Sistema de processamento de imagens aéreas múlti espectrais para agricultura de precisão

Autores

  • Samy Kharuf-Gutierrez Universidad Central “Marta Abreu” de las Villas
  • Rubén Orozco-Morales Universidad Central Marta Abreu de Las Villas, Santa Clara
  • Osmany de la C. Aday Díaz Estación Territorial de Investigaciones de la Caña de Azúcar
  • Emma Pineda Ruiz Estación Territorial de Investigaciones de la Caña de Azúcar

DOI:

https://doi.org/10.18046/syt.v16i47.3221

Palavras-chave:

Agricultura de precisão; índice de vegetação; infravermelho próximo; Veículo aéreo não tripulado; Sequoia.

Resumo

A agricultura cubana tem uma necessidade crescente de aumentar sua produtividade, e para isso, a agricultura de precisão pode desempenhar um papel fundamental. É necessário, portanto, desenvolver um sistema de processamento de imagens capaz de processar toda a informação dos plantios e calcular de forma satisfatória índices de vegetação, de forma de poder medir com precisão o déficit de nitrogênio, o estresse hídrico e o vigor vegetal, entre outros aspectos, para que a atenção desses aspectos também seja precisa. Este documento relata os resultados de uma pesquisa focada ao desenvolvimento de um procedimento para a obtenção e processamento de imagens aéreas múlti espectrais obtidas desde veículos aéreos não tripulados [VANT], para obter índices de vegetação de plantios de cana-de-açúcar que podem ser correlacionados com o nível de vigor vegetal, o número de hastes ou a massa foliar por parcela. Foi utilizado um VANT USENSE-X8 e seus componentes, um sensor múlti espectral Sequoia e o software de processamento QGIS. O procedimento foi validado experimentalmente.

Biografia do Autor

  • Samy Kharuf-Gutierrez, Universidad Central “Marta Abreu” de las Villas

    Automation Engineer from the Universidad Central “Marta Abreu” de Las Villas [UCLV] (Cuba, 2014). He is a professor at the Department of Automation and Computer Systems from the UCLV’s Faculty of Engineering and member of its Automation, Robotics and Perception Group [GARP]. His areas of professional interest include: multispectral image processing, modeling and control and guidance of unmanned vehicles.

  • Rubén Orozco-Morales, Universidad Central Marta Abreu de Las Villas, Santa Clara

    Engineer in Electronics, Master in Telecommunications (1994) and Ph.D., in Technical Sciences (1998) from the Electrical Engineering School of the Universidad Central de Las Villas (Santa Clara, Cuba). He is a professor at the Department of Automation and Computer Systems of the Faculty of Engineering of the same university and member of the Automation, Robotics and Perception Group [GARP]. His areas of professional interest include image analysis and recognition of patterns in images.

  • Osmany de la C. Aday Díaz, Estación Territorial de Investigaciones de la Caña de Azúcar

    Agronomics Engineer from the Universidad Central de Las Villas (Santa Clara, Cuba and PhD in Technical Sciences (2015) from the Universidad Agraria de la Habana “Fructuoso Rodríguez Pérez”. He works for ETICA the main research entity in matters related with sugar cane in Cuba. His main area of professional interest is vegetal sanitation.

  • Emma Pineda Ruiz, Estación Territorial de Investigaciones de la Caña de Azúcar

    Agronomics Engineer from the Universidad Central de Las Villas (Santa Clara, Cuba, 1981) and PhD in Technical Sciences (2002). She works for ETICA the main research entity in matters related with sugar cane in Cuba. Her main area of professional interest is the edaphology.

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Publicado

2018-10-31

Edição

v. 16 n. 47 (2018): Outubro - Dezembro, 2018

Seção

Original Research

Licença

Esta publicação está licenciada sob os termos da licença CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/deed.pt_BR).