Search results for »vegetation«

Indices

Nr Name Abbrev. Formula Variables
1 Aerosol free vegetation index 1600 AFRI1600 ( NIR - 0.66 1600nm NIR + 0.66 1600nm )
2 Aerosol free vegetation index 2100 AFRI2100 ( NIR - 0.5 2100nm NIR + 0.56 2100nm )
3 Ashburn Vegetation Index AVI 2.0 [800:1100] - [600:700]
4 Atmospherically Resistant Vegetation Index ARVI NIR - RED - y ( RED - BLUE ) NIR + RED - y ( RED - BLUE ) NIR = [781:1399]
5 Atmospherically Resistant Vegetation Index 2 ARVI2 -0.18 + 1.17 ( NIR - RED NIR + RED )
6 Blue-wide dynamic range vegetation index BWDRVI 0.1 NIR - BLUE 0.1 NIR + BLUE
7 Chlorophyll vegetation index CVI NIR RED GREEN2
8 Corrected Transformed Vegetation Index CTVI NDVI + 0 ,5 | NDVI + 0 ,5| · | ( NDVI ) + 0 ,5|
9 Difference NIR/Green Green Difference Vegetation Index GDVI NIR - G
10 Differenced Vegetation Index MSS DVIMSS 2.4 [800:1100] - [600:700]
11 Enhanced Vegetation Index EVI 2.5 NIR - RED ( NIR + 6 RED - 7.5 BLUE ) + 1
12 Enhanced Vegetation Index 2 EVI2 2.4 NIR - RED NIR + RED + 1
13 Enhanced Vegetation Index 2 -2 EVI2 2.5 NIR - RED NIR + 2.4 RED + 1
14 Global Vegetation Moisture Index GVMI ( NIR + 0.1 ) - ( SWIR + 0.02 ) ( NIR + 0.1 ) + ( SWIR + 0.02 )
15 Green atmospherically resistant vegetation index GARI NIR - ( GREEN - ( BLUE - RED ) ) NIR - ( GREEN + ( BLUE - RED ) )
16 Green Normalized Difference Vegetation Index GNDVI NIR - [540:570] NIR + [540:570]
17 Green Optimized Soil Adjusted Vegetation Index GOSAVI NIR - G NIR + G + Y
18 Green Soil Adjusted Vegetation Index GSAVI NIR - G NIR + G + L ( 1 + L )
19 Ideal vegetation index IVI NIR - b a · RED
20 Infrared percentage vegetation index IPVI NIR NIR + RED 2 ( NDVI + 1 )

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Sensors

Nr. Name Spectrum [nm] Spat.Res. [m] Incl. Platform Operator
1 CASI-2 Vegetation 441.53-869.54 0-0 0 airborne ITRES

Applications

Nr. Name Description
1 Vegetation
2 Vegetation - Biomass
3 Vegetation - Cellulose
4 Vegetation - Chlorophyll
5 Vegetation - Fluorescence
6 Vegetation - LAI Leaf area index
7 Vegetation - Lignin
8 Vegetation - Nitrogen content Nitrogen content of plants
9 Vegetation - Nitrogen stress
10 Vegetation - PAR
11 Vegetation - Protein
12 Vegetation - Salinity stress
13 Vegetation - Starch
14 Vegetation - Stress
15 Vegetation - Sugar
16 Vegetation - Vitality
17 Vegetation - Water
18 Vegetation - Water stress
19 Vegetation - Water use efficiency

