ABSTRACT

Mineral nutrition is essential for optimal plant growth. Phosphorus (P) is a relatively small component of leaf dry weight, with a concentration in plant foliage of less than 1%. Despite its low concentration, P is an essential element in plants, mainly used for energy transfer. Mapping P concentration using traditional methods is expensive and usually limited to a small area; it is time-consuming and covers only a few plant individuals or species. In this study, we demonstrate the use of remote-sensing (RS) data acquired from the feld and airborne hyperspectral sensors to predict and map the P concentration in leaves of different woody Mediterranean plant species. Comprehensive field work included leaf sampling, laboratory analyses, and spectral measurements using a visible, near-infrared and shortwave-infrared (VIS–NIR–SWIR) field spectrometer. Using different spectral configurations, we built accurate models to predict P concentration in leaf samples. The models were built using a NIR data analysis technique with the data mining software PARACUDA II. This software allowed us to identify the correlative wavelengths for P-bearing molecules in selected woody Mediterranean plant species. The hyperspectral-based model for leaf P concentration was extracted from the reflectance data acquired using a manned aircraft carrying a hyperspectral sensor (Specim AisaFenix 1 K). The model gave a reliable correlation between points extracted from the hyperspectral image and samples measured in the field. We believe that the methodology used in this study will help forest ecologists better understand the concentration of P in the foliage of woody Mediterranean plant species.

摘要

矿物质营养对于植物的最佳生长至关重要。磷 (P) 是叶片干重中相对较小的成分，在植物叶片中的浓度低于 1%。尽管浓度低，但 P 是植物中必不可少的元素，主要用于能量传递。使用传统方法绘制 P 浓度图很昂贵，而且通常仅限于小区域；它非常耗时，并且仅涵盖少数植物个体或物种。在这项研究中，我们展示了使用从野外和机载高光谱传感器获取的遥感 (RS) 数据来预测和绘制不同地中海木本植物物种叶片中 P 浓度的地图。综合实地工作包括使用可见光、近红外和短波红外 (VIS-NIR-SWIR) 现场光谱仪进行叶片采样、实验室分析和光谱测量。使用不同的光谱配置，我们建立了准确的模型来预测叶样本中的 P 浓度。这些模型是使用 NIR 数据分析技术和数据挖掘软件 PARACUDA II 建立的。该软件使我们能够确定选定的地中海木本植物物种中含磷分子的相关波长。基于高光谱的叶磷浓度模型是从使用载有高光谱传感器（Specim AisaFenix 1 K）的有人驾驶飞机获取的反射数据中提取的。该模型给出了从高光谱图像中提取的点与现场测量的样本之间的可靠相关性。我们相信本研究中使用的方法将帮助森林生态学家更好地了解木本地中海植物物种叶子中 P 的浓度。