Modelling Leaf Chlorophyll Content in Coffee (Coffea Arabica) Plantations Using Sentinel 2 Msi Data

摘要

Coffee leaf chlorophyll (ChI) is an important proxy for coffee plant photosynthetic rates, nitrogen content, leaf health and yield potential. Whereas the recently launched Sentinel 2 multi -spectral instrument (MSI) data has great potential for plant condition assessment, the value of its spectral settings at variable spatial resolutions in relation to crop canopy cover on ChI content prediction remains largely unexplored. In this study, we apply an empirical model to estimate coffee leaf ChI with Sentinel 2 MSI data. Results showed that coffee biophysical parameters (height and canopy cover) are significantly influenced by stand age while plant water concentration and total ChI are age invariant. Results further showed that the best modelling results (R^{2=0.69, RMSE=64.4) were achieved when all the bands at 10m spatial resolution with all data were used. We concluded that Sentinel 2 MSI is a valuable dataset for predicting coffee leaf ChI, however, based on our findings, we suggest that finer spatial resolutions of 10m on mature coffee stands should be adopted for better prediction results.}