Above-ground biomass estimation of arable crops using UAV-based SfM photogrammetry

Methods of estimating the total amount of above-ground biomass (AGB) in crop fields are generally based on labourious, random, and destructive in situ sampling. This study proposes a methodology for estimating herbaceous crop biomass using conventional optical cameras and structure from motion (SfM)...

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Detalles Bibliográficos
Autores: Gil Docampo, María de la Luz, Arza García, Marcos, Ortiz Sanz, Juan, Martínez Rodríguez, Santiago, Marcos Robles, José Luis, Sánchez Sastre, Luis Fernando
Tipo de recurso: artículo
Fecha de publicación:2018
País:España
Institución:Universidad de Santiago de Compostela (USC)
Repositorio:Minerva. Repositorio Institucional de la Universidad de Santiago de Compostela
Idioma:inglés
OAI Identifier:oai:minerva.usc.gal:10347/17888
Acceso en línea:http://hdl.handle.net/10347/17888
Access Level:acceso abierto
Descripción
Sumario:Methods of estimating the total amount of above-ground biomass (AGB) in crop fields are generally based on labourious, random, and destructive in situ sampling. This study proposes a methodology for estimating herbaceous crop biomass using conventional optical cameras and structure from motion (SfM) photogrammetry. The proposed method is based on the determination of volumes according to the difference between a digital terrain model (DTM) and digital surface model (DSM) of vegetative cover. A density factor was calibrated based on a subset of destructive random samples to relate the volume and biomass and efficiently quantify the total AGB. In all cases, RMSE Z values less than 0.23 m were obtained for the DTMDSM coupling. Biomass field data confirmed the goodness of fit of the yieldbiomass estimation (R2=0,88 and 1,12 kg/ha) mainly in plots with uniform vegetation coverage. Furthermore, the method was demonstrated to be scalable to multiple platform types and sensors