Success in Precision Agriculture (PA) for improving crop performance and environmental quality is related to how well and accurately vegetation, soil, and environment parameters are measured. This paper proposes a preliminary assessment of the measurement uncertainty related to Normalized Difference Vegetation Index (NDVI) by considering wavelength as uncertainty source. Furthermore, it reports an overview of the main sensors embedded in UAVs for PA applications. In particular, the physical principles of multispectral cameras and the impact of the atmospheric absorption and scattering on the spectral measurements are discussed. Also, three figures of merit widely used in PA (i.e., NDVI, Normalized Difference Moisture Index, and Crop Water Stress Index) are presented.
UAV in Precision Agriculture: a Preliminary Assessment of Uncertainty for Vegetation Health Index
Khalesi F.;Daponte P.;De Vito L.;Picariello F.;Tudosa I.
2022-01-01
Abstract
Success in Precision Agriculture (PA) for improving crop performance and environmental quality is related to how well and accurately vegetation, soil, and environment parameters are measured. This paper proposes a preliminary assessment of the measurement uncertainty related to Normalized Difference Vegetation Index (NDVI) by considering wavelength as uncertainty source. Furthermore, it reports an overview of the main sensors embedded in UAVs for PA applications. In particular, the physical principles of multispectral cameras and the impact of the atmospheric absorption and scattering on the spectral measurements are discussed. Also, three figures of merit widely used in PA (i.e., NDVI, Normalized Difference Moisture Index, and Crop Water Stress Index) are presented.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
