Comparison of Direct and Indirect Determination of Leaf Area Index in Permanent Grassland

Abstract

Indirect, non-destructive methods to derive biophysical parameters, such as leaf area index (LAI), are of major importance for optimal grassland growth modelling and management. In this study, we compared different methods for the estimation of LAI in permanent grassland including (i) two direct methods, (ii) two indirect optical methods (AccuPAR and LAI-2200C), (iii) a proximal (field spectrometer) and a satellite remote sensing approach using Sentinel-2 (S-2) data, both based on radiative transfer modelling (RTM) of vegetation. To consider the seasonal variability of LAI sufficiently, we performed in situ measurements weekly during the entire growing season of 2018 and 2019. The RTM-based methods showed the lowest root-mean-square error (RMSE) when compared with direct green LAI measurements, which ranged from 1.68 to 7.85. The indirect optical methods resulted in higher RMSE values but in similar high correlation coefficients (r). The comparison between the indirect optical methods showed that the AccuPAR and the LAI-2200C highly correlate with a systematic underestimation of the AccuPAR in the upper range of LAI values. As expected, S-2 and the field spectrometer showed the highest correlation (RMSE: 0.40 and r: 0.95). Generally, we observed a significant influence of the seasonal changes of the canopy structure and morphology on the estimation accuracy.