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Improved Prediction of Olive Crop Yield Using Satellite Imagery

Authors:
M. Isabel Ramos
Lidia Ortega
Angel Calle
Ruth Cordoba
Juan J. Cubillas

Keywords: olive crop; predictive modeling; multi-source data; satellite imagery.

Abstract:
Agriculture is one of the strategic economic and social sectors in many countries. In Spain, agriculture has been and continues to be a fundamental sector on which the development of the rest of the sectors depends to a large extent. However, there are many factors that influence its performance, some are dependent on the farmer and others, such as the effects of climate change, do not depend on this. Therefore, crop yields are not always easy to forecast, especially not at an early stage, i.e. before any investment is made for the new cropping season. A case example is presented here in the olive grove in Andalusia, Spain. The objective is to analyze the most influential predictor variables on an early predictive model and the contribution, in this case, of data from satellite images.

Pages: 9 to 13

Copyright: Copyright (c) IARIA, 2024

Publication date: May 26, 2024

Published in: conference

ISSN: 2308-393X

ISBN: 978-1-68558-168-8

Location: Barcelona, Spain

Dates: from May 26, 2024 to May 30, 2024