Abstract
ABSTRACT The study aimed to characterize the spatial structure of variability of biophysical indexes of vegetation through images obtained by Unmanned Aerial Vehicles under strong heterogeneity and anisotropy, using geostatistical procedures. Plots with different types and densities of culture were evaluated in a didactic vegetable garden. Five vegetation indexes obtained from aerial multispectral camera images were evaluated parallel with geostatistical analysis and anisotropy investigation for multiscale spatial modeling. For the studied domain, geometric anisotropy was identified for the biometric indexes. The spherical model presented a better fit when anisotropy was not considered, whereas the exponential model had the best performance in the anisotropic analysis. Contrasting targets were better identified in multispectral images and considering anisotropy. The Soil-Adjusted Vegetation Index is recommended for similar applications.
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