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Image indexes

Tiago Olivoto

2024-11-04

Source: vignettes/indexes.Rmd
indexes.Rmd

Getting started

In this vignette, you will learn about the color space indexes provided by the package, with a focus on the RGB color space, the HSB color space, and the CIE-Lab color space.

Throughout the vignette, we will delve into the underlying formulas and methodologies used for converting colors between different color spaces, ensuring that you have a comprehensive understanding of how these transformations work.

RGB Color Space

The RGB (Red, Green, Blue) color space is a widely used color representation in computer graphics and digital imaging. In the pliman package, we provide a range of indexes to analyze and manipulate color data within the RGB color space:

Indexes in the RGB Color Space

Abbreviation Name Formula Reference
B Blue (445 nm) B
BCC Blue Chromatic Coordinate Index B/(R+G+B) De Swaef et al. (2021)
BGI Blue Green Pigment B/G Zarco-Tejada et al. (2005)
BI Brightness Index sqrt((R^2 + G^2 + B^2) / 3) A. J. Richardson and Wiegand (1977)
BI2 Brightness Index 2 sqrt((R^2 + G^2 + B^2) / 3)
BRVI Blue Red Vegetation Index (B-R)/(B+R) De Swaef et al. (2021)
CI Coloration Index ((R - B) / R)
CIVE Color Index of Vegetation Extraction (0.811*G)+(0.385*B)+18.78745) Kataoka et al. (2003)
EGVI Excess Green Index 2 * G - R - B Woebbecke et al. (1995)
ERVI Excess Red Vegetation Index ((1.4 * R) - G) Meyer and Neto (2008)
GCC Green Percentage Index G/(R+G+B) A. D. Richardson et al. (2007)
GD Green Difference Liang et al. (2017)
GLI Green Leaf Index ((G-R)+(G-B))/(G+R+G+B) Louhaichi, Borman, and Johnson (2001)
GLAI (25 * (G - R) / (G + R - B) + 1.25)
GR Green-Red Ratio G / R
GRAY 0.299 * R + 0.587 * G + 0.114 * B
GRAY2 ((R^2.2 + (1.5 * G)^2.2 + (0.6 * B)^2.2) / (1 + 1.5^2.2 + 0.6^2.2))^(1/2.2)
GRVI2 Green Red Vegetation Index (G-R)/(G+R) Motohka et al. (2010)
G Green (545 nm) G
GB Green-Blue Ratio G / B
HI Primary Colours Hue Index (2*R-G-B)/(G-B) Escadafal, Belghit, and Ben-Moussa (1994)
HUE Overall Hue Index atan(2*(B-G-R)/30.5*(G-R)) Escadafal, Belghit, and Ben-Moussa (1994)
HUE2 Overall Hue Index 2 atan(2*(R-G-R)/30.5*(G-B)) Escadafal, Belghit, and Ben-Moussa (1994)
I Total intensity R + G + B
IPCA Principal Component Analysis Index 0.994*abs(R-B) + 0.961*abs(G-B) + 0.914*abs(G-R) Saberioon et al. (2014)
L Average Intensity (R + G + B) / 3
MGVRI Modified Green Red Vegetation Index (G2 - R2) / (G2 + R2) Bendig et al. (2015)
MVARI Modified Visible Atmospherically Resistant Vegetation Index (G - B)/(G + R - B) Z. Yang, Willis, and Mueller (2008)
NB Normalized Blue B / (R + G + B) W. Yang et al. (2015)
NDI Normalized Difference Index 128*((G - R)/(G + R) + 1) McNairn and Protz (1993)
NG Normalized Green G / (R + G + B) W. Yang et al. (2015)
NGBDI Normalized Green-Blue Difference Index (G-B)/(G+B) Bannari et al. (1995)
NGRDI Normalized Green-Red Difference Index (G-R)/(G+R) Tucker (1979)
NR Normalized Red R / (R + G + B) W. Yang et al. (2015)
PRI Photochemical Reflectance Index R / G Gamon, Serrano, and Surfus (1997)
R Red (650 nm) R
RB Red-Blue Ratio R / B
RCC Red Chromatic Coordinate Index R/(R + G + B) De Swaef et al. (2021)
RGBVI Red Green Blue Vegetation Index (G2 - (B * R))/(G2 + (B * R)) Bendig et al. (2015)
RI Redness Index (R^2 / (B * G^3))
SAT Overall Saturation Index ((max(R, G, B) - min(R, G, B)) / max(R, G, B))
SAVI Soil Adjusted Vegetation Index (1 + 0.5)*(G-R)/(G+R+0.5) Li et al. (2010)
SCI Soil Colour Index (R - G) / (R + G) Mathieu et al. (1998)
SHP Shape Index (2 * (R - G - B) / (G - B))
SI Normalized Red-Blue Difference Index (R-B)/(R+B) Escadafal, Belghit, and Ben-Moussa (1994)
S Saturation ((R + G + B) - 3 * B) / (R + G + B)
TGI Triangular Greenness Index G - 0.39*R - 0.61*B Hunt et al. (2013)
VARI Visible Atmospherically Resistant Index (G-R)/(G+R-B) Anatoly A. Gitelson et al. (2002a)
VEG Vegetative Index G/(R^0.667 * B^0.334) Hague, Tillett, and Wheeler (2006)
vNDVI Visible NDVI 0.5268 * (R - 0.1294*G**0.3389 * B - 0.3118) Costa, Nunes, and Ampatzidis (2020)
WI Woebbecke Index G - B)/(R - G) Woebbecke et al. (1995)

