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A weed monitoring system using UAV- IMAGERY and the hough transform

Authors: Pérez-Ortiz, María; Peña Barragán, José Manuel; Torres-Sánchez, Jorge; Hervás-Martínez, César; López Granados, Francisca;

A weed monitoring system using UAV- IMAGERY and the hough transform

Abstract

[ES] Las infestaciones de malas hierbas precisan del uso de herbicidas para controlar la calidad y el rendimiento de los cultivos. Aunque las malas hierbas con frecuencia se distribuyen en rodales o agregados, la práctica más extendida es la aplicación de herbicidas en todo el cultivo, resultando en un aumento de los costes. El control localizado de malas hierbas se hace mediante muestreos en campo, detección próxima o teledetección. En este último caso es necesaria la obtención de mapas de emergencias de malas hierbas en fases fenológicas tempranas para utilizarlos para su control en post-emergencia. Las imágenes remotas de aviones pilotados o satélites no son útiles debido a su baja resolución espacial y temporal. Sin embargo, este no es el caso de los vehículos aéreos no tripulados. Este artículo presenta un nuevo método para monitorización de malas hierbas mediante este tipo de plataformas, mostrando resultados prometedores.

[EN] Usually, weed-infested crops require the use of herbicides as a useful manner of controlling the quality and quantity of crop production. Although there are weed-free areas, the most common approach is to broadcast herbicides entirely over crops fields, resulting in a potential reduction of profits. Recently, patch spraying has allowed the application of site-specific weed management by using precise and timely weed maps at very early phenological stage obtained either by ground sampling or proximal or remote sensing. Remote imagery from piloted planes and satellites are not suitable for this purpose given their low spatial and temporal resolutions; however, unmanned aerial vehicles (UAV) represent an excellent alternatuve. This paper presents a new classification framework for weed monitoring via UAV showing promising results and accurate generalisation in different scenarios.

This work was financed by the Recupera 2020 project (Spanish MINECO and EU-FEDER Funds). Research of Mr. Torres-Sánchez and Dr. Peña was financed by the FPI and Ramón y Cajal programs, respectively. Research of Dr. Gutiérrez and Dr. Hervás-Martínez has been subsidized by the TIN2014-54583-C2-1-R project of the Spanish Ministerial Commission of Science and Technology (MICYT), FEDER funds and the P11-TIC-7508 project of the “Junta de Andalucía” (Spain).

Trabajo presentado en el XV Congreso de la Sociedad Española de Malherbologia (SEMh), celebrado en Sevilla del 19 al 22 de octubre de 2015.

No

Country
Spain
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Keywords

Precision agriculture, Agricultura de precisión, Teledetección, Post-emergence, Unmanned aerial vehicle, Remote sensing, Unmanned aerial vehicles, Post-emergencia, Drones

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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