Quality of forest plantations using aerial images and computer vision techniques

• Autor(a) principal: Garcia da Silva, Arlindo
• Data de Publicação: 2020
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Revista ciência agronômica (Online)
• Texto Completo: http://periodicos.ufc.br/revistacienciaagronomica/article/view/88835
• topic: Remote Sensing. Vegetation index. Drone. Python. Eucalyptus.

Geotechnology has provided several tools that allow the spatial and temporal variability of soils and plants tobe investigated, leading to the consolidation of Precision Agriculture. The great challenge for studies using sensors mountedaboard Remotely Piloted Aircraft (RPA) lies in interpreting the high-dimensional data, since most sensors do not measure thebiometric parameters of a plant directly. Therefore, the aim of the present study was to develop a methodology for using digitalimages (obtained by means of an airborne RGB sensor mounted aboard an RPA) in the quality control of forest plantations,specifically Eucalyptus (Eucalyptus ssp.), planted in a commercial area. A Phantom 4 Pro multirotor RPA was used, equippedwith a 20 Megapixel RGB sensor, acquiring images with 80% and 60% longitudinal and lateral overlap, respectively. Fromthe generated orthomosaic, a Test Area was outlined to be used in developing the processing routine based on computer visiontechniques. In general, the proposed methodology maps the individual location of each plant in the orthomosaic, resulting in amesh that allows the automatic generation of report maps of various silvicultural variables, such as plant count, planting failures,and spacing between rows and plants. In addition to high computer performance, with real-time processing, the methodologywas highly accurate in correctly identifying more than 93% of plants in an area of more than 3,000 plants.