Biomass Estimation of Agave durangensis Gentry Using High-Resolution Images in Nombre de Dios, Durango

Abstract

The high demand for distilled agave products reduces wild populations. The use of geospatial technologies such as unmanned aerial vehicles (UAVs) offer enormous benefits in spatial and temporal resolution and lower costs than traditional direct field observation techniques for natural resource monitoring. The objective was to estimate the green biomass (Wt) of Agave durangensis Gentry using high-resolution images obtained by a UAV in Nombre de Dios, Durango. Random sampling was performed in the agave area. A Pearson correlation analysis was performed, followed by a regression analysis. The results showed that NDVI was the most correlated (r = 0.65). The regression analysis showed that the model obtained explains 59% (RMSE = 32.06 kg) of the total variability in the estimation of green biomass (Wt) of agave using images derived from the UAV. The best estimate was achieved with B1, B2, NDVI, GNDVI, EVI2, and SAVI as predictor variables. High-resolution images were shown to be a tool for estimating Wt of Agave durangensis Gentry.