冬小麦叶片SPAD遥感探测的光谱尺度效应  

Spectral scale effects on the optical estimation of winter wheat leaf SPAD value

作　　者：池浩然 李映雪[4] 吴芳 邹晓晨 CHI Haoran;LI Yingxue;WU Fang;ZOU Xiaochen(School of Remote Sensing and Geomatics Engineering,Nanjing University of Information Science and Technology,Nanjing 210044,China;Technology Innovation Center of Integration Applications in Remote Sensing and Navigation,Ministry of Natural Resources,China,Nanjing 210044,China;Jiangsu Engineering Center for Collaborative Navigation/Positioning and Smart Applications,Nanjing 210044,China;School of Ecology and Applied Meteorology,Nanjing University of Information Science and Technology,Nanjing 210044,China;Xinghua Meteorological Bureau,Xinghua 225700,China)

机构地区：[1]南京信息工程大学遥感与测绘工程学院,南京210044 [2]自然资源部遥感导航一体化应用工程技术创新中心,南京210044 [3]江苏省协同精密导航定位与智能应用工程研究中心,南京210044 [4]南京信息工程大学生态与应用气象学院,南京210044 [5]兴化市气象局,兴化225700

出　　处：《农业工程学报》2025年第2期196-205,共10页Transactions of the Chinese Society of Agricultural Engineering

基　　金：国家自然科学基金项目(41801243)。

摘　　要：叶片SPAD(soil and plant analyzer development)值表征了叶片叶绿素相对含量,是监测农作物长势和营养状况的重要参数。光学遥感是大面积无损探测叶片SPAD值的重要手段。然而,由于不同光谱尺度数据探测光谱变化存在差异,影响了光学探测作物生化参数的精度,但目前很少有研究系统评估不同光谱尺度对探测冬小麦叶片SPAD值的影响。为优化光谱尺度提升叶片SPAD探测精度,该研究通过连续4年田间试验,获取冬小麦4个关键生育期(拔节期、抽穗期、开花期和灌浆期)和3种施氮水平(N1、N2和N3)条件下的冠层光谱反射率和叶片SPAD值,评估了5种光谱尺度(1、5、10、25和50 nm)下单一波段反射率和植被指数对叶片SPAD值敏感性差异及对机器学习模型估算SPAD值的影响。结果表明,红光波段反射率对SPAD值敏感性最大,光谱尺度敏感性变异系数Var为0.497。红边波段波长710 nm反射率受到光谱尺度影响最大,在全生育期敏感性变异系数Var为1.000。全生育期敏感性最佳植被指数为m ND705,在50 nm光谱尺度对SPAD的敏感性最高(R^(2)=0.685)且光谱尺度敏感性变异系数低(Var=0.014)。在4个单一生育期中,mND705在灌浆期对SPAD的敏感性最佳(R^(2)=0.895)且受到光谱尺度的影响小(Var=0.014)。施氮水平的增加提升了植被指数对SPAD的敏感性。优化光谱尺度提升了机器学习模型估算SPAD的能力,全生育期中以25 nm光谱尺度构建的偏最小二乘回归模型对SPAD的估算精度最佳(R^(2)=0.816和均方根误差RMSE=4.04)。该研究为从优化光谱尺度角度优化光学传感器选择和设计、光谱植被指数波段选择和机器学习模型光谱特征构建提供了理论基础。Chlorophyll is one of the most important photosynthesis pigments in crops. The photosynthetic capacity of the plant can also indicate the plant's growth and nutritional status. Leaf chlorophyll content can be accurately acquired to monitor crop growth and yield. The portable optical instrument SPAD-502 can be used to rapidly acquire the SPAD value in a non-destructive way, indicating the leaf's relative chlorophyll content. However, the tremendous amount of hand labor cannot fully meet the needs to estimate the leaf SPAD value in a large area and then monitor the dynamic of crop growth and agricultural management. Alternatively, optical remote sensing can be expected to non-destructively measure the leaf SPAD value at a large scale. This study aims to evaluate the effects of spectral resolution on the optical SPAD estimation of winter wheat leaf using remote sensing. A four-year field experiment was carried out under four growth stages (jointing, heading, anthesis, and filling) and three levels of nitrogen application. A systematic investigation was implemented to determine the canopy spectral reflectance and leaf SPAD values of winter wheat. The leaf SPAD estimation model was constructed using 25 commonly used chlorophyll content-sensitive spectral indices combined with machine learning. An evaluation was also made on the effects of five spectral resolutions on the reflectance of a single band, spectral indices, and the estimation of SPAD value using machine learning. The results show that the sensitivity of single-band reflectance to SPAD was dominated by the spectral resolution, growth stages, and nitrogen application levels. In the whole growth period, the reflectance of the red band was more sensitive to the SPAD than the rest bands, where the determination coefficient R^(2) was between 0.411 and 0.579 at the five spectral resolutions. The reason was that there was a strong absorption of chlorophyll in the red band. Specifically, the R^(2) was between 0.242 and 0.700, and the Var was between 0.313 and 0.952

关 键 词：光谱尺度 植被指数 叶绿素含量 冬小麦 机器学习 

分 类 号：S126[农业科学—农业基础科学]