Multispectral indexes

{pliman} provides tools to analyze up to 5 bands , which are generally B, G, R, RE (red-edge) and NIR (near-infrared). The following build-in indexes are available.

Abbreviation Name Formula Reference
ARI Anthocyanin Reflectance Index (1 / G) - (1 / RE) A. A. Gitelson, Merzlyak, and Chivkunova (2001)
ARVI Atmospherically Resistant Vegetation Index (NIR - (R - 0.1*(R-B))) / (NIR + (R - 0.1*(R-B))) Kaufman and Tanre (1992)
BAI Burn Area Index 1/((0.1 - R)^2 + (0.06 - NIR)^2) Chuvieco, Martín, and Palacios (2002)
BWDRVI Blue-Wide Dynamic Range Vegetation Index (0.1*NIR-B)/(0.1*NIR+B) Anatoly A. Gitelson (2004)
CCCI Canopy Chlorophyll Content Index ((NIR-R)/(NIR+R))/((NIR-R)/(NIR+R)) Index DataBase (2023)
CIG Chlorophyll Index Green (NIR/G)-1 Anatoly A. Gitelson, Gritz †, and Merzlyak (2003)
CIRE Chlorophyll Index - Red-Edge (NIR/RE)-1 Anatoly A. Gitelson, Gritz †, and Merzlyak (2003)
CVI Chlorophyll Vegetation Index NIR * (R/(G*G)) Index DataBase (2023)
CVI Chlorophyll Vegetation Index NIR*(R/G^2) Vincini, Frazzi, and D’Alessio (2008)
EVI Enhanced Vegetation Index 2.5*(NIR-R)/(NIR+6*R-7.5*B+1) A. Huete et al. (2002)
GARI Green Atmospherically Resistant Index (NIR - (1.7 * (B-R))) / (NIR + (1.7 * (B-R))) Anatoly A. Gitelson, Kaufman, and Merzlyak (1996)
GEMI Global Environmental Monitoring Index (2*(NIR*NIR-R*R)+1.5*NIR+0.5*R)/(NIR+R+0.5)*(1-0.25*(2*(NIR*NIR-R*R)+1.5*NIR+0.5*R)/(NIR+R+0.5))-((R-0.125)/(1-R)) Pinty and Verstraete (1992)
GDVI Green Difference Vegetation Index NIR-G Index DataBase (2023)
GNDVI Normalized Difference NIR/G (NIR - G) / (NIR + G) Anatoly A. Gitelson and Merzlyak (1996)
GOSAVI Green Optimized Soil Adjusted Vegetation Index (NIR-G)/(NIR+G+0.16) Index DataBase (2023)
GRVI Green Ratio Vegetation Index NIR / G Sripada et al. (2006)
GSAVI Green Soil Adjusted Vegetation Index ((NIR-G)/(NIR+G+0.5))*(1+0.5) Index DataBase (2023)
IPVI Infrared Percentage Vegetation Index NIR / (NIR + R) Crippen (1990)
LAI Leaf Area Index 3.368 * (2.5*(NIR-R)/(NIR+6*R-7.5*B+1)) - 0.118 Boegh et al. (2002)
MCARI1 Modified Chlorophyll Absorption in Reflectance Index 1 1.2*((2.5*(NIR-R))-(1.3*(NIR-G))) Haboudane et al. (2004)
MCARI2 Modified Chlorophyll Absorption in Reflectance Index 2 ((1.2*(2.5*(NIR-R)-1.3*(NIR-G))/sqrt((2*NIR+1)^2-(6*NIR-5*sqrt(R))-0.5))) Haboudane et al. (2004)
MSAVI Modified Soil Adjusted Vegetation Index (1/2)*(2*(NIR+1)-sqrt((2*NIR+1)*2-8*(NIR-R))) Qi et al. (1994)
MSAVI2 Modified Soil Adjusted Vegetation Index 2 (2 * NIR + 1 - sqrt((2 * NIR + 1)^2 - 8 * (NIR - R))) / 2 Qi et al. (1994)
MSR Modified Simple Ratio (NIR / R - 1) / (sqrt(NIR / R) + 1) Chen (1996)
NDRE Normalized Difference NIR/Rededge (NIR-RE)/(NIR+RE) A. Gitelson and Merzlyak (1994)
NDI Non-Linear Index (NIR ^2 - R) / (NIR ^2 + R) Goel and Qin (1994)
NDVI Normalized Difference Vegetation Index (NIR - R) / (NIR + R) Kriegler (1969)
NDWI Normalized Difference Water Index (G-NIR)/(G+NIR) McFEETERS (1996)
OSAVI Optimized Soil Adjusted Vegetation Index (NIR-R)/(NIR+R+0.16) Rondeaux, Steven, and Baret (1996)
PNDVI Pan NDVI ((NIR-(G+R+B))/(NIR+(G+R+B))) Index DataBase (2023)
PSRI Plant Senescence Reflectance Index (R-G)/RE Merzlyak et al. (1999)
RDVI Renormalized Difference Vegetation Index (NIR - R) / (sqrt(NIR + R)) Roujean and Breon (1995)
RESR Red-Edge Simple Ratio NIR/RE Anatoly A. Gitelson et al. (2002b)
RVI Ratio Vegetation Index R/NIR Pearson and Miller (1972)
SAVI Soil Adjusted Vegetation Index ((NIR-R) / (NIR + R + 0.5) * 1 + 0.5) A. R. Huete (1988)
TCARI Transformed Chlorophyll Absorption in Reflectance Index 3 * ((RE - R) - 0.2 * (RE - G) * (RE/R)) Haboudane et al. (2002)
TDVI Transformed Difference Vegetation Index 1.5 * ((NIR - R) / (sqrt(NIR ^2 + R + 0.5))) Bannari, Asalhi, and Teillet (2002)
TSAVI Transformed Soil Adjusted Vegetation Index (2*((NIR-2)*(R-1)))/(R+2*(NIR-1)+0.5*(1+2*2)) Baret, Guyot, and Major (1989)
TVI Transformed Vegetation Index sqrt((NIR - R) / (NIR + R) + 0.5) Broge and Leblanc (2001)
VARIRE Visible Atmospherically Resistant Index (red-edge) (RE - 1.7 * R + 0.7 * B) / (RE + 2.3 * R - 1.3 * B) Anatoly A. Gitelson et al. (2002c)
VIG Vegetation Index (green) (G-R)/(G+R) Anatoly A. Gitelson et al. (2002c)
VIN Vegetation Index Number NIR/R Pearson and Miller (1972)
VIRE Vegetation Index (red-edge) (RE-R)/(RE+R) Anatoly A. Gitelson et al. (2002c)
WDRVI Wide Dynamic Range Vegetation Index (0.2 * NIR - R) / (0.2 * NIR + R) Anatoly A. Gitelson (2004)

Usefull references

HSB Color Space

The HSB (Hue, Saturation, Brightness) color space is an alternative color representation that emphasizes the perceptual aspects of color.

Conversion to CIE-Lab

The rgb_to_hsb() function can be used to convert RGB to HSB color space. The conversion is performed according to described by Karcher and Richardson (2003).

  • Hue (H):
    • If max (R,G,B) = R, H = 60 * (G - B) / (max(R,G,B) - min(R,G,B))
    • If max (R,G,B) = G, H = 60 * (2 + (B - R) / (max(R,G,B) - min(R,G,B))
    • If max (R,G,B) = B, H = 60 * (4 + (R - G) / (max(R,G,B) - min(R,G,B))
  • Saturation (S):
    • S = (max(R,G,B) - min(R,G,B)) / max(R,G,B)
  • Brightness (B):
    • B = max(R,G,B)

Indexes in the HSB Color Space

Abbreviation Name Formula Reference
DGCI Dark Green Color Inde ((H - 60) / 60 + (1 - S/100) + (1 - B/100)) / 3 Karcher and Richardson (2003)

CIE-Lab Color Space

The CIE-Lab (CIELAB) color space is a color model that approximates human vision and is often used for color difference analysis and color correction. In the pliman package, we support the conversion from RGB to Lab color space.

Conversion to CIE-Lab

The conversion from RGB to Lab is performed by the rgb_to_lab() function in the pliman package. This involves several steps, including the transformation from RGB to sRGB, sRGB to XYZ, and then from XYZ to Lab.

To understand the specific formulas and steps involved in this conversion, please refer to the detailed formulas.

Indexes in the CIE-Lab Color Space (soon)

