USING HYPERSPECTRAL DATA FORMONITORING AND OBSERVATION OF FABA BEAN CROP GROWTH - Tarek FOUDA; Abeer ABDELSALAM (Scientific Papers Series : Management, Economic Engineering in Agriculture and Rural Development)
The optical imagery at high spatial resolution to monitoring and observation of faba bean crop growth obtained from The Sentinel-2 sensor during November 2021 to February 2022 (daytime) were used. Thirteen bands of multispectral data covering the visible, near-infrared, and short wave infrared portions of the spectrum using to monitor land cover change for environmental monitoring. A surface emissivity calculation is the first step of land surface temperature observation and finding the agricultural indices of faba bean crop.The emissivity per pixel was obtained directly from Sentinel-2 sensor data. Natural surfaces at the resolution of 30 m are heterogeneous and they differ from each other in their emissivity. In the present study, surface emissivity was evaluated by analysis of NDVI, NDMI, SWIR, NDWI, Agriculture Composite, and SAVI of vegetation cover per pixel, and the maximum values of climatic indices such as sunshine duration, relative humidity, long, short wave radiation, ultraviolet radiation direct, diffuse radiation, soil temperature, FAO reference evapotranspiration (Eto.The results showed the monthly composite pictures which produced using to generate correct crop growth findings by comparing band reflectance values, vegetation indices, and environmental indicators.