Remote estimation of the fraction of absorbed photosynthetically active radiation for a maize canopy in Northeast China

Abstract

Aims: Accurate remote estimation of the fraction of absorbed photosynthetically active radiation (fAPAR) is essential for the light use efficiency (LUE) models. Currently, one challenge for the LUE models is lack of knowledge about the relationship between fAPAR and the normalized difference vegetation index (NDVI). Few studies have tested this relationship against field measurements and evaluated the accuracy of the remote estimation method. This study aimed to reveal the empirical relationship between NDVI and fAPAR and to improve algorithms for remote estimation of fAPAR. Methods: To investigate the method of remote estimation of fAPAR seasonal dynamics, the CASA (Carnegie-Ames-Stanford Approach) model and spectral vegetation indices (VIs) were used for in situ measurements of spectral reflectance and fAPAR during the growing season of a maize canopy in Northeast China. Important Findings: The results showed that the fAPAR increased rapidly with the day of year during the vegetative stage, it remained relatively stable at the stage of reproduction, and finally decreased slowly during the senescence stage. In addition, fAPARgreen [fAPARgreen = fAPAR x (green LAI/green LAImax)] showed clearer seasonal trends than fAPAR. The NDVI, red-edge NDVI, wide dynamic range vegetation index, red-edge position (REP) and REP with Sentinel-2 bands derived from hyperspectral remote sensing data were all significantly positively related to fAPARgreen during the entire growing season. In a comparison of the predictive performance of VIs for the whole growing season, REP was the most appropriate spectral index, and can be recommended for monitoring seasonal dynamics of fAPAR in a maize canopy.