Estimation of Nitrogen Content on Apple Tree Canopy through Red-Edge Parameters from Fractional-Order Differential Opera
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RESEARCH ARTICLE
Estimation of Nitrogen Content on Apple Tree Canopy through RedEdge Parameters from Fractional-Order Differential Operators using Hyperspectral Reflectance Yufeng Peng1 • Xicun Zhu1,2 • Jingling Xiong1 • Ruiyang Yu1 • Tianlin Liu1 • Yuanmao Jiang3 Guijun Yang4
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Received: 14 July 2020 / Accepted: 2 October 2020 Ó Indian Society of Remote Sensing 2020
Abstract Timely, nondestructive and effective determination of canopy nitrogen content provides an important reference value for real-time monitoring of total nitrogen status of apple trees. Different processing methods are used to mine hyperspectral information to estimate nitrogen content. However, the overprocessing or underprocessing of hyperspectral data leads to the underutilization of spectral information. The primary objective of this study was to establish a model for estimating the nitrogen content of apple tree canopy by red-edge parameters based on fractional differential. The Grunwald–Letnikov fractional difference algorithm was used to extract the red-edge parameters from the hyperspectral canopy data, so as to develop the support vector machine (SVM) and random forest (RF) models. The results showed that the correlation with nitrogen content can be enhanced by differential spectroscopy compared with the original spectrum. The spectral parameters such as red-edge peak area (Sr(a)) obtained by fractional differential and logarithmic transformation processing and the correlation coefficient with nitrogen content can reach 0.6 or greater. The R2 of SVM and RF models constructed with red-edge parameters reached 0.56 (RMSE was 1.51 for SVM) and 0.94 (RMSE was 0.84 for RF), respectively. The RPD greater than 2 indicates that both models could be used for nitrogen estimation, and the RF model has a better predictive effect (RPD was 2.17 for SVM, RPD was 2.43 for RF). It provides an effective method for real-time monitoring of apple canopy nitrogen status and provides theoretical and technical support for hyperspectral information mining and data processing. Keywords Hyperspectral Fractional differential Red-edge parameter Canopy nitrogen
Introduction
& Xicun Zhu [email protected] 1
College of Resources and Environment, Shandong Agricultural University, Tai’an 271018, China
2
National Engineering Laboratory for Efficient Utilization of Soil and Fertilizer Resources, Shandong Agricultural University, Tai’an, Shandong, China
3
College of Horticulture Science and Engineering, Shandong Agricultural University, National Apple Engineering and Technology Research Center, Tai’an 271018, China
4
National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China
Nitrogen (N) plays an important role in the growth and development of apple trees (Wang et al. 2018; Ji et al. 2015; Yin et al. 2019) and can be used as a symbolic element in vegetation nutrition monitoring (Liu et al. 2019). The traditional nitrogen content determination method is time-consuming, laborious and destructive, which cannot realize c
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