Index: Simple Ratio NIR/RED Difference Vegetation Index, Vegetation Index Number (VIN)

Simple Ratio NIR/RED Difference Vegetation Index, Vegetation Index Number (VIN)

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Basic information

Name	Simple Ratio NIR/RED Difference Vegetation Index, Vegetation Index Number (VIN)
Abbreviation	DVI
Formula	$\frac{\mathrm{NIR}}{\mathrm{RED}}$
Variables
Expl. of Variables
Wavelengths	640:760,780:1400
Source	Original formula
Description	Jordan 1969

Visualisation of required spectral range

Sensors

Nr.	Name	Spectral Range	Bands	Specific Formula	Calculated	Comment
1	AHS	428.5-13140	80	$\frac{\mathrm{20}}{\mathrm{10}}$	Automatic
2	AISA	400-2506.7	498	$\frac{\mathrm{264}}{\mathrm{131}}$	Automatic
3	ALI	433-2350	10	$\frac{\mathrm{MS\_\_\_5\text{'}}}{\mathrm{MS\_\_\_3}}$	Automatic
4	ALOS	0-890	6	$\frac{5}{4}$	Automatic
5	ARIES-1	400-2587	105	$\frac{\mathrm{36}}{\mathrm{16}}$	Automatic
6	ASAS	400-1020	62	$\frac{\mathrm{62}}{\mathrm{30}}$	Automatic
7	ASTER	520-11650	15	$\frac{\mathrm{VNIR\_Band3N}}{\mathrm{VNIR\_Band2}}$	Automatic
8	AVHRR	580-12500	6	$\frac{2}{1}$	Automatic
9	AVIRIS	355.15-2515	224	$\frac{\mathrm{78}}{\mathrm{37}}$	Automatic
10	AVIS	550-994	74	$\frac{\mathrm{74}}{\mathrm{25}}$	Automatic
11	AVNIR	400-920	5	$\frac{5}{4}$	Automatic
12	Azimuth Systems AZ-16	0-13000	12	$\frac{8}{6}$	Automatic
13	CASI 550	400-1000	288	$\frac{\mathrm{288}}{\mathrm{144}}$	Automatic
14	CASI EG	474.7-789.5	13	$\frac{\mathrm{13}}{6}$	Manual
15	CASI spectral	391-905.5	96	$\frac{\mathrm{96}}{\mathrm{58}}$	Automatic
16	CASI-2 Vegetation	441.53-869.54	12	$\frac{\mathrm{12}}{5}$	Automatic
17	CASI1500	380-1500	288	$\frac{\mathrm{183}}{\mathrm{83}}$	Automatic
18	CASI_spatial	417-806	11	$\frac{\mathrm{11}}{8}$	Automatic
19	CBERS-1/CBERS-2	450-890	8	$\frac{\mathrm{infrared}}{\mathrm{red}}$	Automatic
20	ChrisProbaM1	406-1003	62	$\frac{\mathrm{A62}}{\mathrm{A29}}$	Automatic
21	ChrisProbaM2	406-1036	18	$\frac{\mathrm{W18}}{\mathrm{W14}}$	Automatic
22	ChrisProbaM3	438-1035	18	$\frac{\mathrm{L18}}{\mathrm{L9}}$	Automatic
23	ChrisProbaM3A	420-910	18	$\frac{\mathrm{L18}}{\mathrm{L10}}$	Automatic
24	ChrisProbaM4	486-796	18	$\frac{\mathrm{C18}}{\mathrm{C8}}$	Automatic
25	ChrisProbaM5	438-1036	37	$\frac{\mathrm{H37}}{\mathrm{H10}}$	Automatic
26	Daedalus	0-13000	12	$\frac{8}{6}$	Automatic
27	DAIS-7915	400-12600	79	$\frac{\mathrm{32}}{\mathrm{16}}$	Automatic
28	Deimos-2	420-890	5	$\frac{\mathrm{MS4}}{\mathrm{MS3}}$	Automatic
29	DubaiSat-1	420-890	5	$\frac{\mathrm{MS4\_Near\_Infrared}}{\mathrm{MS3\_Red}}$	Automatic
30	Early Bird	450-890	4	$\frac{4}{3}$	Automatic
31	EnMap	420-2450	244	$\frac{\mathrm{108}}{\mathrm{44}}$	Automatic
32	Formosat-2	450-900	5	$\frac{\mathrm{B4}}{\mathrm{B3}}$	Automatic
33	GeoEye-1	450-920	5	$\frac{\mathrm{NIR1}}{\mathrm{Red}}$	Automatic
34	GLI	375-12500	36	$\frac{\mathrm{24}}{\mathrm{14}}$	Automatic
35	GOMOS	250-952	5	$\frac{\mathrm{NIR2}}{\mathrm{Red\_phonometer}}$	Automatic
36	HRSC-A	395-1015	5	$\frac{\mathrm{Infrared}}{\mathrm{Red}}$	Automatic
37	HYDICE	400-2500	210	$\frac{\mathrm{69}}{\mathrm{30}}$	Automatic
38	HyMap	429-2493.8	126	$\frac{\mathrm{44}}{\mathrm{18}}$	Automatic
