An Experimental Comparison for the Identification of Weeds in Sunflower Crops via Unmanned Aerial Vehicles and Object-Based Analysis

  • María Pérez-OrtizEmail author
  • Pedro Antonio Gutiérrez
  • Jose Manuel Peña
  • Jorge Torres-Sánchez
  • César Hervás-Martínez
  • Francisca López-Granados
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9094)


Weed control in precision agriculture refers to the design of site-specific control treatments according to weed coverage and it is very useful to minimise costs and environmental risks. The crucial component is to provide precise and timely weed maps via weed monitoring. This paper compares different approaches for weed mapping using imagery from Unmanned Aerial Vehicles in sunflower crops. We explore different alternatives, such as object-based analysis, which is a strategy that is spreading rapidly in the field of remote sensing. The usefulness of these approaches is tested by considering support vector machines, one of the most popular machine learning classifiers. The results show that the object-based analysis is more promising than the pixel-based one and demonstrate that both the features related to vegetation indexes and those related to the shape of the objects are meaningful for the problem.


Unmanned Aerial Vehicles Object-based analysis Weed mapping Image segmentation Support vector machines 


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • María Pérez-Ortiz
    • 1
    Email author
  • Pedro Antonio Gutiérrez
    • 2
  • Jose Manuel Peña
    • 1
  • Jorge Torres-Sánchez
    • 1
  • César Hervás-Martínez
    • 2
  • Francisca López-Granados
    • 1
  1. 1.Institute for Sustainable AgricultureCSICCórdobaSpain
  2. 2.Department of Computer Science and Numerical AnalysisUniversity of CórdobaCórdobaSpain

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