SCAVIHO: Scalable Vegetation Index and Harvesting Forecaster
We broaden the interpretation of intermediate values of NDVI corresponding to the growing stage of a crop with the aim of helping farmers to assess the growth evolution. NVDI extracted from the imagery from the satellite Sentinel-2 for 4 years, for 11 plots in Calahorra, La Rioja, Spain, for two different varieties of grapevines: Tempranillos and Garnacha; where the different phenological stages are known.
Categories
What is the challenge that is being addressed?
NDVI (Normalized Difference Vegetation Index) is a valuable tool used in precision agriculture to assess the overall health of a crop's canopy, with values ranging from 0 to 1. However, intermediate NDVI values during the growing stage are challenging for farmers to interpret, which is where AI can provide valuable assistance. The main objective of the project is to broaden the interpretation of these intermediate values and provide a scale according to the phenological status of the crop.
What is the AI solution the project has implemented?
The implemented AI solution is a valuable real time tool for farmers, allowing them to select a specific plot and date and displaying the corresponding NDVI values extracted from the satellite image. The NDVI values can be manually scaled by modifying their range, which adapts the index colors represented on the map to the selected scale. Overall, this tool enables farmers to visualize and interpret NDVI data more effectively during the growing period, helping them make more informed decisions for their crops.
Who helped implement the AI solution?
This solution is implemented in the context of SCAVIHO, a winning project from the AI4Copernicus 1st Open Call. The consortium consists of Encore Lab and Castillo de Maetierra, while the results of the project are available here and here.
