Record Details

Aerial Monitoring of Rice Crop Variables using an UAV Robotic System

CGSpace

View Archive Info
 
 
Field Value
 
Title Aerial Monitoring of Rice Crop Variables using an UAV Robotic System
 
Creator Devia, Carlos Andres
Rojas Bustos, Juan Pablo
Petro, Eliel E.
Mondragon, Iván Fernando
Patino, D.
Rebolledo, C.
Colorado, Julian
 
Subject RICE
MACHINE LEARNING
APRENDIZAJE ELECTRÓNICO
PRECISION AGRICULTURE
AGRICULTURA DE PRECISIÓN
IMAGE PROCESSING
TRATAMIENTO DE IMÁGENES
MULTISPECTRAL IMAGERY
IMÁGENES MULTIESPECTRALES
 
Description This paper presents the integration of an UAV for the autonomous monitoring of rice crops. The system integrates image processing and machine learning algorithms to analyze multispectral aerial imagery. Our approach calculates 8 vegetation indices from the images at each stage of rice growth: vegetative, reproductive and ripening. Multivariable regressions and artificial neural networks have been implemented to model the relationship of these vegetation indices against two crop variables: biomass accumulation and leaf nitrogen concentration. Comprehensive experimental tests have been conducted to validate the setup. The results indicate that our system is capable of estimating biomass and nitrogen with an average correlation of 80% and 78% respectively.
 
Date 2019-10-29T20:43:15Z
2019-10-29T20:43:15Z
2019-07
 
Type Journal Article
 
Identifier Devia, Carlos Andres; Rojas Bustos, Juan P.; Petro, Eliel E.; Mondragon, Iván F.; Patino, D.; Rebolledo, C. & Colorado, Julian (2019). Aerial Monitoring of Rice Crop Variables using an UAV Robotic System. In: ICINCO 2019 - International Conference on Informatics in Control, Automation and Robotics. 29-31 Jul. Prague, Czech Republic, 1-7 p.
978-989-758-380-3
https://hdl.handle.net/10568/105568
 
Language en
 
Rights CC-BY-NC-ND-4.0
 
Format 1-7 p.