A visible band index for remote sensing leaf chlorophyll content at the canopy scale |
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| Institution: | 1. Department of Geography, School of Geographic and Environmental Science, Guizhou Normal University, No.116 BaoshanBeiLu, Guiyang 550001, Guizhou, China;2. Institute of Environment, Energy and Sustainability, The Chinese University of Hong Kong, Hong Kong;3. School of Arts, Guizhou Normal University, No.116 BaoshanBeiLu, Guiyang 550001,Guizhou, China;4. Faculty of Environmental Engineering, The University of Kitakyushu, Kitakyushu, Fukuoka 802-0841, Japan;1. Department of Geosciences and Natural Resource Management (IGN), University of Copenhagen, Øster Voldgade 10, DK-1350 Copenhagen, Denmark;2. Department of Physical Geography and Ecosystem Analysis, Lund University, Sölvegatan 12, SE-223 62 Lund, Sweden;3. Efficient Use of Water in Agriculture Program, Institut de Recerca i Tecnologia Agroalimentàries (IRTA), Fruitcentre, Parc Cientific i Tecnològic Agroalimentari, Lleida 25003, Spain;4. Department of Hydrology, Geological Survey of Denmark and Greenland (GEUS), Øster Voldgade 10, DK-1350 Copenhagen, Denmark;5. Department of Environmental Engineering, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark;6. Department of Meteorology, University of Reading, 3 Earley Gate, PO Box 238, Reading, United Kingdom;7. Space Research Centre, University of Leicester, University Road Leicester, LE1 7RH, United Kingdom |
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| Abstract: | Leaf chlorophyll content is an important variable for agricultural remote sensing because of its close relationship to leaf nitrogen content. The triangular greenness index (TGI) was developed based on the area of a triangle surrounding the spectral features of chlorophyll with points at (670 nm, R670), (550 nm, R550), and (480 nm, R480), where Rλ is the spectral reflectance at wavelengths of 670, 550 and 480, respectively. The equation is TGI = ?0.5(670 ? 480)(R670 ? R550) ? (670 ? 550)(R670 ? R480)]. In 1999, investigators funded by NASA's Earth Observations Commercialization and Applications Program collaborated on a nitrogen fertilization experiment with irrigated maize in Nebraska. Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data and Landsat 5 Thematic Mapper (TM) data were acquired along with leaf chlorophyll meter and other data on three dates in July during late vegetative growth and early reproductive growth. TGI was consistently correlated with plot-averaged chlorophyll-meter values at the spectral resolutions of AVIRIS, Landsat TM, and digital cameras. Simulations using the Scattering by Arbitrarily Inclined Leaves (SAIL) canopy model indicate an interaction among TGI, leaf area index (LAI) and soil type at low crop LAI, whereas at high LAI and canopy closure, TGI was only affected by leaf chlorophyll content. Therefore, TGI may be the best spectral index to detect crop nitrogen requirements with low-cost digital cameras mounted on low-altitude airborne platforms. |
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| Keywords: | Spectral indices Triangular greenness index (TGI) Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) PROSPECT SAIL Landsat Thematic Mapper (TM) Nitrogen fertilization |
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