A review on the use of Unmanned Aerial Vehicles and imaging sensors for monitoring and assessing plant stresses.
Abstract: Unmanned aerial vehicles (UAVs) are becoming a valuable tool to collect data in a variety of contexts. Their use in agriculture is particularly suitable, as those areas are often vast, making ground scouting difficult, and sparsely populated, which means that injury and privacy risks are n...
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2019 |
| País: | Brasil |
| Institución: | Empresa Brasileira de Pesquisa Agropecuária (Embrapa) |
| Repositorio: | Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) |
| Idioma: | inglés |
| OAI Identifier: | oai:www.alice.cnptia.embrapa.br:doc/1108655 |
| Acceso en línea: | http://www.alice.cnptia.embrapa.br/alice/handle/doc/1108655 |
| Access Level: | acceso abierto |
| Palabra clave: | Imagem de sensor Stress de planta Drone Crop Orchard Unmanned aerial systems Agricultura de Precisão Stress Precision agriculture Unmanned aerial vehicles |
| Sumario: | Abstract: Unmanned aerial vehicles (UAVs) are becoming a valuable tool to collect data in a variety of contexts. Their use in agriculture is particularly suitable, as those areas are often vast, making ground scouting difficult, and sparsely populated, which means that injury and privacy risks are not as important as in urban settings. Indeed, the use of UAVs for monitoring and assessing crops, orchards, and forests has been growing steadily during the last decade, especially for the management of stresses such as water, diseases, nutrition deficiencies, and pests. This article presents a critical overview of the main advancements on the subject, focusing on the strategies that have been used to extract the information contained in the images captured during the flights. Based on the information found in more than 100 published articles and on our own research, a discussion is provided regarding the challenges that have already been overcome and the main research gaps that still remain, together with some suggestions for future research. |
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