基于地物光谱仪与成像光谱仪耦合的玉米生长信息监测研究

发布时间：2018-05-08 04:30

本文选题：玉米 + SVC光谱　；参考：《西北农林科技大学》2017年硕士论文

【摘要】：玉米是我国主要粮食作物,其产量和品质直接影响我国粮食安全和农业生产的发展。叶绿素含量、植株含水量、叶片氮素含量等生理参数对玉米长势和产量评估有重要作用,可以为农田管理、灌溉、施肥提供参考依据。以西北地区玉米为对象,应用地物光谱辐射仪和成像光谱仪观测光谱数据,测定各生育期玉米的叶绿素相对含量(Soil and plant analyzer development,SPAD)值、植株含水量以及叶片氮素含量,分析了不同生育期不同光谱仪下的光谱响应特征以及与SPAD值、植株含水量、叶片氮素含量的相关性,建立了基于特征波段、植被指数和高光谱特征参数的玉米生理参数高光谱估算模型,研究结果可以为西北地区玉米生长状况遥感监测和定量反演提供理论依据和技术支持。得到主要结论如下:(1)不同生育期玉米冠层光谱反射率响应特征有所不同。随着玉米生长发育,“绿峰”波段光谱反射率逐渐增大;在近红外波段,抽雄期和乳熟期光谱反射率较大,拔节期和完熟期光谱反射率较小。从拔节期到乳熟期,叶片SPAD值不断增加,乳熟期到完熟期,叶片SPAD值下降;在整个生育期,植株含水量呈现出逐渐减小的趋势。(2)地物光谱辐射仪测得的冠层光谱(SVC光谱Spectra Vista Corporation)与玉米SPAD值的相关性,拔节期、抽雄期、乳熟期和完熟期,光谱反射率与SPAD值的相关性分别在709nm、552nm、712nm和710nm处达到最大;光谱反射率一阶微分与SPAD值的相关性分别在752nm、756nm、760nm和749nm达到最大;玉米各生育期,植被指数GRVI、GNDVI、MCARI、TCARI与SPAD值均极显著相关;高光谱特征参数λr、Db、SDb、SDg、SDr/SDb、SDr/SDy、(SDr-SDb)/(SDr+SDb)和(SDr-SDy)/(SDr+SDy)与SPAD值达到相关系数绝对值0.7以上的极显著相关,通用性较好。抽雄期光谱一阶微分的幂函数模型,高光谱特征参数的多元线性回归模型建模为最优估算模型。(3)SVC光谱反射率与玉米植株含水量的相关性在各个生育期均较小,光谱一阶微分与植株含水量在各个生育期的最大相关波段分别为1685nm、2090nm、2455nm和433nm,最大相关系数分别为0.542、0.570、0.510和-0.685;FD2246/2084、FD2234/2028、FD2337/2249和FD(2341-433)/(2341+433)分别为各生育期的最佳光谱指数,与植株含水量的相关系数分别为0.716、0.668、0.726和-0.888。完熟期FD(2341-433)/(2341+433)的指数模型,高光谱特征参数的多元线性回归模型为最优估算模型。(4)成像光谱仪(SOC光谱Surface Optics Corporation)测得的玉米原始光谱反射率及其光谱一阶微分分别与SPAD值在717.17nm和696.12nm处达到最大相关,相关系数分别为-0.567和-0.841;植被指数MCARI与SPAD值呈最大负相关,相关系数-0.830;高光谱特征参数Dy、SDg和(SDr-SDb)/(SDr+SDb)与SPAD值相关性较好,相关系数分别为0.799、-0.795和0.862。(SDr-SDb)/(SDr+SDb)的一元线性模型、光谱一阶微分的多元线性模型为最优估算模型。(5)SOC测得的原始反射率光谱和一阶微分光谱分别与叶片氮素在711.90nm和545.84nm处达最大相关,相关系数分别为-0.530和-0.667;植被指数GNDVI与叶片氮素呈最大正相关,相关系数0.608;高光谱特征参数Ro、SDg和SDr/SDb与叶片氮素相关性较好,相关系数分别为-0.578、-0.635和0.717。SDr/SDb的一元线性模型、高光谱特征参数的多元线性模型为最优估算模型。
[Abstract]:Corn is the main grain crop in China, its yield and quality directly affect the development of grain safety and agricultural production in China. Chlorophyll content, plant water content, leaf nitrogen content and other physiological parameters play an important role in the evaluation of maize growth and yield, which can provide reference for farmland management, irrigation and fertilization. Using spectral radiometer and imaging spectrometer, the relative content of chlorophyll (Soil and plant analyzer development, SPAD), plant water content and leaf nitrogen content were measured by using the spectral radiometer and imaging spectrometer. The spectral response characteristics of different growth periods and the value of SPAD and plant water content were analyzed. The correlation of nitrogen content in leaves was related to the establishment of a Hyperspectral Estimation Model of maize physiological parameters based on characteristic band, vegetation index and hyperspectral characteristic parameters. The results could provide theoretical basis and technical support for remote sensing monitoring and quantitative inversion of maize growth in Northwest China. The main conclusions are as follows: (1) different growth period corn. The spectral reflectance characteristics of canopy spectral reflectance are different. With the growth and development of maize, the spectral reflectance of the "green peak" band increases gradually. In the near infrared band, the spectral reflectance of the male and the milk ripening periods is larger, and the spectral reflectance of the jointing and finishing stages is small. From the jointing stage to the milk ripening