Compararea senzorilor multispectrali (Micasense, Parrot Sequoia, Sentera) și elaborarea unei baze calibrate de imagini [Articol]

Abstract

In precision agriculture, multispectral images collected by drones represent an essential source of information for assessing plant health, chlorophyll content, water stress, and crop productivity. However, the quality and comparability of these data largely depend on the characteristics of the sensors used, such as spectral sensitivity, radiometric calibration, spatial resolution, and stability under variable lighting conditions. The aim of the project is the comparative evaluation of the performance of multispectral sensors (MicaSense, Parrot Sequoia, Sentera) in collecting data over the same agricultural areas and the development of a calibrated database containing radiometrically and spectrally standardized images.