Abbreviation Name Formula Reference

References

Bannari, A., H. Asalhi, and P.M. Teillet. 2002. “Transformed Difference Vegetation Index (TDVI) for Vegetation Cover Mapping.” In IEEE International Geoscience and Remote Sensing Symposium, 5:3053–3055 vol.5. https://doi.org/10.1109/IGARSS.2002.1026867.
Bannari, A., D. Morin, F. Bonn, and A. R. Huete. 1995. “A Review of Vegetation Indices.” Remote Sensing Reviews 13 (1-2): 95–120. https://doi.org/10.1080/02757259509532298.
Baret, F., G. Guyot, and D.J. Major. 1989. “TSAVI: A Vegetation Index Which Minimizes Soil Brightness Effects On LAI And APAR Estimation.” In 12th Canadian Symposium on Remote Sensing Geoscience and Remote Sensing Symposium, 3:1355–58. https://doi.org/10.1109/IGARSS.1989.576128.
Bendig, Juliane, Kang Yu, Helge Aasen, Andreas Bolten, Simon Bennertz, Janis Broscheit, Martin L. Gnyp, and Georg Bareth. 2015. “Combining UAV-Based Plant Height from Crop Surface Models, Visible, and Near Infrared Vegetation Indices for Biomass Monitoring in Barley.” International Journal of Applied Earth Observation and Geoinformation 39 (July): 79–87. https://doi.org/10.1016/j.jag.2015.02.012.
Boegh, Eva, H. Soegaard, N. Broge, C. B. Hasager, N. O. Jensen, K. Schelde, and A. Thomsen. 2002. “Airborne Multispectral Data for Quantifying Leaf Area Index, Nitrogen Concentration, and Photosynthetic Efficiency in Agriculture.” Remote Sensing of Environment 81 (2): 179–93. https://doi.org/10.1016/S0034-4257(01)00342-X.
Broge, N. H, and E Leblanc. 2001. “Comparing Prediction Power and Stability of Broadband and Hyperspectral Vegetation Indices for Estimation of Green Leaf Area Index and Canopy Chlorophyll Density.” Remote Sensing of Environment 76 (2): 156–72. https://doi.org/10.1016/S0034-4257(00)00197-8.
Chen, Jing M. 1996. “Evaluation of Vegetation Indices and a Modified Simple Ratio for Boreal Applications.” Canadian Journal of Remote Sensing 22 (3): 229–42. https://doi.org/10.1080/07038992.1996.10855178.
Chuvieco, E., M. P. Martín, and A. Palacios. 2002. “Assessment of Different Spectral Indices in the Red-Near-Infrared Spectral Domain for Burned Land Discrimination.” International Journal of Remote Sensing 23 (23): 5103–10. https://doi.org/10.1080/01431160210153129.
Costa, Lucas, Leon Nunes, and Yiannis Ampatzidis. 2020. “A New Visible Band Index (vNDVI) for Estimating NDVI Values on RGB Images Utilizing Genetic Algorithms.” Computers and Electronics in Agriculture 172 (May): 105334. https://doi.org/10.1016/j.compag.2020.105334.
Crippen, Robert E. 1990. “Calculating the Vegetation Index Faster.” Remote Sensing of Environment 34 (1): 71–73. https://doi.org/10.1016/0034-4257(90)90085-Z.
De Swaef, T., W.H. Maes, J. Aper, J. Baert, M. Cougnon, D. Reheul, K. Steppe, I. Roldán-Ruiz, and P. Lootens. 2021. “Applying RGB- and Thermal-Based Vegetation Indices from UAVs for High-Throughput Field Phenotyping of Drought Tolerance in Forage Grasses.” Remote Sensing 13 (1): 147. https://doi.org/10.3390/rs13010147.
Escadafal, R., A. Belghit, and A. Ben-Moussa. 1994. “Indices Spectraux Pour La Télédétection de La Dégradation Des Milieux Naturels En Tunisie Aride.” In Actes Du 6eme Symposium International Sur Les Mesures Physiques Et Signatures En Télédétection, edited by G. Guyot, 253–59. Val d’Isère (France).
Gamon, J. A., L. Serrano, and J. S. Surfus. 1997. “The Photochemical Reflectance Index: An Optical Indicator of Photosynthetic Radiation Use Efficiency Across Species, Functional Types, and Nutrient Levels.” Oecologia 112 (4): 492–501. https://doi.org/10.1007/s004420050337.
