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<p>Significant advancements in technology have been evident across various sectors in recent years, including medicine, security, and infrastructure. In agriculture, the use of remotely piloted aircraft (RPAs) holds promise for automating and optimizing processes that previously took days or weeks to complete. Monitoring the status of rural properties is crucial for effective planning and decision-making. This study explores the potential of textural characterization using RPAs in areas affected by weed infestations in sugarcane cultivation in the Eastern Amazon. The study area was a sugarcane plantation located within the Pará Pastoril e Agrícola – PAGRISA/SA in Paragominas, PA. Performance was evaluated based on 13 textural characterization measures: Angular Second Moment, Contrast, Correlation, Variance, Inverse Difference Moment, Sum Average, Sum Variance, Sum Entropy, Entropy, Difference Variance, Difference Entropy, Information Measure of Correlation I, and Information Measure of Correlation II, combined with four sizes of moving windows (3, 11, 21, and 31 pixels), at a distance of 1 pixel, and four angular directions (0°, 45°, 90°, and 135°). Among the analyzed textural characterization measures, Sum Average (SA) showed the highest Spearman’s <i>ρ</i> correlation with the true color orthomosaic, when combined with an 11-pixel moving window and a 1-pixel distance, yielding a correlation value of 0.718 and a coefficient of determination of 79.96%. Further detailed studies are needed to compare textural characteristics among themselves, as these combinations may yield new insights and improve classifier accuracy for image segmentation.</p>

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Textural Characterization of Sugarcane Areas with Mucuna Aterrima Infestation Using Remotely Piloted Aircraft in the Eastern Brazilian Amazon

  • 期刊论文

  • 发表日期：

    2025年10月25日

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  • Antonio Rafael Neri dos Santos,
  • Luiz Antonio Soares Cardoso,
  • Carlos Rodrigo Tanajura Caldeira,
  • Lucinda Helena Fragoso Monfort,
  • Antônio Francisco de Brito Nunes Netto,
  • Francisca das Chagas Bezerra de Araújo,
  • Raphael Coelho Pinho,
  • Artur Vinícius Ferreira dos Santos,
  • Fábio Júnior de Oliveira

摘要

Significant advancements in technology have been evident across various sectors in recent years, including medicine, security, and infrastructure. In agriculture, the use of remotely piloted aircraft (RPAs) holds promise for automating and optimizing processes that previously took days or weeks to complete. Monitoring the status of rural properties is crucial for effective planning and decision-making. This study explores the potential of textural characterization using RPAs in areas affected by weed infestations in sugarcane cultivation in the Eastern Amazon. The study area was a sugarcane plantation located within the Pará Pastoril e Agrícola – PAGRISA/SA in Paragominas, PA. Performance was evaluated based on 13 textural characterization measures: Angular Second Moment, Contrast, Correlation, Variance, Inverse Difference Moment, Sum Average, Sum Variance, Sum Entropy, Entropy, Difference Variance, Difference Entropy, Information Measure of Correlation I, and Information Measure of Correlation II, combined with four sizes of moving windows (3, 11, 21, and 31 pixels), at a distance of 1 pixel, and four angular directions (0°, 45°, 90°, and 135°). Among the analyzed textural characterization measures, Sum Average (SA) showed the highest Spearman’s ρ correlation with the true color orthomosaic, when combined with an 11-pixel moving window and a 1-pixel distance, yielding a correlation value of 0.718 and a coefficient of determination of 79.96%. Further detailed studies are needed to compare textural characteristics among themselves, as these combinations may yield new insights and improve classifier accuracy for image segmentation.