Use of Hyperspectral Prisma Level-1 Data and ISDA Soil Fertility Map for Soil Macronutrient Availability Quantification in a Moroccan Agricultural Land

This study aims to establish a quantitative framework for soil nitrogen (N), phosphorus (P), and potassium (K) availability in crop fields, using hyperspectral remote sensing imagery and 30m resolution landmark map charting soil fertility across the whole of Africa that has been recently developed by a group of international scientists (iSDA soil). The iSDA map data will be analysed against PRISMA derived Level-2 surface reflectance imagery. We expect to highlight spectral absorption features of N, P and K that relate with their variability in soil. We will investigate the performance of random forest, principal component analysis, support vector regression, partial least squares regression and artificial neural networks in estimating soil total N and extractable P and K quantities from hyperspectral imagery. These models will be assessed using descriptive statistical indices and analysis of variance. We expect to demonstrate the suitability of remote sensing in precision for African agriculture.