1i.vi(1) Grass User's Manual i.vi(1)
2
6 i.vi - Calculates different types of vegetation indices.
7 Uses red and nir bands mostly, and some indices require additional
8 bands.
9
11 imagery, vegetation index, biophysical parameters, NDVI
12
14 i.vi
15 i.vi --help
16 i.vi red=name output=name viname=type [nir=name] [green=name]
17 [blue=name] [band5=name] [band7=name] [soil_line_slope=float]
18 [soil_line_intercept=float] [soil_noise_reduction=float] [stor‐
19 age_bit=integer] [--overwrite] [--help] [--verbose] [--quiet]
20 [--ui]
21 Flags:
23 --overwrite
24 Allow output files to overwrite existing files
25 --help
27 Print usage summary
28 --verbose
30 Verbose module output
31 --quiet
33 Quiet module output
34 --ui
36 Force launching GUI dialog
37 Parameters:
39 red=name [required]
40 Name of input red channel surface reflectance map
41 Range: [0.0;1.0]
42 output=name [required]
44 Name for output raster map
45 viname=type [required]
47 Type of vegetation index
48 Options: arvi, dvi, evi, evi2, gvi, gari, gemi, ipvi, msavi,
49 msavi2, ndvi, pvi, savi, sr, vari, wdvi
50 Default: ndvi
51 arvi: Atmospherically Resistant Vegetation Index
52 dvi: Difference Vegetation Index
53 evi: Enhanced Vegetation Index
54 evi2: Enhanced Vegetation Index 2
55 gvi: Green Vegetation Index
56 gari: Green Atmospherically Resistant Vegetation Index
57 gemi: Global Environmental Monitoring Index
58 ipvi: Infrared Percentage Vegetation Index
59 msavi: Modified Soil Adjusted Vegetation Index
60 msavi2: second Modified Soil Adjusted Vegetation Index
61 ndvi: Normalized Difference Vegetation Index
62 pvi: Perpendicular Vegetation Index
63 savi: Soil Adjusted Vegetation Index
64 sr: Simple Ratio
65 vari: Visible Atmospherically Resistant Index
66 wdvi: Weighted Difference Vegetation Index
67 nir=name
69 Name of input nir channel surface reflectance map
70 Range: [0.0;1.0]
71 green=name
73 Name of input green channel surface reflectance map
74 Range: [0.0;1.0]
75 blue=name
77 Name of input blue channel surface reflectance map
78 Range: [0.0;1.0]
79 band5=name
81 Name of input 5th channel surface reflectance map
82 Range: [0.0;1.0]
83 band7=name
85 Name of input 7th channel surface reflectance map
86 Range: [0.0;1.0]
87 soil_line_slope=float
89 Value of the slope of the soil line (MSAVI only)
90 soil_line_intercept=float
92 Value of the intercept of the soil line (MSAVI only)
93 soil_noise_reduction=float
95 Value of the factor of reduction of soil noise (MSAVI only)
96 storage_bit=integer
98 Maximum bits for digital numbers
99 If data is in Digital Numbers (i.e. integer type), give the max
100 bits (i.e. 8 for Landsat -> [0-255])
101 Options: 7, 8, 10, 16
102 Default: 8
103
105 i.vi calculates vegetation indices based on biophysical parameters.
106 · ARVI: atmospherically resistant vegetation indices
108 · DVI: Difference Vegetation Index
110 · EVI: Enhanced Vegetation Index
112 · EVI2: Enhanced Vegetation Index 2
114 · GARI: Green atmospherically resistant vegetation index
116 · GEMI: Global Environmental Monitoring Index
118 · GVI: Green Vegetation Index
120 · IPVI: Infrared Percentage Vegetation Index
122 · MSAVI2: second Modified Soil Adjusted Vegetation Index
124 · MSAVI: Modified Soil Adjusted Vegetation Index
126 · NDVI: Normalized Difference Vegetation Index
128 · PVI: Perpendicular Vegetation Index
130 · RVI: ratio vegetation index
132 · SAVI: Soil Adjusted Vegetation Index
134 · SR: Simple Vegetation ratio
136 · WDVI: Weighted Difference Vegetation Index
138 Background for users new to remote sensing
140 Vegetation Indices are often considered the entry point of remote sens‐
141 ing for Earth land monitoring. They are suffering from their success,
142 in terms that often people tend to harvest satellite images from online
143 sources and use them directly in this module.