39	Hyperion	349.896-2582.28	242	$\frac{\mathrm{B95}}{\mathrm{B35}}$	Automatic
40	IKONOS-2	445-900	5	$\frac{\mathrm{nahe\_Infrarot}}{\mathrm{Rot}}$	Automatic
41	INSAT-2E	550-12500	6	$\frac{\mathrm{CCD\_Near\_Infrared}}{\mathrm{VHRR\_Visible}}$	Automatic
42	IRS-1A	450-860	4	$\frac{4}{3}$	Automatic
43	IRS-1B	450-860	4	$\frac{4}{3}$	Automatic
44	IRS-1C	500-1700	5	$\frac{\mathrm{NIR}}{\mathrm{Red}}$	Automatic
45	IRS-1D	500-1700	5	$\frac{\mathrm{NIR}}{\mathrm{Red}}$	Automatic
46	IRS-P2	450-860	4	$\frac{4}{3}$	Automatic
47	IRS-P3	403-1650	18	$\frac{\mathrm{MOS\_B11}}{\mathrm{MOS\_B8}}$	Automatic
48	IRS-P4	402-1700	9	$\frac{8}{6}$	Automatic
49	Kompsat-2	0-900	5	$\frac{5}{4}$	Automatic
50	Landsat 8	435-12510	11	$\frac{\mathrm{Near\_Infrared}}{\mathrm{Red}}$	Automatic
51	LandsatETM+ (Landsat7)	450-12500	8	$\frac{\mathrm{NIR}}{\mathrm{Red}}$	Automatic
52	LandsatMSS (Landsat1-3)	500-1100	4	$\frac{4}{2}$	Automatic
53	LandsatTM (Landsat4,5)	450-12500	7	$\frac{\mathrm{NIR}}{\mathrm{Red}}$	Automatic
54	MERIS	407.5-905	15	$\frac{\mathrm{15}}{9}$	Automatic
55	MERSI	402-12750	20	$\frac{\mathrm{18}}{\mathrm{12}}$	Automatic
56	MIPAS	685-2410	5	$\frac{\mathrm{NIR2}}{\mathrm{NIR1}}$	Automatic
57	MMR	450-2300	7	$\frac{5}{3}$	Automatic
58	MODIS	405-14385	36	$\frac{5}{\mathrm{14}}$	Automatic
59	Monitor-E	510-900	4	$\frac{4}{3}$	Automatic
60	MSU-MR	500-12500	6	$\frac{2}{1}$	Automatic
61	MVISR	430-12200	10	$\frac{\mathrm{10}}{1}$	Automatic
62	OCM-2	402-885	8	$\frac{8}{7}$	Automatic
63	Orbview-1	450-900	5	$\frac{5}{4}$	Automatic
64	Orbview-4	450-2450	200	$\frac{\mathrm{64}}{\mathrm{25}}$	Automatic
65	PHI	400-1000.35	244	$\frac{\mathrm{244}}{\mathrm{122}}$	Automatic
66	Pleiades-1	430-950	5	$\frac{\mathrm{NIR1}}{\mathrm{Red}}$	Automatic
67	PROBA-V	440-1635	4	$\frac{\mathrm{NIR}}{\mathrm{RED}}$	Automatic
68	QuickBird	450-900	5	$\frac{\mathrm{near\_infrared}}{\mathrm{red}}$	Automatic
69	RapidEye	440-850	5	$\frac{\mathrm{Near\_Infrared}}{\mathrm{Red\_edge}}$	Automatic
70	Resource21	450-1650	6	$\frac{4}{3}$	Automatic
71	Resurs-DK1	500-800	4	$\frac{4}{3}$	Automatic
72	SCIAMACHY	240-2380	15	$\frac{\mathrm{NIR2}}{\mathrm{VIS2}}$	Automatic
73	SeaWiFS	412-905	8	$\frac{8}{6}$	Automatic
74	Sentinel-2A	433-2280	13	$\frac{9}{5}$	Automatic
75	SEVIRI	560-14400	12	$\frac{\mathrm{VIS\_0.8\_}}{\mathrm{HRV}}$	Automatic
76	SIS	450-900	5	$\frac{5}{4}$	Automatic
77	SPOT 1-3	500-890	4	$\frac{\mathrm{near\_infrared}}{\mathrm{red}}$	Automatic
78	SPOT 4	500-1750	5	$\frac{\mathrm{near\_infrared}}{\mathrm{red}}$	Automatic
79	SPOT 5	480-1750	5	$\frac{\mathrm{near\_infrared}}{\mathrm{red}}$	Automatic
80	SPOT 6	450-890	5	$\frac{\mathrm{NIR}}{\mathrm{RED}}$	Automatic
81	SPOT 7	450-890	5	$\frac{\mathrm{NIR}}{\mathrm{RED}}$	Automatic
82	UK-DMC 2	520-900	3	$\frac{\mathrm{NIR}}{\mathrm{Red}}$	Automatic
83	VENμS	400-920	12	$\frac{\mathrm{12}}{8}$	Automatic
84	VIIRS	412-13350	22	$\frac{\mathrm{DNB}}{\mathrm{I1}}$	Automatic
85	VIRR	430-12500	10	$\frac{2}{1}$	Automatic
86	WorldView-2	400-1040	9	$\frac{\mathrm{Near\_Infrared\_2\_Band}}{\mathrm{Red}}$	Automatic
87	WorldView-3	400-2365	29	$\frac{\mathrm{SWIR\_1}}{\mathrm{Red\_Edge}}$	Automatic

