基于高光谱遥感的植被冠层氮素反演方法研究进展

Research on the Method of Vegetation Canopy Nitrogen Inversion based on Hyperspectral Remote Sensing

氮素是植被生长活动中的重要元素,对植被叶绿素、蛋白质和酶等物质的合成至关重要,在植被光合作用中起关键作用。高光谱遥感反演技术凭借其快速、准确和不破坏植被的优势,已经成为植被氮素含量的定量分析的重要方法。本研究综述了近年科学文献中高光谱氮素反演的研究成果,主要介绍了植被冠层氮素高光谱研究的原理及处理方法,包括了高光谱数据处理、光谱变换、高光谱植被指数,多元逐步回归、偏最小二乘回归(PLSR)和人工神经网络(BP网络和RBF网络)回归模型等,在此基础上,对植被冠层氮素高光谱反演中存在的问题进行了探讨。

Nitrogen is an important element in vegetation growth, which is essential to the synthesis of chlorophyll, protein and enzyme, and plays a key role in the process of photosynthesis. Hyperspectral remote sensing inversion technology known with its advantages of being rapid, accurate and non de- struction of vegetation has become an important method for quantitative analysis of vegetation nitro- gen content. This paper reviewed the research results of hyperspectral inversion of nitrogen in the sci- entific literature, introduced the principles and processing methods of hyperspectral vegetation cano- py, including hyperspectrat data processing, spectral transform, hyperspectral vegetation index, step- wise regression and partial least squares regression （PLSR） and artificial neural network （BP network and RBF network） regression model. On this basis, the existing vegetation canopy hyperspectral in- version problems are discussed.