144 From Digital number to Radiance:
146 Satellite imagery is commonly stored in Digital Number (DN) for storage
147 purposes; e.g., Landsat5 data is stored in 8bit values (ranging from 0
148 to 255), other satellites maybe stored in 10 or 16 bits. If the data is
149 provided in DN, this implies that this imagery is "uncorrected". What
150 this means is that the image is what the satellite sees at its position
151 and altitude in space (stored in DN). This is not the signal at ground
152 yet. We call this data at-satellite or at-sensor. Encoded in the 8bits
153 (or more) is the amount of energy sensed by the sensor inside the
154 satellite platform. This energy is called radiance-at-sensor. Gener‐
155 ally, satellites image providers encode the radiance-at-sensor into
156 8bit (or more) through an affine transform equation (y=ax+b). In case
157 of using Landsat imagery, look at the i.landsat.toar for an easy way to
158 transform DN to radiance-at-sensor. If using Aster data, try the
159 i.aster.toar module.
160 From Radiance to Reflectance:
162 Finally, once having obtained the radiance at sensor values, still the
163 atmosphere is between sensor and Earth’s surface. This fact needs to be
164 corrected to account for the atmospheric interaction with the sun
165 energy that the vegetation reflects back into space. This can be done
166 in two ways for Landsat. The simple way is through i.landsat.toar, use
167 e.g. the DOS correction. The more accurate way is by using i.atcorr
168 (which works for many satellite sensors). Once the atmospheric correc‐
169 tion has been applied to the satellite data, data vales are called sur‐
170 face reflectance. Surface reflectance is ranging from 0.0 to 1.0 theo‐
171 retically (and absolutely). This level of data correction is the proper
172 level of correction to use with i.vi.
173 Vegetation Indices
175 ARVI: Atmospheric Resistant Vegetation Index
176 ARVI is resistant to atmospheric effects (in comparison to the NDVI)
178 and is accomplished by a self correcting process for the atmospheric
179 effect in the red channel, using the difference in the radiance between
180 the blue and the red channels (Kaufman and Tanre 1996).
181 arvi( redchan, nirchan, bluechan )
182 ARVI = (nirchan - (2.0*redchan - bluechan)) /
183 ( nirchan + (2.0*redchan - bluechan))
184 DVI: Difference Vegetation Index
186 dvi( redchan, nirchan )
187 DVI = ( nirchan - redchan )
188 EVI: Enhanced Vegetation Index
190 The enhanced vegetation index (EVI) is an optimized index designed to
192 enhance the vegetation signal with improved sensitivity in high biomass
193 regions and improved vegetation monitoring through a de-coupling of the
194 canopy background signal and a reduction in atmosphere influences
195 (Huete A.R., Liu H.Q., Batchily K., van Leeuwen W. (1997). A comparison
196 of vegetation indices global set of TM images for EOS-MODIS. Remote
197 Sensing of Environment, 59:440-451).
198 evi( bluechan, redchan, nirchan )
199 EVI = 2.5 * ( nirchan - redchan ) /
200 ( nirchan + 6.0 * redchan - 7.5 * bluechan + 1.0 )
201 EVI2: Enhanced Vegetation Index 2
203 A 2-band EVI (EVI2), without a blue band, which has the best similarity
205 with the 3-band EVI, particularly when atmospheric effects are
206 insignificant and data quality is good (Zhangyan Jiang ; Alfredo R.
207 Huete ; Youngwook Kim and Kamel Didan 2-band enhanced vegetation index
208 without a blue band and its application to AVHRR data. Proc. SPIE 6679,
209 Remote Sensing and Modeling of Ecosystems for Sustainability IV, 667905
210 (october 09, 2007) doi:10.1117/12.734933).
