Application: Vegetation Water

Vegetation Water

Select other Application.

Basic information

Name Vegetation
Specific Name Water
Description

Indices

Nr. Name Formula Variables Comment
1 Simple Ratio NIR/RED NIR RED
2 Simple Ratio 1600/820 1600nm 820nm
3 Normalized Difference 850/1650 850nm - 1650nm 850nm + 1650nm
4 Normalized Difference NIR/Red NIR - RED NIR + RED RED=[670;50;30],NIR=[800;10;10]
5 Normalized Difference 860/1240 860nm - 1240nm 860nm + 1240nm
6 Simple Ratio 970/900 970nm 900nm
7 Disease water stress index 802nm + 547nm 1657nm + 682nm
8 Normalized Difference 1094/983 1094nm - 893nm 1094nm + 893nm
9 Normalized Difference 1094/1205 1094nm - 1205nm 1094nm + 1205nm
10 Leaf Water Content Index log ⁡ ( 1 - ( NIR - MIDIR ) ) - log ⁡ ( 1 - ( NIR - MIDIR ) )
11 Three-Band Ratio 1200 2 ⁢ [1180:1220] [1090:1110] + ( [1265:1285] )
12 Three-Band Ratio 975 2 ⁢ [960:990] [920:940] + [1090:1110]
13 Simple Ratio 1058/1148 1058nm 1148nm
14 Normalized Difference 860/1640 860nm - 1640nm 860nm + 1640nm
15 Simple Ratio 860/1240 860nm 1240nm
16 Simple Ratio 800/1660 800nm 1660nm
17 Simple Ratio 1660/550 1660nm 550nm
18 Simple Ratio 1660/680 1660nm 680nm
19 Simple Ratio 550/680 550nm 680nm
20 Disease-Water Stress Index 5 800nm - 550nm 1660nm + 680nm
21 Ratio of WI and Normalised Difference 750/660 900nm 970nm 750nm–705nm 750nm + 705nm
22 Crop water stress index C - A B - A
23 Relative Water Content Index FW - DW TW - DW
24 Single Band 970 970nm
25 Single Band 1200 1200nm
26 Single Band 1400 1400nm
27 Single Band 1450 1450nm
28 Single Band 1940 1940nm
29 WI/NDVI 900nm 970nm 800nm - 680nm 800nm + 680nm
30 Simple Ratio 970/902 970nm 902nm
31 Simple Ratio 895/972 895nm 972nm
32 Normalized Difference 857/1241 857nm - 1241nm 857nm + 1241nm
33 Simple Ratio 1193/1126 1193nm 1126nm

Sensors

Nr. Name Spectral Range Bands
1 ChrisProbaM1 406-1003 62
2 ChrisProbaM2 406-1036 18
3 ChrisProbaM3 438-1035 18
4 ChrisProbaM4 486-796 18
5 ChrisProbaM5 438-1036 37
6 LandsatMSS (Landsat1-3) 500-1100 4
7 LandsatTM (Landsat4,5) 450-12500 7
8 LandsatETM+ (Landsat7) 450-12500 8
9 ASTER 520-11650 15
10 RapidEye 440-850 5
11 HyMap 429-2493.8 126
12 AVHRR 580-12500 6
13 MODIS 405-14385 36
14 QuickBird 450-900 5
15 SPOT 1-3 500-890 4
16 IKONOS-2 445-900 5
17 MERIS 407.5-905 15
18 Kompsat-2 0-900 5
19 EnMap 420-2450 244
20 GeoEye-1 450-920 5
21 Orbview-1 450-900 5
22 AVIRIS 355.15-2515 224
23 HRSC-A 395-1015 5
24 ChrisProbaM3A 420-910 18
25 Orbview-4 450-2450 200
26 ALI 433-2350 10
27 Hyperion 349.896-2582.28 242
28 SPOT 4 500-1750 5
29 SPOT 5 480-1750 5
30 WorldView-2 400-1040 9
31 Formosat-2 450-900 5
32 ALOS 0-890 6
33 CBERS-1/CBERS-2 450-890 8
34 WorldView-3 400-2365 29
35 SeaWiFS 412-905 8
36 MVISR 430-12200 10
37 VIRR 430-12500 10
38 MERSI 402-12750 20
39 SEVIRI 560-14400 12
40 VIIRS 412-13350 22
41 MSU-MR 500-12500 6
42 OCM-2 402-885 8
43 UK-DMC 2 520-900 3
44 DubaiSat-1 420-890 5
45 Resurs-DK1 500-800 4
46 Monitor-E 510-900 4
47 AISA 400-2506.7 498
48 CASI_spatial 417-806 11
49 DAIS-7915 400-12600 79
50 HYDICE 400-2500 210
51 AHS 428.5-13140 80
52 IRS-1D 500-1700 5
53 IRS-1C 500-1700 5
54 Sentinel-2A 433-2280 13
55 VENμS 400-920 12
56 GOMOS 250-952 5
57 MIPAS 685-2410 5
58 SCIAMACHY 240-2380 15
59 CASI 550 400-1000 288
60 CASI1500 380-1500 288
61 GLI 375-12500 36
62 ARIES-1 400-2587 105
63 ASAS 400-1020 62
64 INSAT-2E 550-12500 6
65 Pleiades-1 430-950 5
66 PHI 400-1000.35 244
67 CASI spectral 391-905.5 96
68 IRS-1A 450-860 4
69 IRS-P2 450-860 4
70 IRS-P3 403-1650 18
71 IRS-1B 450-860 4
72 IRS-P4 402-1700 9
73 CASI EG 474.7-789.5 13
74 MMR 450-2300 7
75 AVNIR 400-920 5
76 Early Bird 450-890 4
77 SIS 450-900 5
78 Resource21 450-1650 6
79 Daedalus 0-13000 12
80 AVIS 550-994 74
81 Azimuth Systems AZ-16 0-13000 12
82 CASI-2 Vegetation 441.53-869.54 12
83 Landsat 8 435-12510 11
84 PROBA-V 440-1635 4
85 Deimos-2 420-890 5
86 SPOT 6 450-890 5
87 SPOT 7 450-890 5
88 CZCS 433-12500 6
89 SASI600 950-2450 100
90 VISSR 500-12500 3
91 ILAS-II 753-11770 2
92 GOSAT 700-13200 4
93 TIMS 0-12200 8
94 POLDER 2 443-910 2
95 WIS 0-1000 64

