Temporal analysis of the vineyard phenology from remote sensing data using Google Earth Engine

Precision Agriculture (PA) has a fundamental role in the sustainability of agricultural systems, supporting decision-making of agricultural crops, increasing yield and quality in production. In the present research a PA approach for viticulture was made combining remote sensing data and robotic monitoring. With this approach it was intended to perform a spatial-temporal analysis of the grapevine phenology, according the 3 periods of the grape's biological cycle reproductive cycle, peak of the season and vegetative dormancy - corresponding to the years of 2017/18, for a specific area of the Green Wine Region, from Celorico de Basto (Portugal). The proposed methodology is based in the automation of spatial analyses through Geographical Information Systems (GIS), Google Earth Engine (GEE) and Python programming language. GEE was used for image acquisition and processing data of several indices, as Normalized Difference Vegetation Index (NDVI), Green Normalized Difference Vegetation Index (GNDVI) and Visible Atmospherically Resistant Index ( VARI). Regarding the geoprocessing of environmental factors, it was considered the following parameters: precipitation, temperature and soil moisture. Afterwards, NDVI was selected for a space-time analysis of the vineyard phenology, once this index represents a close dynamic to the vineyard biological cycle. From the relation between environmental factors and NDVI it was possible to interpret the space-time dynamics of the vineyard phenology. Finally, a spatial interpolation of yield and NDVI was made to understand the influence of NDVI in the yield. It can be assumed that the NDVI does not have a statistically significant influence on vineyard yield.