Influence of Spatial Resolution for Vegetation Indices’ Extraction Using Visible Bands from Unmanned Aerial Vehicles’ Orthomosaics Datasets

The consolidation of unmanned aerial vehicle (UAV) photogrammetric techniques for campaigns with high and medium observation scales has triggered the development new application areas. Most these vehicles are equipped common visible-band sensors capable mapping areas interest at various spatial resolutions. It is often necessary to identify vegetated masking purposes during postprocessing phase, excluding them digital elevation models (DEMs) generation or change detection purposes. However, vegetation can be extracted using capturing near-infrared part spectrum, which cannot recorded by visible (RGB) cameras. In this study, after reviewing different indices in environments UAV technology, influence resolution orthomosaics generated processes extraction was examined. triangular greenness index (TGI) provided a level separability between nonvegetation all case studies any resolution. efficiency remained fundamentally linked context scenario under investigation, correlation incisiveness found more complex than might trivially assumed.