2026-04-14T18:11:43Zhttps://uvadoc.uva.es/oai/request

oai:uvadoc.uva.es:10324/661052024-12-17T08:16:13Zcom_10324_1136com_10324_931com_10324_894col_10324_1218

Gil-Docampo, M. L. Arza-García, M. Ortiz-Sanz, J. Martínez-Rodríguez, S. Marcos Robles, José Luis Sánchez Sastre, Luis Fernando 2024-02-09T18:16:42Z 2024-02-09T18:16:42Z 2019 M. L. Gil-Docampo, M. Arza-García, J. Ortiz-Sanz, S. Martínez-Rodríguez, J. L. Marcos-Robles & L. F. Sánchez-Sastre (2020) Above-ground biomass estimation of arable crops using UAV-based SfM photogrammetry, Geocarto International, 35:7, 687-699, DOI: 10.1080/10106049.2018.1552322 1010-6049 https://uvadoc.uva.es/handle/10324/66105 10.1080/10106049.2018.1552322 7 Geocarto International 35 1752-0762 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 DTM-DSM coupling. Biomass field data confirmed the goodness of fit of the yield-biomass 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. spa info:eu-repo/semantics/restrictedAccess Taylor & Francis Above-ground biomass estimation of arable crops using UAV-based SfM photogrammetry info:eu-repo/semantics/article