211 evi2( redchan, nirchan )
212 EVI2 = 2.5 * ( nirchan - redchan ) /
213 ( nirchan + 2.4 * redchan + 1.0 )
214 GARI: green atmospherically resistant vegetation index
216 The formula was actually defined: Gitelson, Anatoly A.; Kaufman, Yoram
218 J.; Merzlyak, Mark N. (1996) Use of a green channel in remote sensing
219 of global vegetation from EOS- MODIS, Remote Sensing of Environment 58
220 (3), 289-298. doi:10.1016/s0034-4257(96)00072-7
221 gari( redchan, nirchan, bluechan, greenchan )
222 GARI = ( nirchan - (greenchan - (bluechan - redchan))) /
223 ( nirchan + (greenchan - (bluechan - redchan)))
224 GEMI: Global Environmental Monitoring Index
226 gemi( redchan, nirchan )
227 GEMI = (( (2*((nirchan * nirchan)-(redchan * redchan)) +
228 1.5*nirchan+0.5*redchan) / (nirchan + redchan + 0.5)) *
229 (1 - 0.25 * (2*((nirchan * nirchan)-(redchan * redchan)) +
230 1.5*nirchan+0.5*redchan) / (nirchan + redchan + 0.5))) -
231 ( (redchan - 0.125) / (1 - redchan))
232 GVI: Green Vegetation Index
234 gvi( bluechan, greenchan, redchan, nirchan, chan5chan, chan7chan)
235 GVI = ( -0.2848 * bluechan - 0.2435 * greenchan -
236 0.5436 * redchan + 0.7243 * nirchan + 0.0840 * chan5chan-
237 0.1800 * chan7chan)
238 IPVI: Infrared Percentage Vegetation Index
240 ipvi( redchan, nirchan )
241 IPVI = nirchan/(nirchan+redchan)
242 MSAVI2: second Modified Soil Adjusted Vegetation Index
244 msavi2( redchan, nirchan )
245 MSAVI2 = (1/2)*(2*NIR+1-sqrt((2*NIR+1)^2-8*(NIR-red)))
246 MSAVI: Modified Soil Adjusted Vegetation Index
248 msavi( redchan, nirchan )
249 MSAVI = s(NIR-s*red-a) / (a*NIR+red-a*s+X*(1+s*s))
250 where a is the soil line intercept, s is the soil line slope, and X
251 is an adjustment factor which is set to minimize soil noise (0.08 in
252 original papers).
253 NDVI: Normalized Difference Vegetation Index
255 ndvi( redchan, nirchan )
256 Satellite specific band numbers ([NIR, Red]):
257 MSS Bands = [ 7, 5]
258 TM1-5,7 Bands = [ 4, 3]
259 TM8 Bands = [ 5, 4]
260 Sentinel-2 Bands = [ 8, 4]
261 AVHRR Bands = [ 2, 1]
262 SPOT XS Bands = [ 3, 2]
263 AVIRIS Bands = [51, 29]
264 NDVI = (NIR - Red) / (NIR + Red)
265 PVI: Perpendicular Vegetation Index
267 pvi( redchan, nirchan )
268 PVI = sin(a)NIR-cos(a)red
269 for a isovegetation lines (lines of equal vegetation) would all be par‐
270 allel to the soil line therefore a=1.
271 SAVI: Soil Adjusted Vegetation Index
273 savi( redchan, nirchan )
274 SAVI = ((1.0+0.5)*(nirchan - redchan)) / (nirchan + redchan +0.5)
275 SR: Simple Vegetation ratio
277 sr( redchan, nirchan )
278 SR = (nirchan/redchan)
279 VARI: Visible Atmospherically Resistant Index VARI was designed to
281 introduce an atmospheric self-correction (Gitelson A.A., Kaufman Y.J.,
282 Stark R., Rundquist D., 2002. Novel algorithms for estimation of vege‐
283 tation fraction Remote Sensing of Environment (80), pp76-87.)
