Examination of vegetation indices based on multitemporal drone images

Abstract

In Hungary, the use of drones (UAV) has been showing an increasing trend over the past few years. The available UAV’s and the camera systems placed a significant influence and, in some cases, can even limit, their effective and reliable - also appropriate from the data security point of view - application in the assessment of plant growing areas. In addition to the generation of the data, the extractable information content of the produced visual and non-visual data can also be greatly influenced by the processing and analysis methods. During our research, we took multitemporal aerial photographs of winter wheat at different times of the vegetation period. In our article, we will present our results for the NDVI, GNDVI, and VDVI vegetation indices, which include the processing of aerial photographs taken with two different UAVs, highlighting our analyses of the correlations between the discrete and nondiscrete bands of the aerial photographs.