Remote Sensing Leaf Chlorophyll Content Using a Visible Band Index

Abstract

Leaf chlorophyll content (μg cm−2) is an important variable for agricultural remote sensing because of its close relationship to leaf N content. The objectives of this study were to develop and test a new index, based on red, green and blue bands, that is sensitive to differences in leaf chlorophyll content at leaf and canopy scales. We propose the triangular greenness index (TGI), which calculates the area of a triangle with vertices: (λr, Rr), (λg, Rg), and (λb, Rb), where λ is the wavelength (nm) and R is the reflectance for bands in red (r), green (g), and blue (b) wavelengths. The TGI was correlated with chlorophyll content using a variety of leaf and plot reflectance data. Generally, indices using the chlorophyll red‐edge (710–730 nm) had higher correlations with chlorophyll content compared to TGI. However, correlations between TGI and chlorophyll content were equal to or higher than broad‐band indices, when leaf area index (LAI) was >2. Simulations using the Scattering by Arbitrarily Inclined Leaves (SAIL) canopy model indicate an interaction among TGI, LAI, and soil type at low LAI, whereas at high LAI, TGI was only affected by leaf chlorophyll content. The TGI could be used with low‐cost sensors, such as commercially‐available digital cameras, for N management by remote sensing.