Value of Using Different Vegetative Indices to Quantify Agricultural Crop Characteristics at Different Growth Stages under Varying Management Practices
By Jerry L. Hatfield, John H. Prueger. Remote Sensing, 2010
323 citations recorded by the source corpus.
The paper investigates the value of using distinct vegetation indices to quantify and characterize agricultural crop characteristics at different growth stages. Research was conducted on four crops (corn, soybean, wheat, and canola) over eight years grown under different tillage practices and nitrogen management practices that varied rate and timing. Six different vegetation indices were found most useful, depending on crop phenology and management practices: (a) simple ratio for biomass, (b) NDVI for intercepted PAR, (c) SAVI for early stages of LAI, (d) EVI for later stages of LAI, (e) CIgreen for leaf chlorophyll, (f) NPCI for chlorophyll during later stages, and (g) PSRI to quantify plant senescence. There were differences among varieties of corn and soybean for the vegetation indices during the growing season and these differences were a function of growth stage and vegetative index. These results clearly imply the need to use multiple vegetation indices to best capture agricultural crop characteristics.
Subfields: Ecology, Global and Planetary Change, Plant Science
View Paper: https://www.semanticscholar.org/paper/51ac67abb9e148abcd9df3e6cd2cdf316e669522
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Citations in the corpus
- A visible band index for remote sensing leaf chlorophyll content at the canopy scale (2013, background): “…are: red 580–670 nm, green 480–610 nm, and blue 400–520 nm (Hunt et al., 2005). b R is the reflectance at wavelength ; Rn , Rre , Rr , Rg , and Rb are the reflectances for NIR, RE, red, green, and blue bands, respectively. and Huete, 1991; Hatfield et al., 2004, 2008; Hatfield and Prueger, 2010).”
- An overview of current and potential applications of thermal remote sensing in precision agriculture (2017, methodology): “…of using thermal images from various platforms (i.e., satellite, aerial and UAV) as a tool for measuring these variables (Shafian and Maas, 2015; Hillel, 2013; Soliman et al., 2013; Chávez et al., 2008; Carlson, 2007) (discussed below), and demonstrated that the timely availability of these…”