284 vari = ( bluechan, greenchan, redchan )
285 VARI = (green - red ) / (green + red - blue)
286 WDVI: Weighted Difference Vegetation Index
288 wdvi( redchan, nirchan, soil_line_weight )
289 WDVI = nirchan - a * redchan
290 if(soil_weight_line == None):
291 a = 1.0 #slope of soil line
292
294 Calculation of DVI
295 The calculation of DVI from the reflectance values is done as follows:
296 g.region raster=band.1 -p
297 i.vi blue=band.1 red=band.3 nir=band.4 viname=dvi output=dvi
298 r.univar -e dvi
299 Calculation of EVI
301 The calculation of EVI from the reflectance values is done as follows:
302 g.region raster=band.1 -p
303 i.vi blue=band.1 red=band.3 nir=band.4 viname=evi output=evi
304 r.univar -e evi
305 Calculation of EVI2
307 The calculation of EVI2 from the reflectance values is done as follows:
308 g.region raster=band.3 -p
309 i.vi red=band.3 nir=band.4 viname=evi2 output=evi2
310 r.univar -e evi2
311 Calculation of GARI
313 The calculation of GARI from the reflectance values is done as follows:
314 g.region raster=band.1 -p
315 i.vi blue=band.1 green=band.2 red=band.3 nir=band.4 viname=gari output=gari
316 r.univar -e gari
317 Calculation of GEMI
319 The calculation of GEMI from the reflectance values is done as follows:
320 g.region raster=band.3 -p
321 i.vi red=band.3 nir=band.4 viname=gemi output=gemi
322 r.univar -e gemi
323 Calculation of GVI
325 The calculation of GVI from the reflectance values is done as follows:
326 g.region raster=band.3 -p
327 i.vi blue=band.1 green=band.2 red=band.3 nir=band.4 band5=band.5 band7=band.7 viname=gvi output=gvi
328 r.univar -e gvi
329 Calculation of IPVI
331 The calculation of IPVI from the reflectance values is done as follows:
332 g.region raster=band.3 -p
333 i.vi red=band.3 nir=band.4 viname=ipvi output=ipvi
334 r.univar -e ipvi
335 Calculation of MSAVI
337 The calculation of MSAVI from the reflectance values is done as fol‐
338 lows:
