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Development of a Geospatial Predictive System of Crop Yield in Vineyards - A Case Study in Spain

Authors:
Juan Jose Cubillas
Francisco Feito
Juan Manuel Jurado
David Jurado
Juan Roberto Jimenez
Lidia Ortega
Carlos Enriquez
Antonio Garrido
Maria Isabel Ramos

Keywords: Artificial intelligence; agriculture; crop yield prediction; remote sensing.

Abstract:
This project aims to develop an Artificial Intelligence (AI)-based system for early crop yield prediction in vineyards. The objective is to provide farmers with a reliable tool that allows them to optimize resource planning, reduce risks, and enhance crop sustainability. The methodology integrates multi source and multi-scale data, including historical yield information, multispectral satellite images, and climatic variables, such as temperature, humidity and precipitation, obtained from MODIS and ERA5, from Copernicus services. It employs advanced AI techniques, such as image processing and regression models. A key phase is validating and adjusting the model using high resolution data captured by drones. The expected impact is outstanding accuracy in harvest prediction, which will lead to a significant reduction in uncertainty, greater operational efficiency, and improved grape quality, transforming viticulture into a more predictive and sustainable discipline.

Pages: 7 to 10

Copyright: Copyright (c) IARIA, 2025

Publication date: May 18, 2025

Published in: conference

ISSN: 2308-393X

ISBN: 978-1-68558-269-2

Location: Nice, France

Dates: from May 18, 2025 to May 22, 2025