stage, the SPAD value of the leaves is increasing, the milk ripening period and the mature period, leaves are the leaves. The SPAD value decreased; in the whole growth period, the water content of the plant decreased gradually. (2) the correlation between the canopy spectrum (SVC spectrum Spectra Vista Corporation) and the value of maize SPAD measured by the ground spectral radiometer, the jointing stage, the male stage, the milk ripening period and the completion period, the correlation of spectral reflectance with the SPAD value was 709nm, 552nm, 712nm respectively. The correlation between the first order differential of spectral reflectance and the value of SPAD reached the maximum in 752nm, 756nm, 760nm and 749nm, respectively, and the vegetation index GRVI, GNDVI, MCARI, TCARI and SPAD were significantly correlated with each growth period of maize; The PAD value reached the extremely significant correlation of the absolute value above 0.7 of the correlation coefficient, and the generality was better. The optimal estimation model was modeled by the power function model of the first order differential of the spectrum and the multivariate linear regression model of hyperspectral characteristic parameters. (3) the correlation between the reflectance of SVC and the water content of maize plants was smaller in each growth period, and the first order of the spectrum The maximum correlation bands of the water content in each growth period were 1685nm, 2090nm, 2455nm and 433nm respectively. The maximum correlation coefficients were 0.542,0.570,0.510 and -0.685, respectively, FD2246/2084, FD2234/2028, FD2337/2249 and FD (2341-433) / (2341+433) were the best spectral indices of each growth period, and the correlation coefficient with the plant water content was 0, respectively. The exponential model of FD (2341-433) / (2341+433) of.716,0.668,0.726 and -0.888., the optimal estimation model of the multivariate linear regression model of hyperspectral characteristic parameters. (4) the original spectral reflectance and the first order differential of the spectral reflectance of the imaging spectrometer (SOC spectrum Surface Optics Corporation) and the SPAD values are in 717.17nm and 696.12nm, respectively. The maximum correlation coefficient is -0.567 and -0.841, the vegetation index MCARI and SPAD have the maximum negative correlation, the correlation coefficient is -0.830, the hyperspectral characteristic parameter Dy, SDg and (SDr-SDb) / (SDr+SDb) and SPAD values are better, the correlation coefficients are 0.799, -0.795 and 0.862.. The multivariate linear model is the optimal estimation model. (5) the maximum correlation between the original reflectance spectra and the first order differential spectra measured by SOC and the leaf nitrogen at 711.90nm and 545.84nm respectively, the correlation coefficients are -0.530 and -0.667, respectively, the vegetation index GNDVI has the maximum positive correlation with the leaf nitrogen, the correlation coefficient is 0.608, the hyperspectral characteristic parameter Ro, SDg The correlation coefficient of SDr/SDb and leaf nitrogen is better. The correlation coefficient is -0.578, -0.635 and 0.717.SDr/SDb linear model, and the multivariate linear model of hyperspectral characteristic parameters is the optimal estimation model.

【学位授予单位】：西北农林科技大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：S513;S126

【参考文献】