Applications

Nr.	Name	Comment
1	Vegetation
2	Vegetation - Biomass
3	Vegetation - Cellulose
4	Vegetation - Chlorophyll
5	Vegetation - LAI
6	Vegetation - Lignin
7	Vegetation - Starch
8	Vegetation - Water

References

Nr.	Author/Title	Year	Comment
1	Ahamed, T.; Tian, L.; Zhang, Y.; Ting, K. C. - A review of remote sensing methods for biomass feedstock production	2011
2	Bannari, A.; Morin, D.; Bonn, F.; Huete, A. R. - A review of vegetation indices	1995
3	Birth, G. S.; McVey, G. - Measuring the Color of Growing Turf with a Reflectance Spectrophotometer	1968
4	Broge, N. H.; Leblanc, E. - Comparing prediction power and stability of broadband and hyperspectral vegetation indices for estimation of green leaf area index and canopy chlorophyll density	2000
5	Choubey, V. K.; Choubey, R. - Spectral reflectance, growth and chlorophyll relationships for rice crop in a semi-arid region of India	1999
6	Cloutis, E. A.; Connery, D. R.; Major, D. J.; Dover, F. J. - Airborne multi-spectral monitoring of agricultural crop status: effect of time of year, crop type and crop condition parameter	1996
7	Ehammer, Andrea; Fritsch, Sebastian; Conrad, Christopher; Lamers, John; Dech, Stefan - Statistical derivation of fPAR and LAI for irrigated cotton and rice in arid Uzbekistan by combining multi-temporal RapidEye data and ground measurements	2010
8	Galvão, Lênio Soares; Formaggio, Antônio Roberto; Tisot, Daniela Arnold - Discrimination of sugarcane varieties in Southeastern Brazil with EO-1 Hyperion data	2005
9	Heiskanen, J. - Estimating aboveground tree biomass and leaf area index in a mountain birch forest using ASTER satellite data	2006
10	Kooistra, L.; Leuven, R. S. E. W.; Wehrens, R.; Nienhuis, P. H.; Buydens, L. M. C. - A comparison of methods to relate grass reflectance to soil metal contamination	2003
11	Kooistra, L.; Salas, E. A. L.; Clevers, J. G. P. W.; Wehrens, R.; Leuven, R. S. E. W.; Nienhuis, P. H.; Buydens, L. M. C. - Exploring field vegetation reflectance as an indicator of soil contamination in river floodplains	2004
12	le Maire, G.; Francois, C.; Dufrene, E. - Towards universal broad leaf chlorophyll indices using PROSPECT simulated database and hyperspectral reflectance measurements	2004
13	Major, D. J.; Baret, F.; Guyot, G. - A ratio vegetation index adjusted for soil brightness	1990
14	Malthus, Tim J.; Andrieu, Bruno; Danson, F. Mark; Jaggard, Keith W.; Steven, Michael D. - Candidate high spectral resolution infrared indices for crop cover	1993
15	Peñuelas, J.; Filella, I. - Visible and near-infrared reflectance techniques for diagnosing plant physiological status	1998
