Aerial Identification of Fruit Maturity in Amazonian Palms via Plant-Canopy Modeling

Research output: Contribution to journalArticlepeer-review

Abstract

UAV-based multispectral imagery was used to characterize and associate the canopy features of the Moriche palm with the maturity state of its fruits, by correlating variations in the palm’s reflectance at different wavelengths throughout the phenological cycle. Several approaches for feature extraction were compared based on vegetation indices and graph-based models. A comprehensive dataset was collected and labeled, containing spatial–temporal variations in the features. Experimental results reported an accuracy of 72% in the estimation of the fruit maturity state, applying the proposed system to the dense forests of Colombia Amazonian region. Also, this UAV-based vision system enables monitoring, inventorying, palm identification, and fruit maturity identification, providing support to the local indigenous organizations of the Amazon.

Original languageEnglish
Article number3752
JournalRemote Sensing
Volume15
Issue number15
DOIs
StatePublished - Aug 2023

Keywords

  • UAV
  • deep learning
  • dense forests
  • graph-based models
  • mauritia flexuosa palm
  • vegetation indices

Fingerprint

Dive into the research topics of 'Aerial Identification of Fruit Maturity in Amazonian Palms via Plant-Canopy Modeling'. Together they form a unique fingerprint.

Cite this