Improving early prediction of crop yield in Spanish olive groves using satellite imagery and machine learning.
In the production sector, the usefulness of predictive systems as a tool for management and decision-making is well known. In the agricultural sector, a correct economic balance of the farm depends on making the right decisions. For this purpose, having information in advance on crop yields is an ex...
Saved in:
Main Authors: | M Isabel Ramos, Juan J Cubillas, Ruth M Córdoba, Lidia M Ortega |
---|---|
Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2025-01-01
|
Series: | PLoS ONE |
Online Access: | https://doi.org/10.1371/journal.pone.0311530 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Improving early prediction of crop yield in Spanish olive groves using satellite imagery and machine learning
by: M. Isabel Ramos, et al.
Published: (2025-01-01) -
Surveying Nearshore Bathymetry Using Multispectral and Hyperspectral Satellite Imagery and Machine Learning
by: David Hartmann, et al.
Published: (2025-01-01) -
Drone imagery dataset for early-season weed classification in maize and tomato cropsDIGITAL.CSIC
by: Gustavo A. Mesías-Ruiz, et al.
Published: (2025-02-01) -
Spatial and temporal heterogeneity of soil respiration in a bare-soil Mediterranean olive grove
by: S. Aranda-Barranco, et al.
Published: (2025-02-01) -
Nitrogen Dioxide Monitoring with Satellite Imagery over Ankara, Turkey
by: Maryam Zare Shahne, et al.
Published: (2024-12-01)