Near‐Remote Green: Red Perpendicular Vegetation Index Ground Cover Fraction Estimation in Cotton

Abstract

ABSTRACTGround cover fraction (GCF) can be used as a proxy for leaf area index, plant radiation capture, and plant canopy characteristics in cotton (Gossypium hirsutum L.). One method of imagery‐based GCF estimation is to separate plant pixels from soil pixels based on intensity of reflected green and red radiation. However, this method can be time‐consuming, may be subject to bias, and is limited by image resolution. We examine a simple, image‐based measure of GCF that provides a rapid measurement of crop growth based on the concept of the perpendicular vegetation index (PVI) but using two visible camera channels. The method is based on two linear relationships: one of which measures the relationship between intensity of green and red reflectance for all soil brightness values (the soil line) and another that measures green and red for 100% canopy cover. The GCF in an image is then calculated based on the mean reflectance of the image and the ratio of the image green values to that of 100% GCF from a defined soil line (GCFPVI‐Green). A strong linear relationship was found between the GCFPVI‐Green and a method of separating soil pixels from plant pixels (GCFPixelCount). The GCFPVI‐Green was relatively insensitive to multiple cultivars and irrigation levels. The high correlation between GCFPVI‐Green and GCFPixelCount, as well as the similarities of results between this method and previous methods based on near‐infrared (NIR) and red pixel values, suggest that GCFPVI‐Green may be useful as a more timely alternative method to estimate GCF in agricultural fields.