Top soil parameters retrieval by using PRISMA and HYTES 2023 campaign: preliminary result on the Jolanda di Savoia test site (Italy)

Understanding the properties of agricultural soils is essential for optimizing the food production and the overall efficiency of agricultural systems. Thermal infrared (TIR) and visible-near-infrared (VNIR) data are the main spectral ranges used for soil parameters retrieval. Both spectral ranges show advantages and limitations. The combination of the new generation of satellite hyperspectral VNIR and TIR data can enhance food security products by optimizing also agricultural management practices. In this study, multiple bare soil PRISMA satellite and HyTES airborne hyperspectral images, in the VNIR and TIR, acquired over the Jolanda di Savoia farm in Northern Italy, were used to retrieve Soil Organic Matter (SOM), Calcium Carbonate (CaCO3), and texture elements (Silt, Clay, Sand) topsoil properties by applying Machine Learning Regression Algorithms (MLRA). Products were validated using an adapted field measurement scheme for soil sampling and analysis. These preliminary tests combining VNIR ad LWIR ranges have yielded satisfactory results that need a further investigation especially for the silt and the sand retrieval.