📅 October 2023
🧑 S. Oprisescu, R. M. Coliban, M. Ivanovici
#Visualization #Image color analysis #Vegetation mapping #Crops Sensors #Task analysis #Hyperspectral imaging
Agriculture has witnessed a series technological transformations over time. In recent years, multispectral and hyperspectral satellites have become powerful tools in precision and efficient agricultural practices. Given the richness of information they provide and the fact that multi- and hyperspectral data are not easy to interpret, a consistent visual mapping of these images can be provided for agricultural purposes through vegetation maps. In this paper, we propose and compare alternatives for computing vegetation indices when the data come from hyperspectral images. We provide a comparative analysis, evaluating the distinctions between NDVI maps derived from Sentinel-2 and PRISMA data. The study offers an interpretation of the results and conclusions.
http://ai4agri.unitbv.ro/wp-content/uploads/2024/04/I_C_Plajer_WHISPERS_2023.pdf