The light absorption coefficient of vegetation is related to the content and composition of pigments in the plant canopy. It is a useful metric for understanding the spatial and temporal dynamics of the absorbed solar radiation, photosynthetic capacity, and productivity of vegetation. Still, its estimation in vivo is challenging due to the large variability induced by numerous features: canopy-related factors, including biochemical and structural characteristics, and factors external to the canopy such as soil background, solar irradiation, and sun-target-sensor geometry conditions. Here we revisit a semi-analytical modeling framework for deriving the light absorption coefficient of plant canopies from reflectance data. The proposed approach is based on the partition of the total light absorption coefficient into photosynthetic and non-photosynthetic pigment components in the canopy, and canopy backscattering. The model-derived absorption coefficient of chlorophyll was compared with field matchups of total canopy chlorophyll content in three crops with contrasting leaf structures, canopy architectures and photosynthetic pathways: maize, soybean, and rice. The model allows for the derivation of absorption coefficient spectra across the photosynthetically active radiation and the red edge spectral regions, as well as accurate estimations of canopy chlorophyll content, both of which are necessary for analyzing the physiological and phenological status, and the canopy-level photosynthetic capacity, of plants. © 2019 Elsevier Inc.