Estimating of SPAD value for jujube leaves at different growth stages using the Sentinel-2A image
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摘要: 准确估算枣树叶片叶绿素含量不仅能反映其长势及营养状况，而且还能为田间管理提供科学依据。该研究以枣树展叶期、坐果期及成熟期叶片为研究对象，旨在评估Sentinel-2A数据估算枣树叶片相对叶绿素含量(SPAD值)的潜力。基于5种典型植被指数框架，利用Sentinel-2A数据的10个波段两两组合构建光谱指数，将构建的光谱指数与实测SPAD值进行相关性分析，通过相关系数筛选最优光谱指数。基于最优光谱指数，分别采用多元线性逐步回归模型(MLSR)、支持向量机回归模型(SVR)和随机森林回归模型(RFR)建立SPAD值估算模型，以决定系数(R2)和均方根误差(RMSE)作为模型评价指标，通过模型评估筛选出估算枣树叶片SPAD值的最优模型。结果表明：(1)3个生育期优选的5种最适光谱指数主要由红波段、红边波段和近红外波段组成，且成熟期优选的5种光谱指数与SPAD值相关性最高，均通过0.01的显著性水平检验，相关系数的绝对值均大于0.37；(2)3个生育期建立的估算模型精度有所差异，其中坐果期估算精度最差，展叶期和成熟期估算精度因模型而异，基于MLSR和SVR模型，成熟期的估算精度最高，基于RFR模型，展叶期精度最高，且展叶期的RFR模型为所有估算模型中的最佳模型，R2和RMSE分别为0.90和1.04；(3)采用的MLSR、SVR和RFR三种回归模型中，MLSR和SVR估算结果较为相似，RFR为最优估算模型，且最优估算模型在不同的植被覆盖场景下具有较强的普适性。以上研究结果表明，Sentinel-2A数据适用于估算枣树叶片SAPD值，且展叶期的RFR模型可作为枣树叶片SPAD值估算的最优模型，研究结果可为基于Sentinel-2A数据估算枣树SPAD值的研究提供重要参考。
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关键词:
- Sentinel-2A /
- 枣树叶片 /
- 不同生育期 /
- SPAD值
Abstract: Objectives: The accurate estimation of leaf chlorophyll content of jujube can not only reflect its growth and nutritional status, but also provide scientific basis for field management. The aim of this study was to evaluate the potential of Sentinel-2A data for estimating soil plant analysis development (SPAD) values of jujube leaves during leaf spreading, fruit setting stage and fruit ripening stage. Methods: In this paper, five traditional vegetation indices related to chlorophyll content were selected, and based on the framework of five traditional vegetation indices, ten bands of Sentinel-2A data were used to improve the traditional vegetation indices, and five spectral indices were constructed for three growth periods respectively. The correlation between the constructed spectral index and the measured SPAD value was analyzed, and the optimal spectral index was screened by the correlation coefficient. Based on the optimal spectral index, multiple linear stepped-regression model (MLSR), support vector machine regression model (SVR) and random forest regression model (RFR) were used to establish SPAD estimation models. The coefficient of determination (R2) and Root mean square error (RMSE) were used as model evaluation indexes, and the optimal model for estimating the SPAD value of jujube leaves was screened out through model evaluation. Results: The results showed that:the five optimal spectral indices optimized at three growth stages were mainly composed of red band, red-edge band and near-infrared band, and the five optimal spectral indices at fruit ripening stage had the highest correlation with SPAD value, all of which passed the significance level test of 0.01, and the absolute values of correlation coefficients were all greater than 0.37. The accuracy of estimation models established at different growth stages was different, and the accuracy of estimation at fruit setting stage was the worst. The estimation accuracy of leaf spreading stage and fruit ripening stage varied according to the models. The accuracy of fruit ripening stage was the highest based on MLSR and SVR, while the accuracy of leaf spreading stage was the highest based on RFR. The RFR model of leaf spreading stage was the best model among all the estimation models, R2 and RMSE were 0.90 and 1.04, respectively. Among the three regression models used, MLSR, SVR and RFR, the estimation results of MLSR and SVR are similar, and RFR is the best estimation model, and the best estimation model has strong universality under different vegetation cover scenarios. Conclusions: The above results show that Sentinel-2A data is suitable for SAPD estimation of jujube leaves, and the RFR model at leaf spreading stage can be used as the optimal model for SPAD estimation of jujube leaves. The results can provide an important reference for the study of estimating SPAD value of jujube based on Sentinel-2A data.-
Keywords:
- Sentinel-2A /
- Jujube tree leaves /
- Different growth stages /
- SPAD value
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