The Use Remotely Piloted Aircraft in Counting Agricultural and Forestry Plants: a Systematic Review

Authors

DOI:

https://doi.org/10.11137/1982-3908_2025_48_64062

Keywords:

RPAS, Machine learning, Algorithms

Abstract

In recent years, plant counting using data collected by sensors embedded in remotely piloted aircraft systems (RPAS), combined with machine learning algorithms, has become popular in the agroforestry sector, especially in crop planning, crop production estimation, among other applications. This study aimed to perform a systematic review of the literature on plant counting in the agricultural and forestry sector that uses data from sensors embedded in RPAS. We sought to identify the principal bibliometric indicators of scientific production and, through content analysis, the main characteristics and trends of the studies. A total of 33 scientific articles obtained on the Scopus and Web of Science platforms were used. Then, a content qualitative analysis of each article was conducted to identify the main thematic categories: agricultural and forest species, platform and sensors, software, and algorithm. There was an increase in scientific publications as of 2017. The USA presented the higher number of researches performed, with eight publications. There was a significant presence of RGB (Red, Green and Blue) sensors followed by multispectral. The algorithms Convoluctional Neural Network (CNN), Structure from Motion (SfM), and K-means stood out for the recurrence of use, either singularly or associated. Studies with this purpose drive new research development, where this technology utilization is revealed as a potential instrument to understand the usage trends, subsidize and encourage the information acquisition, promoting improvements and progress for research in the agroforestry scope.

Author Biographies

Roberta Aparecida Fantinel, Universidade Federal do Espírito Santo, Departamento de Ciências Florestais

Universidade Federal do Espírito Santo, Departamento de Ciências Florestais, Jerônimo Monteiro, ES, Brasil

Rudiney Soares Pereira, Universidade Federal de Santa Maria

Forest Engineer, Master in Agricultural Engineering and PhD from the Federal University of Paraná in the area of ​​Forest Management, Image Processing in 1995. Currently, he is Professor of Remote Sensing at the Federal University of Santa Maria, RS. He published 94 articles in specialized journals, 124 papers in the annals of national and international events. He presented scientific works in Brazil, Argentina, Chile, Australia, Morocco, Italy and Finland. He supervised 92 Specialization, Master and Doctorate works. He served as Adviser to the Regional Council of Engineering and Architecture CREA-RS, for two consecutive terms between the years 1993 and 1997. Interacted with 149 collaborators in the authorship and co-authorship of scientific works. The most frequent terms in the context of its scientific and technological production are: Remote Sensing, Image Processing, Forest Resources, Water Resources, Land Use, Modeling the Dynamics of Use and Land Cover and Free Software. He performed activities of co-orientation and research collaborator at UFPel (Federal University of Pelotas) in Soil Science, UFRGS (Federal University of Rio Grande do Sul) in the Post-Graduation in Remote Sensing and Technical-Scientific Cooperation with EMBRAPA- CPACT. He is the leader of the CNPq Research Group, called Modeling the Dynamics of Land Use and Coverage. He is currently a Professor and Advisor in the Graduate Program in Forest Engineering, master's and doctoral level. Ad-Doc Consultant of the Ciência Rural Magazines, Forest Science, Natural and Exact Sciences and Geodetic Sciences Series.

Fernando Coelho Eugenio, Universidade Federal dos Vales do Jequitinhonha e Mucuri

Adjunct Professor at the Federal University of Vales do Jequitinhonha and Mucuri – UFVJM (Brazil). Former Adjunct Professor at the Federal University of Santa Maria - UFSM. Permanent Professor of the PPG in Forestry Sciences UFVJM. Permanent Professor of the PPG in Plant Production - UFVJM. Forestry Engineer from the Federal University of Espírito Santo (2013). Occupational Safety Engineer from Faculdade Cândido Mendes (2015). Master in Forestry Sciences from the Federal University of Espírito Santo (2014). Doctor in Forestry Sciences from the Federal University do Espírito Santo (2017). Sandwich PhD at the University of Barcelona, Spain (2015-2016). Currently his research aims to integrate the use of deep learning algorithms and very high spatial resolution images obtained by RPAS to solve problems encountered in the day-to-day activities of forestry and agricultural companies. Precision Forestry. Digital agriculture. - Smart Farm.