References

Nr. Author/Title Year Comment
1 Bastiaanssen, Wim G. M.; Molden, David J.; Makin, Ian W. - Remote sensing for irrigated agriculture: examples from research and possible applications 2000
2 Ceccato, Pietro; Flasse, Stéphane; Tarantola, Stefano; Jacquemoud, Stéphane; Grégoire, Jean-Marie - Detecting vegetation leaf water content using reflectance in the optical domain 2001
3 Ceccato, Pietro; Gobron, Nadine; Flasse, Stéphane; Pinty, Bernard; Tarantola, Stefano - Designing a spectral index to estimate vegetation water content from remote sensing data: Part 1: Theoretical approach 2002
4 Cibula, W. G.; Zetka, E. F.; Rickman, D. L. - Response of thematic mapper bands to plant water stress 1992
5 Curran, Paul J. - Remote sensing of foliar chemistry 1989
6 Datt, Bisun - Remote Sensing of Water Content in Eucalyptus Leaves 1999
7 Gao, Bo-cai - NDWI—A normalized difference water index for remote sensing of vegetation liquid water from space 1996
8 Glenn, Edward; Huete, Alfredo; Nagler, Pamela; Nelson, Stephen - Review - Relationship Between Remotely-sensed Vegetation Indices, Canopy Attributes and Plant Physiological Processes: What Vegetation Indices Can and Cannot Tell Us About the Landscape 2008
9 Hunt Jr, E. Raymond; Rock, Barrett N. - Detection of changes in leaf water content using Near- and Middle-Infrared reflectances 1989
10 Hunt Jr, Raymond E.; Rock, Barrett N.; Nobel, Park S. - Measurement of leaf relative water content by infrared reflectance 1987
11 Nagler, Pamela L.; Scott, Russell L.; Westenburg, Craig; Cleverly, James R.; Glenn, Edward P.; Huete, Alfredo R. - Evapotranspiration on western U.S. rivers estimated using the Enhanced Vegetation Index from MODIS and data from eddy covariance and Bowen ratio flux towers 2005
12 Penuelas, J.; Filella, I.; Biel, C.; Serrano, L.; Save, R. - The reflectance at the 950–970 nm region as an indicator of plant water status 1993
13 Penuelas, J.; Pinol, J.; Ogaya, R.; Filella, I. - Estimation of plant water concentration by the reflectance Water Index WI (R900/R970) 1997
14 Peñuelas, J.; Filella, I. - Visible and near-infrared reflectance techniques for diagnosing plant physiological status 1998
15 Peñuelas, J.; Gamon, J. A.; Fredeen, A. L.; Merino, J.; Field, C. B. - Reflectance indices associated with physiological changes in nitrogen- and water-limited sunflower leaves 1994
16 Pinter, P. J.; Hatfield, J. L.; Schepers, J. S.; Barnes, E. M.; Moran, M. S.; Daughtry, C. S. T.; Upchurch, D. R. - Remote sensing for crop management 2003
17 Pu, R.; Ge, S.; Kelly, N. M.; Gong, P. - Spectral absorption features as indicators of water status in coast live oak ( Quercus agrifolia ) leaves 2003
18 Serrano, Lydia; Ustin, Susan L.; Roberts, Dar A.; Gamon, John A.; Peñuelas, Josep - Deriving Water Content of Chaparral Vegetation from AVIRIS Data 2000
19 Thenot, F.; Méthy, M.; Winkel, T. - The Photochemical Reflectance Index (PRI) as a water-stress index 2002
20 Underwood, Emma; Ustin, Susan; DiPietro, Deanne - Mapping nonnative plants using hyperspectral imagery 2003
21 Zarco-Tejada P.J.; Sepulcre-Cantó, G. - REMOTE SENSING OF VEGETATION BIOPHYSICAL PARAMETERS FOR DETECTING STRESS CONDITION AND LAND COVER CHANGES 2007
22 Zarco-Tejada, P. J.; Rueda, C. A.; Ustin, S. L. - Water content estimation in vegetation with MODIS reflectance data and model inversion methods 2003

Export bibliographic references as: BibTeX • RIS (Endnote) • CSV

List of Applications