References

Nr. Author Title Year Journal Publisher/Loc. Keywords Comment
1 Ahamed, T.; Tian, L.; Zhang, Y.; Ting, K. C. A review of remote sensing methods for biomass feedstock production 2011 Biomass & Bioenergy Perennial energy crops; Site-specific management; Vegetative indices; Leaf area index; Satellite imagery; Remote sensing; tropical forest biomass; landsat tm data; unmanned aerial vehicle; leaf-area index; aboveground biomass; radar backscatter; vegetation; index; water-stress; biophysical properties; image segmentation
2 Apan, Armando; Held, Alex; Phinn, Stuart; Markley, John Formulation and assessment of narrow-band vegetation indices from EO-1 hyperion imagery for discriminating sugarcane disease 2003 2003 Spatial Sciences Institute Conference: Spatial Knowledge Without Boundaries (SSC2003) Spatial Sciences Institute, Canberra, Australia hyperspectral remote sensing, spectral vegetation indices, sugarcane disease, Hyperion
3 Bannari, A.; Morin, D.; Bonn, F.; Huete, A. R. A review of vegetation indices 1995 Remote Sensing Reviews Taylor & Francis
4 Baret, F.; Guyot, G. Potentials and limits of vegetation indices for LAI and APAR assessment 1991 Remote Sensing of Environment
5 Baret, F.; Guyot, G.; Major, D. TSAVI: a vegetation index which minimizes soil brightness effects on LAI and APAR estimation 1989 Proceedings of 12th Canadian Symposium on Remote Sensing and IGARSS’89
6 Baroni, F.; Boscagli, A.; Di Lella, L. A.; Protano, G.; Riccobono, F. Arsenic in soil and vegetation of contaminated areas in southern Tuscany (Italy) 2004 Journal of Geochemical Exploration Arsenic; Plant accumulation; Mining area; Soil contamination
7 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 Remote Sensing of Environment
8 Brunn, A.; Busch, W.; Dittmann, C.; Fischer, C.; Vosen, P. Monitoring Mining Induced Plant Alteration and Change Detection in a German Coal Mining Area using Airborne Hyperspectral Imagery 2003 Spectral Remote Sensing of Vegetation Conference at the U.S. EPA Environmental Sciences Div. Las Vegas, Nevada
9 Buschmann, C.; Nagel, E. In vivo spectroscopy and internal optics of leaves as basis for remote sensing of vegetation 1993 International Journal of Remote Sensing Taylor & Francis
10 Carlson, T. N.; Ripley, David A. On the relation between NDVI, fractional vegetation cover, and leaf area index 1997 Remote Sensing of Environment
11 Ceccato, Pietro; Flasse, Stéphane; Tarantola, Stefano; Jacquemoud, Stéphane; Grégoire, Jean-Marie Detecting vegetation leaf water content using reflectance in the optical domain 2001 Remote Sensing of Environment Leaf water content; Fuel moisture content; Optical domain; Shortwave infrared
12 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 Remote Sensing of Environment
13 Chen, J.M. Evaluation of vegetation indices and a modified simple ratio for boreal applications 1996 Canadian Journal of Remote Sensing Boreal forests; FPAR; LAI; Vegetation index
14 Choubey, V. K.; Choubey, R. Spectral reflectance, growth and chlorophyll relationships for rice crop in a semi-arid region of India 1999 Water Resources Management chlorophyll; growth; rice crop; spectral reflectance; red edge; leaf biochemistry; vegetation; prospect; model
15 Clarke, T. R.; Moran, M. S.; Barnes, E. M.; Pinter, P. J., Jr.; Qi, J. Planar domain indices: a method for measuring a quality of a single component in two-component pixels 2001 Geoscience and Remote Sensing Symposium, 2001. IGARSS '01. IEEE 2001 International agriculture, geophysical signal processing, geophysical techniques, image processing, terrain mapping, vegetation mapping, canopy, geophysical measurement technique, land surface, planar domain index, planar domain indices, quality, remote sensing, single
16 Clevers, J. G. P. W. Application of a weighted infrared-red vegetation index for estimating leaf Area Index by Correcting for Soil Moisture 1989 Remote Sensing of Environment
17 Cole, Monica M.; Smith, Roger F. Vegetation as Indicator of Environmental Pollution 1984 Transactions of the Institute of British Geographers Vegetation, Minerals, Indicator plants, Metal-tolerance, Mining, Pollution, Environment, Australia, Africa, Lrnited Kingdom
18 Crippen, Robert E. Calculating the vegetation index faster 1990 Remote Sensing of Environment
19 Dang, Y. P.; Pringle, M. J.; Schmidt, M.; Dalal, R. C.; Apan, A. Identifying the spatial variability of soil constraints using multi-year remote sensing 2011 Field Crops Research Soil constraints; Crop yield; Precision agriculture; NDVI; Whole-farm; economics; crop yield; wheat yield; subsoil constraints; grain production; australia; vegetation; satellite; ndvi; management; salinity
20 Dorigo, W. A.; Zurita-Milla, R.; de Wit, A. J. W.; Brazile, J.; Singh, R.; Schaepman, M. E. A review on reflective remote sensing and data assimilation techniques for enhanced agroecosystem modeling 2007 International Journal of Applied Earth Observation and Geoinformation data assimilation; agroecosystem modeling; vegetation indices; canopy; reflectance modeling; biophysical variables; biochemical variables; parallel processing; radiative-transfer models; leaf-area index; hyperspectral vegetation; indexes; hydrologic data assimilation; multiple linear-regression; canopy chlorophyll density; ensemble kalman filter; bidirectional; reflectance; soil-moisture; crop models

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