This study introduces a first assessment of the capabilities of PRISMA (PRecursore IperSpettrale della Missione Applicativa)—the new hyperspectral satellite sensor of the Italian Space Agency (ASI)—for Non-Photosynthetic Vegetation (NPV) monitoring, a topic which is becoming very relevant in the field of sustainable agriculture, being an indicator of crop residue (CR) presence in the field. Data-sets collected during the mission validation phase in croplands are used for mapping the NPV presence and for modelling the diagnostic absorption band of cellulose around 2.1 $\mathsf{\mu }$m with an Exponential Gaussian Optimization approach, in the perspective of the prediction of the abundance of crop residues. Results proved that PRISMA data are suitable for these tasks, and call for further investigation to achieve quantitative estimates of specific biophysical variables, also in the framework of other hyperspectral missions.

中文翻译：

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农田中PRISMA高光谱数据对非光合植被的检测和分类

本研究介绍了意大利航天局（ASI）的新型高光谱卫星传感器PRISMA（PRecursore IperSpettrale della Missione Applicativa）的功能的首次评估，该功能用于非光合植被（NPV）监测，这一话题已变得非常相关在可持续农业领域中，它是该领域中作物残渣（CR）含量的指标。在农田的任务验证阶段收集的数据集用于绘制NPV的分布图并为2.1左右的纤维素诊断吸收带建模$\mathsf{\mu }$从预测作物残渣的丰度角度来看，采用指数高斯优化方法优化m。结果证明PRISMA数据适合于这些任务，并要求进一步研究以实现对特定生物物理变量的定量估计，以及其他高光谱任务的框架。