16	Peñuelas, Josep; Gamon, John A.; Griffin, Kevin L.; Field, Christopher B. - Assessing community type, plant biomass, pigment composition, and photosynthetic efficiency of aquatic vegetation from spectral reflectance	1993
17	Pu, Ruiliang; Gong, Peng; Yu, Qian - Comparative Analysis of EO-1 ALI and Hyperion, and Landsat ETM+ Data for Mapping Forest Crown Closure and Leaf Area Index	2008
18	Richardson, A. J.; Everitt, J. H. - Using spectral vegetation indices to estimate rangeland productivity	1992
19	Richardson, Andrew D.; Duigan, Shane P.; Berlyn, Graeme P. - An evaluation of noninvasive methods to estimate foliar chlorophyll content	2002
20	Rondeaux, Geneviève; Steven, Michael; Baret, Frédéric - Optimization of soil-adjusted vegetation indices	1996
21	Royo, C.; Aparicio, N.; Villegas, D.; Casadesus, J.; Monneveux, P.; Araus, J. L. - Usefulness of spectral reflectance indices as durum wheat yield predictors under contrasting Mediterranean conditions	2003
22	Schlerf, M.; Atzberger, C.; Hill, J. - Remote sensing of forest biophysical variables using HyMap imaging spectrometer data	2005
23	Serrano, Lydia; Filella, Iolanda; Peñuelas, Josep - Remote Sensing of Biomass and Yield of Winter Wheat under Different Nitrogen Supplies	2000
24	Tucker, C. J.; Elgin Jr, J. H.; McMurtrey Iii, J. E.; Fan, C. J. - Monitoring corn and soybean crop development with hand-held radiometer spectral data	1979
25	Wu, Chaoyang; Niu, Zheng; Tang, Quan; Huang, Wenjiang - Estimating chlorophyll content from hyperspectral vegetation indices: Modeling and validation	2008
26	Zheng, Guang; Moskal, L. Monika - Retrieving Leaf Area Index (LAI) Using Remote Sensing: Theories, Methods and Sensors	2009

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Visualisation of Sensor-Bands

Index:

Sensors:

AHS

AISA

ALI

ALOS

ARIES-1

ASAS

ASTER

AVHRR

AVIRIS

AVIS

AVNIR

Azimuth Systems AZ-16

CASI 550

CASI EG

CASI spectral

CASI-2 Vegetation

CASI1500

CASI_spatial

CBERS-1/CBERS-2

ChrisProbaM1

ChrisProbaM2

ChrisProbaM3

ChrisProbaM3A

ChrisProbaM4

ChrisProbaM5

Daedalus

DAIS-7915

Deimos-2

DubaiSat-1

Early Bird

EnMap

Formosat-2

GeoEye-1

GLI

GOMOS

HRSC-A

HYDICE

HyMap

Hyperion

IKONOS-2

INSAT-2E

IRS-1A

IRS-1B

IRS-1C

IRS-1D

IRS-P2

IRS-P3

IRS-P4

Kompsat-2

Landsat 8

LandsatETM+ (Landsat7)

LandsatMSS (Landsat1-3)

LandsatTM (Landsat4,5)

MERIS

MERSI

MIPAS

MMR

MODIS

Monitor-E

MSU-MR

MVISR

OCM-2

Orbview-1

Orbview-4

PHI

Pleiades-1

PROBA-V

QuickBird

RapidEye

Resource21

Resurs-DK1

SCIAMACHY

SeaWiFS

Sentinel-2A

SEVIRI

SIS

SPOT 1-3

SPOT 4

SPOT 5

SPOT 6

SPOT 7

UK-DMC 2

VENμS

VIIRS

VIRR

WorldView-2

WorldView-3

List of Indices