Gitelson, A. A., M. N. Merzlyak, and O. B. Chivkunova. 2001. “Optical properties and nondestructive estimation of anthocyanin content in plant leaves.” Photochemistry and Photobiology 74 (1): 38–45. https://doi.org/10.1562/0031-8655(2001)074<0038:opaneo>2.0.co;2.
Gitelson, Anatoly A. 2004. “Wide Dynamic Range Vegetation Index for remote quantification of biophysical characteristics of vegetation.” Journal of Plant Physiology 161 (2): 165–73. https://doi.org/10.1078/0176-1617-01176.
Gitelson, Anatoly A., Yuri Gritz †, and Mark N. Merzlyak. 2003. “Relationships Between Leaf Chlorophyll Content and Spectral Reflectance and Algorithms for Non-Destructive Chlorophyll Assessment in Higher Plant Leaves.” Journal of Plant Physiology 160 (3): 271–82. https://doi.org/10.1078/0176-1617-00887.
Gitelson, Anatoly A., Yoram J. Kaufman, and Mark N. Merzlyak. 1996. “Use of a Green Channel in Remote Sensing of Global Vegetation from EOS-MODIS.” Remote Sensing of Environment 58 (3): 289–98. https://doi.org/10.1016/S0034-4257(96)00072-7.
Gitelson, Anatoly A., Yoram J. Kaufman, Robert Stark, and Don Rundquist. 2002a. “Novel Algorithms for Remote Estimation of Vegetation Fraction.” Remote Sensing of Environment 80 (1): 76–87. https://doi.org/10.1016/s0034-4257(01)00289-9.
———. 2002b. “Novel Algorithms for Remote Estimation of Vegetation Fraction.” Remote Sensing of Environment 80 (1): 76–87. https://doi.org/10.1016/S0034-4257(01)00289-9.
———. 2002c. “Novel Algorithms for Remote Estimation of Vegetation Fraction.” Remote Sensing of Environment 80 (1): 76–87. https://doi.org/10.1016/S0034-4257(01)00289-9.
Gitelson, Anatoly A., and Mark N. Merzlyak. 1996. “Signature Analysis of Leaf Reflectance Spectra: Algorithm Development for Remote Sensing of Chlorophyll.” Journal of Plant Physiology 148 (3-4): 494–500. https://doi.org/10.1016/s0176-1617(96)80284-7.
Gitelson, Anatoly, and Mark N. Merzlyak. 1994. “Quantitative Estimation of Chlorophyll-a Using Reflectance Spectra: Experiments with Autumn Chestnut and Maple Leaves.” Journal of Photochemistry and Photobiology B: Biology 22 (3): 247–52. https://doi.org/10.1016/1011-1344(93)06963-4.
Goel, Narendra S., and Wenhan Qin. 1994. “Influences of Canopy Architecture on Relationships Between Various Vegetation Indices and LAI and Fpar: A Computer Simulation.” Remote Sensing Reviews 10 (4): 309–47. https://doi.org/10.1080/02757259409532252.
Haboudane, Driss, John R Miller, Elizabeth Pattey, Pablo J Zarco-Tejada, and Ian B Strachan. 2004. “Hyperspectral Vegetation Indices and Novel Algorithms for Predicting Green LAI of Crop Canopies: Modeling and Validation in the Context of Precision Agriculture.” Remote Sensing of Environment 90 (3): 337–52. https://doi.org/10.1016/j.rse.2003.12.013.
Haboudane, Driss, John R. Miller, Nicolas Tremblay, Pablo J. Zarco-Tejada, and Louise Dextraze. 2002. “Integrated Narrow-Band Vegetation Indices for Prediction of Crop Chlorophyll Content for Application to Precision Agriculture.” Remote Sensing of Environment 81 (2): 416–26. https://doi.org/10.1016/S0034-4257(02)00018-4.
Hague, T., N. D. Tillett, and H. Wheeler. 2006. “Automated Crop and Weed Monitoring in Widely Spaced Cereals.” Precision Agriculture 7 (1): 21–32. https://doi.org/10.1007/s11119-005-6787-1.
Huete, A, K Didan, T Miura, E.P Rodriguez, X Gao, and L.G Ferreira. 2002. “Overview of the Radiometric and Biophysical Performance of the MODIS Vegetation Indices.” Remote Sensing of Environment 83 (1-2): 195–213. https://doi.org/10.1016/s0034-4257(02)00096-2.
Huete, A.R. 1988. “A Soil-Adjusted Vegetation Index (SAVI).” Remote Sensing of Environment 25 (3): 295–309. https://doi.org/10.1016/0034-4257(88)90106-x.