Ana Caroline Paim Benedetti, Universidade Federal de Santa Maria

Adjunct Professor III at the Polytechnic College of the Federal University of Santa Maria, Brazil where she works as a teacher and researcher in the Specialization Courses in Geomatics, Specialization in Environmental Education, Technology in Geoprocessing and Environmental Technician. Graduated in Forestry Engineering (2003) from the Federal University of Santa Maria (UFSM), Master's Degree (2006) and Doctorate (2010) from the Graduate Program in Forestry Engineering at UFSM in which the objective was to apply dynamic spatial modeling techniques to simulate changes in forest cover in regions of the Pampa Biome. She was an instructor in the GPS (Global Positioning System) course at the National Rural Learning Service (SENAR-RS) between 2007 and 2009. She was a professor in the Forest Engineering and Environmental Management courses at the Federal University of Pampa between 2009 and 2012, developing projects research in the area of ​​temporal analysis of land use and coverage and analysis of vegetation; she taught disciplines in the area of ​​Geoprocessing and Remote Sensing. Currently she teaches the disciplines of Environmental Analysis and Applied GIS for the Specialization Course in Geomatics, Remote Sensing, Digital Image Classification and Dynamic Spatial Modeling for the Higher Course in Technology in Geoprocessing. She coordinates and guides research projects that involve the use of Geoprocessing techniques for environmental analysis and the use of Remote Sensing to monitor vegetation in Rio Grande do Sul.

Juliana Marchesan, Secretaria da Agricultura Pecuária e Desenvolvimento Rural

PhD in Forestry Engineering from Federal University of Santa Maria, Brazil. Currently, she is Agricultural and Forestry Analyst in the Department of Agricultural Diagnosis and Research at the Secretariat of Agriculture, Livestock, Sustainable Production and Irrigation (SEAPI/RS) the state of Rio Grande do Sul, Brazil. Her research include geoprocessing, remote sensing, artificial intelligence, forest measurement and landscape analysis

Elenice Broetto Weiler, Universidade Federal de Santa Maria

another in Forestry Engineering from the Federal University of Santa Maria (2017-2021). Master in Forestry Engineering from the Federal University of Santa Maria (2015-2017). Graduated in Forestry Engineering from the Federal University of Santa Maria (2010-2015). Graduated from the Special Graduation Program for Teacher Training for Professional and Technological Education (PEG) at the Federal University of Santa Maria (2017-2018). Currently studying Specialization in Environmental Education at the Federal University of Santa Maria (2021-Current) and studying Agronomy at the Federal Institute Farroupilha - Santo Augusto Unit (2023-Current). Main topics of interest: forestry and agricultural resources, with an emphasis on environmental planning, water resources, river basin management and erosion processes, geoprocessing and the environment, forestry and regional development, economics and forestry policies.

Sally Deborah Pereira da Silva, Universidade Federal de Santa Maria

Forestry Engineer from the State University of Pará, Campus VI Paragominas (2014-2019). Master in Forestry Engineering from the Federal University of Santa Maria (2020-2022). She is currently a PhD candidate in Forestry Engineering at the Federal University of Santa Maria, working in the line of applied geomatics research.

Fernanda Dias dos Santos, Casa Familiar Rural, Caibi, Santa Catarina

Technologist in Environmental Management from the Northern University of Paraná (2012-2014), Forestry Engineer from the Federal University of Santa Maria, Campus Frederico Westphalen (2011-2015), Master in Forestry Engineering from the Federal University of Santa Maria (2016-2018), Engineer of Occupational Safety from the Franciscan University (2020-2021), Degree in Natural Resources from R2 Pedagogical Training (2022), PhD in Civil Engineering from the Federal University of Santa Maria (2019 - 2023). Member of the Water Resources Management Research Group - GERHI, developing research activities with an emphasis on Natural Engineering and Water Resources, working with herbicides as soil, water and plant contaminants. Teacher of the Technical Course in Agriculture at Casa Familiar Rural, Caibi, SC.

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2025-04-23

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Fantinel, R. A. (2025) “The Use Remotely Piloted Aircraft in Counting Agricultural and Forestry Plants: a Systematic Review”, Anuário do Instituto de Geociências. Rio de Janeiro, BR, 48. doi: 10.11137/1982-3908_2025_48_64062.

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Vol. 48 (2025): Anuário do Instituto de Geociências

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Environmental Sciences

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