavi Calculation of NDVIThe calculation of NDVI from the reflectance values is done as follows:g.region raster=band.3 -p i.vi red=band.3 nir=band.4 viname=ndvi output=ndvi r.univar -e ndvi Calculation of NDWIThe calculation of NDWI from the reflectance values is done as follows:g.region raster=band.2 -p i.vi green=band.2 nir=band.4 viname=ndwi output=ndwi r.colors ndwi color=byg -n r.univar -e ndwi Calculation of PVIThe calculation of PVI from the reflectance values is done as follows:g.region raster=band.3 -p i.vi red=band.3 nir=band.4 viname=pvi output=pvi r.univar -e pvi Calculation of SAVIThe calculation of SAVI from the reflectance values is done as follows:g.region raster=band.3 -p i.vi red=band.3 nir=band.4 viname=savi output=savi r.univar -e savi Calculation of SRThe calculation of SR from the reflectance values is done as follows:g.region raster=band.3 -p i.vi red=band.3 nir=band.4 viname=sr output=sr r.univar -e sr Calculation of VARIThe calculation of VARI from the reflectance values is done as follows:g.region raster=band.3 -p i.vi blue=band.2 green=band.3 red=band.4 viname=vari output=vari r.univar -e vari Landsat TM7 exampleThe following examples are based on a LANDSAT TM7 scene included in the North Carolina sample dataset.Preparation: DN to reflectanceAs a first step, the original DN (digital number) pixel values must be converted to reflectance using i.landsat.toar. To do so, we make a copy (or rename the channels) to match i.landsat.toar’s input scheme:g.copy raster=lsat7_2002_10,lsat7_2002.1 g.copy raster=lsat7_2002_20,lsat7_2002.2 g.copy raster=lsat7_2002_30,lsat7_2002.3 g.copy raster=lsat7_2002_40,lsat7_2002.4 g.copy raster=lsat7_2002_50,lsat7_2002.5 g.copy raster=lsat7_2002_61,lsat7_2002.61 g.copy raster=lsat7_2002_62,lsat7_2002.62 g.copy raster=lsat7_2002_70,lsat7_2002.7 g.copy raster=lsat7_2002_80,lsat7_2002.8 Calculation of reflectance values from DN using DOS1 (metadata obtained from p016r035_7x20020524.met.gz): i.landsat.toar input=lsat7_2002. output=lsat7_2002_toar. sensor=tm7 \ method=dos1 date=2002-05-24 sun_elevation=64.7730999 \ product_date=2004-02-12 gain=HHHLHLHHLThe resulting Landsat channels are names lsat7_2002_toar.1 .. lsat7_2002_toar.8. Calculation of NDVIThe calculation of NDVI from the reflectance values is done as follows:g.region raster=lsat7_2002_toar.3 -p i.vi red=lsat7_2002_toar.3 nir=lsat7_2002_toar.4 viname=ndvi \ output=lsat7_2002.ndvi r.colors lsat7_2002.ndvi color=ndvi d.mon wx0 d.rast.leg lsat7_2002.ndvi North Carolina dataset: NDVI Calculation of ARVIThe calculation of ARVI from the reflectance values is done as follows:g.region raster=lsat7_2002_toar.3 -p i.vi blue=lsat7_2002_toar.1 red=lsat7_2002_toar.3 nir=lsat7_2002_toar.4 \ viname=arvi output=lsat7_2002.arvi d.mon wx0 d.rast.leg lsat7_2002.arvi North Carolina dataset: ARVI Calculation of GARIThe calculation of GARI from the reflectance values is done as follows:g.region raster=lsat7_2002_toar.3 -p i.vi blue=lsat7_2002_toar.1 green=lsat7_2002_toar.2 red=lsat7_2002_toar.3 \ nir=lsat7_2002_toar.4 viname=gari output=lsat7_2002.gari d.mon wx0 d.rast.leg lsat7_2002.gari North Carolina dataset: GARI NOTESOriginally from kepler.gps.caltech.edu (FAQ):A FAQ on Vegetation in Remote Sensing
Snail Mail: Terrill Ray
SEE ALSOi.albedo, i.aster.toar, i.landsat.toar, i.atcorr, i.tasscapREFERENCESAVHRR, Landsat TM5:
AUTHORSBaburao Kamble, Asian Institute of Technology, ThailandYann Chemin, Asian Institute of Technology, Thailand SOURCE CODEAvailable at: i.vi source code (history)Main index | Imagery index | Topics index | Keywords index | Graphical index | Full index © 2003-2021 GRASS Development Team, GRASS GIS 7.8.6 Reference Manual
Visit the GSP FreeBSD Man Page Interface. |