Hunt, E. Raymond, Paul C. Doraiswamy, James E. McMurtrey, Craig S. T. Daughtry, Eileen M. Perry, and Bakhyt Akhmedov. 2013. “A Visible Band Index for Remote Sensing Leaf Chlorophyll Content at the Canopy Scale.” International Journal of Applied Earth Observation and Geoinformation 21 (April): 103–12. https://doi.org/10.1016/j.jag.2012.07.020.
Index DataBase. 2023. “IDB - List of Available Indices.” 2023. https://www.indexdatabase.de/db/i.php.
Karcher, Douglas E., and Michael D. Richardson. 2003. “Quantifying Turfgrass Color Using Digital Image Analysis.” Crop Science 43 (3): 943–51. https://doi.org/10.2135/cropsci2003.9430.
Kataoka, T., T. Kaneko, H. Okamoto, and S. Hata. 2003. “Crop Growth Estimation System Using Machine Vision.” In Proceedings 2003 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM 2003), 2:b1079–b1083 vol.2. https://doi.org/10.1109/AIM.2003.1225492.
Kaufman, Y.J., and D. Tanre. 1992. “Atmospherically Resistant Vegetation Index (ARVI) for EOS-MODIS.” IEEE Transactions on Geoscience and Remote Sensing 30 (2): 261–70. https://doi.org/10.1109/36.134076.
Kriegler, F. 1969. “Preprocessing Transformations and Their Effects on Multspectral Recognition.” Proceedings of the Sixth International Symposium on Remote Sesning of Environment, 97–131. https://cir.nii.ac.jp/crid/1572261549021269760.
Li, Y., D. Chen, C. N. Walker, and J. F. Angus. 2010. “Estimating the Nitrogen Status of Crops Using a Digital Camera.” Field Crops Research 118 (3): 221–27. https://doi.org/10.1016/j.fcr.2010.05.011.
Liang, Ying, Daisuke Urano, Kang-Ling Liao, Tyson L. Hedrick, Yajun Gao, and Alan M. Jones. 2017. “A Nondestructive Method to Estimate the Chlorophyll Content of Arabidopsis Seedlings.” Plant Methods 13 (1): 26. https://doi.org/10.1186/s13007-017-0174-6.
Louhaichi, Mounir, Michael M. Borman, and Douglas E. Johnson. 2001. “Spatially Located Platform and Aerial Photography for Documentation of Grazing Impacts on Wheat.” Geocarto International 16 (1): 65–70. https://doi.org/10.1080/10106040108542184.
Mathieu, Renaud, Marcel Pouget, Bernard Cervelle, and Richard Escadafal. 1998. “Relationships Between Satellite-Based Radiometric Indices Simulated Using Laboratory Reflectance Data and Typic Soil Color of an Arid Environment.” Remote Sensing of Environment 66 (1): 17–28. https://doi.org/10.1016/S0034-4257(98)00030-3.
McFEETERS, S. K. 1996. “The Use of the Normalized Difference Water Index (NDWI) in the Delineation of Open Water Features.” International Journal of Remote Sensing 17 (7): 1425–32. https://doi.org/10.1080/01431169608948714.
McNairn, H., and R. Protz. 1993. “Mapping Corn Residue Cover on Agricultural Fields in Oxford County, Ontario, Using Thematic Mapper.” Canadian Journal of Remote Sensing 19 (2): 152–59. https://doi.org/10.1080/07038992.1993.10874543.
Merzlyak, Mark N., Anatoly A. Gitelson, Olga B. Chivkunova, and Victor YU. Rakitin. 1999. “Non-Destructive Optical Detection of Pigment Changes During Leaf Senescence and Fruit Ripening.” Physiologia Plantarum 106 (1): 135–41. https://doi.org/10.1034/j.1399-3054.1999.106119.x.
Meyer, George E., and João Camargo Neto. 2008. “Verification of Color Vegetation Indices for Automated Crop Imaging Applications.” Computers and Electronics in Agriculture 63 (2): 282–93. https://doi.org/10.1016/j.compag.2008.03.009.
Motohka, Takeshi, Kenlo Nishida Nasahara, Hiroyuki Oguma, and Satoshi Tsuchida. 2010. “Applicability of Green-Red Vegetation Index for Remote Sensing of Vegetation Phenology.” Remote Sensing 2 (10): 2369–87. https://doi.org/10.3390/rs2102369.
