Canopy chlorophyll content and LAI estimation from Sentine1-2: Vegetation indices and Sentine1-2 Leve1-2A automatic products comparison

The aim of this work is to analyze different methodologies for the estimation of leaf area index (LAI) and canopy chlorophyll content (CCC), using the Sentine1-2 satellite. LAI and CCC are biophysical parameters indicator of crop health state and fundamental in the productivity prediction. The purpose is to define the most optimal LAI and CCC estimation method for operational use in the monitoring of agricultural areas. Moreover, the CCC and LAI automatic products obtained directly through the Sentinel Application Platform Software (SNAP) biophysical processor and Sentine1-2 images by means of an artificial neural network (ANN) are validated. On the other hand, common vegetation indices use…