Canopy Height Estimation of Three Sugarcane Varieties Using an Unmanned Aerial Vehicle (UAV)

Abstract

The objective of this study is to estimate the canopy height of three sugarcane varieties at different growth stages, with UAV data and to evaluate its relationship with two vegetation indices (VIs) (NDVI and EVI) at different spatial resolutions (3m, 10m and 30m). The indices were calculated using images from the PlanetScope, Sentinel-2, and Landsat 8 satellites, acquired as close as possible to the UAV imaging date. The estimated canopy height for each field was obtained by subtracting the Digital Surface Model (DSM) from the Digital Terrain Model (DTM), built by the Structure from Motion (SfM) technique with UAV RGB images as input. The average from each estimated height was compared with the average measured in the field, to verify the accuracy of the model. Both Pearson’s correlation and the Determination Coefficient (R²) were calculated between the estimated heights and the VIs. The average estimated canopy height and measurements in the field were different (p<0.05), with the model generally underestimating the height. However, the plantation’s surface models portrayed the spatial variability within the field. The use of GCPs is mandatory to reduce errors in estimation. Regarding the indices, the spatial resolution did not influence the correlation analysis, with NDVI showing higher values than EVI, except for area A. However, all values, for both coefficients, were below 0.5 for all areas. Despite that, a temporal analysis is necessary to improve the relationship between the canopy height and VIs. The potential of UAV data as a proxy to zonal management should be addressed in future studies.