Monitoring crop phenology applying biophysical indices from Sentinel-2 data: the case of Thessaly region in Greece

Abstract

The newest Earth Observation optical sensors, such as Sentinel-2, provide global biophysical products and vegetation indices at high spatial (decametric or twentimetric resolution) and temporal resolution (about 5 days retrieval). These biophysical parameters are essential for constant crop status monitoring at local scale. Optimizing the water use for irrigation, the weed mapping, quantifying ground above biomass and crop yield production, are some of the benefits of biophysical parameters in agriculture. This research investigates the crop status during the 2021’s growing season in Thessaly agricultural area in Greece. Thus, in maize, biophysical variables, and vegetation indices, that is, Leaf Area Index (LAI), fraction of absorbed photosynthetically active Radiation (FAPAR), Fraction of Vegetation Cover (FVC), Leaf Chlorophyll content (Cab), Canopy Water Content (CWC), Normalized Difference Vegetation Index (NDVI) and Normalized Difference Red Edge Index (NDRedEdge) are retrieved. The PROSAIL radiative transfer model by artificial neural network approach is employed (available of the free SNAP® software) to retrieve the biophysical parameters from Sentinel-2 multispectral imagery. The monitoring of the abovementioned biophysical variables during the growth period of maize crop shows a uniform behavior. Finally, high consistency among vegetation parameters confirms the usefulness of Sentinel-2 products in agriculture.Keywords: Biophysical indices; phenological stages; monitoring maize crop; Mediterranean agroecosystems

Plant phenotyping relevance

Sentinel-2画像とPROSAIL・人工ニューラルネットワークを用いて、トウモロコシのLAI、FAPAR、葉面積・水分・クロロフィルなどの植物形質を推定するワークフローが中心であり、単なる生物学的実験のルーチン測定ではない。

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