Predicting carob tree physiological parameters under different irrigation systems using Random Forest and Planet satellite images.

ABSTRACT:

Introduction

In the context of climate change, monitoring the spatial and temporal variability of plant physiological parameters has become increasingly important. Remote spectral imaging and GIS software have shown effectiveness in mapping field variability. Additionally, the application of machine learning techniques, essential for processing large data volumes, has seen a significant rise in agricultural applications. This research was focused on carob tree, a drought-resistant tree crop spread through the Mediterranean basin. The study aimed to develop robust models to predict the net assimilation and stomatal conductance of carob trees and to use these models to analyze seasonal variability and the impact of different irrigation systems.

Methods

Planet satellite images

SUBMITTER: Garofalo SP 

PROVIDER: S-EPMC10989058 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature