Carbon estimation in an integrated crop-livestock system with imaging sensors aboard unmanned aerial platforms

• Published in: Remote sensing applications 2022-11, Vol.28, p.100867, Article 100867
• Main Authors: de Lima, Gabriella Santos Arruda, Ferreira, Manuel Eduardo, Madari, Beata Emoke, Carvalho, Márcia Thaís de Melo
• Format: Article
• Language: English
• Subjects: Biomass; Carbon stock; Drones; Unmanned aerial vehicle; Vegetation index
• ISSN: 2352-9385; 2352-9385
• DOI: 10.1016/j.rsase.2022.100867

Biomass and carbon estimates in integrated crop–livestock (iLP) systems remain scarce. Recently, sensors aboard an unmanned aerial vehicle (UAV) have been used for such estimation and can represent an efficient and low-cost method for acquiring accurate remote-sensing data. This study aimed to estimate the relationship between vegetation indices (VIs) and carbon stock in an upland rice field intercropped with Brachiaria, an exotic grass species in the savanna ecosystem of Brazil (Cerrado biome), using multispectral aerial imaging with a high cartographic scale. The research was conducted in an experimental iLP system located at the Brazilian Agricultural Research Corporation (Embrapa Arroz e Feijão), Goiás State. During the data collection stage, flights were conducted with a fixed-wing UAV (eBee Plus RTK) on the same day or close to collecting biomass samples in the field. In the processing step, a correlation was performed between the normalized difference vegetation index (NDVI), simple ratio (SR), soil-adjusted vegetation index (SAVI), and modified photochemical reflectance index (MPRI) VIs and the biomass measured in the field. The results indicated that the vegetation index (VI) that used the near-infrared (NIR) band showed a stronger correlation with biomass than the VI that used only the visible band information. All VIs were significantly correlated with the estimated field biomass (P