339 g.region raster=band.3 -p
340 i.vi red=band.3 nir=band.4 viname=msavi output=msavi
341 r.univar -e msavi
342 Calculation of NDVI
344 The calculation of NDVI from the reflectance values is done as follows:
345 g.region raster=band.3 -p
346 i.vi red=band.3 nir=band.4 viname=ndvi output=ndvi
347 r.univar -e ndvi
348 Calculation of PVI
350 The calculation of PVI from the reflectance values is done as follows:
351 g.region raster=band.3 -p
352 i.vi red=band.3 nir=band.4 viname=pvi output=pvi
353 r.univar -e pvi
354 Calculation of SAVI
356 The calculation of SAVI from the reflectance values is done as follows:
357 g.region raster=band.3 -p
358 i.vi red=band.3 nir=band.4 viname=savi output=savi
359 r.univar -e savi
360 Calculation of SR
362 The calculation of SR from the reflectance values is done as follows:
363 g.region raster=band.3 -p
364 i.vi red=band.3 nir=band.4 viname=sr output=sr
365 r.univar -e sr
366 Calculation of VARI
368 The calculation of VARI from the reflectance values is done as follows:
369 g.region raster=band.3 -p
370 i.vi blue=band.2 green=band.3 red=band.4 viname=vari output=vari
371 r.univar -e vari
372 Landsat TM7 example
374 The following examples are based on a LANDSAT TM7 scene included in the
375 North Carolina sample dataset.
376 Preparation: DN to reflectance
378 As a first step, the original DN (digital number) pixel values must be
379 converted to reflectance using i.landsat.toar. To do so, we make a copy
380 (or rename the channels) to match i.landsat.toar’s input scheme:
381 g.copy raster=lsat7_2002_10,lsat7_2002.1
383 g.copy raster=lsat7_2002_20,lsat7_2002.2
384 g.copy raster=lsat7_2002_30,lsat7_2002.3
385 g.copy raster=lsat7_2002_40,lsat7_2002.4
386 g.copy raster=lsat7_2002_50,lsat7_2002.5
387 g.copy raster=lsat7_2002_61,lsat7_2002.61
388 g.copy raster=lsat7_2002_62,lsat7_2002.62
389 g.copy raster=lsat7_2002_70,lsat7_2002.7
390 g.copy raster=lsat7_2002_80,lsat7_2002.8
391 Calculation of reflectance values from DN using DOS1 (metadata obtained
393 from p016r035_7x20020524.met.gz):
394 i.landsat.toar input=lsat7_2002. output=lsat7_2002_toar. sensor=tm7 \
396 method=dos1 date=2002-05-24 sun_elevation=64.7730999 \
397 product_date=2004-02-12 gain=HHHLHLHHL
398 The resulting Landsat channels are names lsat7_2002_toar.1 ..
399 lsat7_2002_toar.8.
400 Calculation of NDVI
402 The calculation of NDVI from the reflectance values is done as follows:
403 g.region raster=lsat7_2002_toar.3 -p
404 i.vi red=lsat7_2002_toar.3 nir=lsat7_2002_toar.4 viname=ndvi \
405 output=lsat7_2002.ndvi
406 r.colors lsat7_2002.ndvi color=ndvi
407 d.mon wx0
408 d.rast.leg lsat7_2002.ndvi
409 North Carolina dataset: NDVI
410 Calculation of ARVI
412 The calculation of ARVI from the reflectance values is done as follows:
413 g.region raster=lsat7_2002_toar.3 -p
414 i.vi blue=lsat7_2002_toar.1 red=lsat7_2002_toar.3 nir=lsat7_2002_toar.4 \
415 viname=arvi output=lsat7_2002.arvi
416 d.mon wx0
417 d.rast.leg lsat7_2002.arvi
418 North Carolina dataset: ARVI
419 Calculation of GARI
421 The calculation of GARI from the reflectance values is done as follows:
422 g.region raster=lsat7_2002_toar.3 -p
423 i.vi blue=lsat7_2002_toar.1 green=lsat7_2002_toar.2 red=lsat7_2002_toar.3 \
424 nir=lsat7_2002_toar.4 viname=gari output=lsat7_2002.gari
425 d.mon wx0
426 d.rast.leg lsat7_2002.gari
427 North Carolina dataset: GARI
428
430 Originally from kepler.gps.caltech.edu (FAQ):
431 A FAQ on Vegetation in Remote Sensing
433 Written by Terrill W. Ray, Div. of Geological and Planetary Sciences,
434 California Institute of Technology, email: terrill@mars1.gps.cal‐
435 tech.edu
436 Snail Mail: Terrill Ray
438 Division of Geological and Planetary Sciences
439 Caltech, Mail Code 170-25
440 Pasadena, CA 91125
441
443 i.albedo, i.aster.toar, i.landsat.toar, i.atcorr, i.tasscap
444
446 AVHRR, Landsat TM5:
447 · Bastiaanssen, W.G.M., 1995. Regionalization of surface flux
449 densities and moisture indicators in composite terrain; a
450 remote sensing approach under clear skies in mediterranean cli‐
451 mates. PhD thesis, Wageningen Agricultural Univ., The Nether‐
452 land, 271 pp. (PDF)
453 · Index DataBase: List of available Indices
455
457 Baburao Kamble, Asian Institute of Technology, Thailand
458 Yann Chemin, Asian Institute of Technology, Thailand
459 Last changed: $Date: 2018-03-24 12:22:48 +0100 (Sat, 24 Mar 2018) $
461
463 Available at: i.vi source code (history)
464 Main index | Imagery index | Topics index | Keywords index | Graphical
466 index | Full index
467 © 2003-2019 GRASS Development Team, GRASS GIS 7.6.0 Reference Manual
469GRASS 7.6.0 i.vi(1)