Estimación de la biomasa en una pradera de kikuyo mediante el uso de sensores remotos

Alvaro A. Bernal; Amanda Acero Camelo; Alex Fernando Gutiérrez

doi:10.22490/21456453.6657

Vol. 15 No. 1 (2024)

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2023-12-19

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Estimation of biomass in a prairie of kikuyu grass using remote sensors

DOI: https://doi.org/10.22490/21456453.6657

Section

Área Agrícola

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Biomasa

Alvaro Bernal Universidad de Cundinamarca

Amanda Acero Camelo Universidad Nacional de Colombia

Alex Fernando Gutiérrez Cooperativa Colanta

Contextualization: The direct measurement of biomass in pastures is the most accurate method, however, it is a destructive and time-consuming method. Knowledge gap: Techniques with the use of remote sensors have recently been investigated to estimate physiological and morphological characteristics in crops based on their optical properties and arrive at an estimation of biomass. It is valuable to evaluate these techniques in perennial forages such as kikuyu (Cenchrus clandestinus).

Purpose: The objective of this study was to develop a methodology to estimate biomasses from their spectral and morphological characteristics, using different sources of remote information.

Methodology: A grazing strip of 1870 m² was subdivided into 27 subplots, where biomass and undisturbed height (ASD) were measured. Aerial photographs were taken with a UAS and a Sentinel 2B satellite image was selected that captured the scene of the study site coinciding with the UAS flight date and field measurements. Using aerial photogrammetry techniques, a digital elevation model (DEM) was calculated to estimate pasture height. The Red Green Blue Vegetation Index (RGBVI) was calculated from the orthophotography and the Normalized Vegetation Difference Index (NDVI) was determined with the satellite image. The height measured in the field was correlated with the height estimated by the DEM using the Pearson coefficient, and the biomass measured in the field was correlated with the NDVI, RGBVI indices, and the height estimated by linear regression.

Results and conclusions: A strong correlation (0.64) was found between the height measured directly and the height calculated using the DEM. The correlation between NDVI and biomass was low (R2= 0.13) and no relationship was found with the RGBVI index (R2= 0.02). Between the height estimated by the DEM and the biomass, a medium relationship was found (R2=0.42), which indicates that this is a promising methodology to replace destructive methods and to provide more precise information in time and space.

Cenchrus clandestinus, drone, grazing management, precision grazing

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Bernal, A., Acero Camelo, A., & Gutiérrez, A. F. (2023). Estimation of biomass in a prairie of kikuyu grass using remote sensors. Revista De Investigación Agraria Y Ambiental, 15(1), 175-190. https://doi.org/10.22490/21456453.6657

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