Pearson, R. L., and L. D. Miller. 1972. Remote Mapping of Standing Crop Biomass for Estimation of the Productivity of the Shortgrass Prairie. https://ui.adsabs.harvard.edu/abs/1972rse..conf.1355P.
Pinty, B., and M. M. Verstraete. 1992. “GEMI: A Non-Linear Index to Monitor Global Vegetation from Satellites.” Vegetatio 101 (1): 15–20. https://doi.org/10.1007/bf00031911.
Qi, J., A. Chehbouni, A.R. Huete, Y.H. Kerr, and S. Sorooshian. 1994. “A Modified Soil Adjusted Vegetation Index.” Remote Sensing of Environment 48 (2): 119–26. https://doi.org/10.1016/0034-4257(94)90134-1.
Richardson, A J, and Claudia Wiegand. 1977. “Distinguishing Vegetation from Soil Background Information.” Photogrammetric Engineering and Remote Sensing 43 (12): 1541–52. https://www.asprs.org/wp-content/uploads/pers/1977journal/dec/1977_dec_1541-1552.pdf.
Richardson, Andrew D., Julian P. Jenkins, Bobby H. Braswell, David Y. Hollinger, Scott V. Ollinger, and Marie-Louise Smith. 2007. “Use of Digital Webcam Images to Track Spring Green-up in a Deciduous Broadleaf Forest.” Oecologia 152 (2): 323–34. https://doi.org/10.1007/s00442-006-0657-z.
Rondeaux, Geneviève, Michael Steven, and Frédéric Baret. 1996. “Optimization of Soil-Adjusted Vegetation Indices.” Remote Sensing of Environment 55 (2): 95–107. https://doi.org/10.1016/0034-4257(95)00186-7.
Roujean, Jean-Louis, and François-Marie Breon. 1995. “Estimating PAR Absorbed by Vegetation from Bidirectional Reflectance Measurements.” Remote Sensing of Environment 51 (3): 375–84. https://doi.org/10.1016/0034-4257(94)00114-3.
Saberioon, M. M., M. S. M. Amin, A. R. Anuar, A. Gholizadeh, A. Wayayok, and S. Khairunniza-Bejo. 2014. “Assessment of Rice Leaf Chlorophyll Content Using Visible Bands at Different Growth Stages at Both the Leaf and Canopy Scale.” International Journal of Applied Earth Observation and Geoinformation 32 (October): 35–45. https://doi.org/10.1016/j.jag.2014.03.018.
Sripada, Ravi P., Ronnie W. Heiniger, Jeffrey G. White, and Alan D. Meijer. 2006. “Aerial Color Infrared Photography for Determining Early In-Season Nitrogen Requirements in Corn.” Agronomy Journal 98 (4): 968–77. https://doi.org/10.2134/agronj2005.0200.
Tucker, Compton J. 1979. “Red and Photographic Infrared Linear Combinations for Monitoring Vegetation.” Remote Sensing of Environment 8 (2): 127–50. https://doi.org/10.1016/0034-4257(79)90013-0.
Vincini, M., E. Frazzi, and P. D’Alessio. 2008. “A Broad-Band Leaf Chlorophyll Vegetation Index at the Canopy Scale.” Precision Agriculture 9 (5): 303–19. https://doi.org/10.1007/s11119-008-9075-z.
Woebbecke, D. M., G. E. Meyer, K. Von Bargen, and D. A. Mortensen. 1995. “Color Indices for Weed Identification Under Various Soil, Residue, and Lighting Conditions.” Transactions of the ASAE 38 (1): 259–69. https://doi.org/10.13031/2013.27838.
Yang, Wenzhu, Sile Wang, Xiaolan Zhao, Jingsi Zhang, and Jiaqi Feng. 2015. “Greenness Identification Based on HSV Decision Tree.” Information Processing in Agriculture 2 (3-4): 149–60. https://doi.org/10.1016/j.inpa.2015.07.003.
Yang, Zhengwei, Patrick Willis, and Rick Mueller. 2008. “IMPACT OF BAND-RATIO ENHANCED AWIFS IMAGE TO CROP CLASSIFICATION ACCURACY.”
Zarco-Tejada, P. J., A. Berjón, R. López-Lozano, J. R. Miller, P. Martín, V. Cachorro, M. R. González, and A. de Frutos. 2005. “Assessing Vineyard Condition with Hyperspectral Indices: Leaf and Canopy Reflectance Simulation in a Row-Structured Discontinuous Canopy.” Remote Sensing of Environment 99 (3): 271–87. https://doi.org/10.1016/j.rse.2005.09.002.