MAPPING CELLULOSE ABSORPTION BAND IN NPV USING PRISMA DATA

Non-photosynthetic vegetation (NPV) in croplands is receiving a growing interest for its relevance in the field of sustainable agriculture. Previous studies have demonstrated the suitability of hyperspectral remote sensing in detection and classification of NPVs. This study is an early assessment of the PRISMA mission capability to provide quantitative estimates of NPVs, through exploiting PRISMA imagery and reference field dataset collected on summer 2020. We investigate the cellulose absorption region (2.0-2.2 ?m) applying a technique of feature reduction (EGO) able to retrieve spectral parameters which can be used for qualitative and quantitative assessment of NPV in croplands. In particular, a significant non-linear relationship has been found between EGO-derived band depth and dry matter abundance (g/m2). The results are very encouraging toward a robust and quantitative estimation of NPV from space and worthy of further investigations.