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dc.contributor.authorSinde González, Ízar
dc.contributor.authorGil Docampo, María de la Luz
dc.contributor.authorArza García, Marcos
dc.contributor.authorGrefa Sánchez, José
dc.contributor.authorYánez Simba, Diana
dc.contributor.authorPérez, Patricio
dc.contributor.authorAbril Porras, Víctor Hugo
dc.identifier.citationInternational Journal of Applied Earth Observation and Geoinformation, 101 (2021), 102355
dc.description.abstractPastures account for more than 56% of the total agricultural area of Ecuador and constitute the main food source for livestock. Hence, the agile, affordable, and reliable quantification of aboveground biomass (AGB) is an essential task in grazing utilization and management. In this paper, a method to estimate the AGB via aerial photogrammetry with a low-cost UAV multirotor is proposed. Digital terrain models and crop surface models were generated from data captured during two flights at different times, and the volume between them was calculated. An empirical relationship between volume and dry biomass was obtained by harvesting and weighing some samples and deriving a density factor (DF). The method was tested over 54 plots with different types of forage under differential fertilization treatments. Fertilized annual ryegrass exhibited the best growth and highest biomass (2632 kg/ha). The estimation and calculation of the crop volume via UAV-based photogrammetry saves time and generates notably precise (R2 = 0.78) information on the dry biomass
dc.rights© 2021 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (
dc.rightsAtribución 4.0 Internacional
dc.subjectCultivated pastures
dc.subjectPrecision agriculture
dc.subjectAboveground biomass
dc.titleBiomass estimation of pasture plots with multitemporal UAV-based photogrammetric surveys
dc.contributor.affiliationUniversidade de Santiago de Compostela. Departamento de Enxeñaría Agroforestal

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© 2021 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (
Except where otherwise noted, this item's license is described as  © 2021 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (

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