Estimating Vegetation Volume of Coffee Crops Using Images From Unmanned Aerial Vehicles

Abstract

Tree crops, such as Arabica coffee (Coffea arabica L.), present enormous technical challenges in terms of pesticide application. The correct deposition and distribution of the active ingredient throughout the aerial part of these plants depends on knowledge of the canopy volume, but manually determining this volume is time consuming and imprecise. The objectives of this study were to develop a method to determine the vegetation volume of coffee crops from digital images captured by camera onboard unmanned aerial vehicles and to compare this approach with traditional vegetation volume estimation (tree row volume (TRV) method). Manual measurements of the canopy volume of four coffee cultivation areas were compared with data obtained using the method presented in this paper. It was concluded that the vegetation volume of coffee trees, a highly important variable in defining pesticide application techniques (in addition to other uses), could be determined in a practical and precise way by digitally processing the images captured by unmanned aerial vehicles. The method is fast and permits the assessment of large areas. Furthermore, estimates based on this method and the traditional TRV method were not significantly different.

Determinação do peso da matéria verde do milho através da análise de imagens / Determination of corn green matter weight through image analysis

“…Então produtor rural que deseja conhecer sua expectativa de produtividade, pode fazer um voo sobre a área com um ARP, determinar o volume da vegetação em seguida o peso/kg Matéria verde usando a equação e calcular quais recursos serão empregados para uma boa colheita, vale lembrar que esse recurso é importante também quando se fala em análise de um grande número de parcelas, grandes empresas chegam a avaliar milhares de parcelas de híbridos de milho por ano esse recurso deixaria o processo mais ágil e eficiente. Cunha et al (2019) estudando o volume da vegetação em quatro áreas de café com imagens de um ARP conseguiu determinar com precisão o volume da vegetação do cafeeiro para dimensionamentos de aplicação de defensivos com base no índice de área foliar.…”

Review on unmanned aerial vehicles, remote sensors, imagery processing, and their applications in agriculture

“…The 3D characterizations such as crop height or volume derived from LiDAR or high-resolution color cameras combined with conventional 2D data could also offer an avenue for increasing the accuracy of these estimates (Chatterjee, Olson, Franzen, & Day, 2019). Finally, incorporating both plant height and NDVI has been used to improve biomass estimation accuracy (Pena et al (2018), and a method to produce biomass estimates utilizing a "Volume Calculator" within the software Pix4D also generated high accuracy biomass estimations (da Cunha, Neto, Matheus, & Hurtado, 2019).…”

Determining the Leaf Area Index and Percentage of Area Covered by Coffee Crops Using UAV RGB Images

“…In addition to [2], other authors have used equation (1) in an adapted manner to estimate the volume or LAI of coffee trees. The authors of [46] used equation (1) to conclude that it is possible to reliably determine the volume of coffee vegetation by digitally processing the images captured by UAVs.…”