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Detection of orange plantation lines using high-resolution orthomosaic and convolutional neural network

Grant number: 23/02772-2
Support Opportunities:Scholarships in Brazil - Scientific Initiation
Effective date (Start): April 01, 2023
Effective date (End): March 31, 2024
Field of knowledge:Physical Sciences and Mathematics - Geosciences - Geodesy
Principal Investigator:Aluir Porfírio Dal Poz
Grantee:Letícia Rodrigues dos Santos
Host Institution: Faculdade de Ciências e Tecnologia (FCT). Universidade Estadual Paulista (UNESP). Campus de Presidente Prudente. Presidente Prudente , SP, Brazil
Associated research grant:21/06029-7 - High resolution remote sensing for digital agriculture, AP.TEM

Abstract

This working plan proposes the use of orthomosaics, produced from very high resolution (circa 10 cm) RGB images, acquired via the Unmanned Aerial Vehicle (UAV) platform, to detect rows or lines of orange plantation. The image analysis method to be used is based on deep learning, known as convolutional neural networks (CNN). The basic idea to be explored in CNN learning is that there will be no plants outside the plantation line and, consequently, plantation lines cannot be formed without there being plants. The orthomosaic to be used in the experiments corresponds to a rural property located in the municipality of Santa Cruz do Rio Pardo-SP. This orthomosaic shows a field of orange plantation lines, where the plants usually appear connected to each other. The results obtained will be evaluated based on quantitative quality metrics, such as the IoU (Intersection over Union), Precision, Recall, and F1-score.

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