Sensors (Oct 2017)

Application of Multilayer Perceptron with Automatic Relevance Determination on Weed Mapping Using UAV Multispectral Imagery

  • Afroditi A. Tamouridou,
  • Thomas K. Alexandridis,
  • Xanthoula E. Pantazi,
  • Anastasia L. Lagopodi,
  • Javid Kashefi,
  • Dimitris Kasampalis,
  • Georgios Kontouris,
  • Dimitrios Moshou

DOI
https://doi.org/10.3390/s17102307
Journal volume & issue
Vol. 17, no. 10
p. 2307

Abstract

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Remote sensing techniques are routinely used in plant species discrimination and of weed mapping. In the presented work, successful Silybum marianum detection and mapping using multilayer neural networks is demonstrated. A multispectral camera (green-red-near infrared) attached on a fixed wing unmanned aerial vehicle (UAV) was utilized for the acquisition of high-resolution images (0.1 m resolution). The Multilayer Perceptron with Automatic Relevance Determination (MLP-ARD) was used to identify the S. marianum among other vegetation, mostly Avena sterilis L. The three spectral bands of Red, Green, Near Infrared (NIR) and the texture layer resulting from local variance were used as input. The S. marianum identification rates using MLP-ARD reached an accuracy of 99.54%. Τhe study had an one year duration, meaning that the results are specific, although the accuracy shows the interesting potential of S. marianum mapping with MLP-ARD on multispectral UAV imagery.

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