夏玉米不同生育时期生理生态参数的高光谱遥感监测模型
发布时间：2018-09-05 11:28
【摘要】：高光谱遥感技术是现代农业信息技术研究的重要方向,高效低耗的作物营养诊断及长势监测技术对精准作物管理及合理施肥具有重要意义。高光谱遥感技术具有分辨率高、连续性强、信息量大等特点,可对作物进行实时、快速、无损的营养诊断、长势监测、产量和品质预测。本试验在不同夏玉米品种、不同氮磷营养水平及不同生育时期的大田试验条件下,测定了冠层光谱反射率、叶片氮磷含量、叶面积指数、地上干物质量、叶片水分含量、籽粒品质及产量等生理生态参数,分析不同生育时期及不同氮磷水平对夏玉米冠层光谱反射率的影响、光谱反射率与生理生态参数的相关性,综合前人已有的研究成果,建立生理生态参数与光谱敏感波段、光谱特征参量、植被指数的相关模型并进行模型精度的检验。最终筛选出适用于不同夏玉米品种及不同生育时期的高光谱诊断与监测生理生态参数模型,为夏玉米营养诊断及长势监测提供理论基础及现实依据。1.在夏玉米拔节期、大喇叭口期、吐丝期和灌浆期,叶片氮素含量随施氮量的增加而增加。可见光波段夏玉米冠层光谱反射率随施氮量的增加而降低,在近红外波段,光谱反射率随施氮量的增加而增加。在可见光波段,从拔节期到吐丝期,光谱反射率逐渐降低,进入灌浆期后,光谱反射率增强;在近红外区域,从拔节期到吐丝期,冠层光谱反射率逐渐增加,进入灌浆期后,光谱反射率降低。夏玉米叶片全氮含量与原始光谱在350~725nm为负相关,在740~1400nm的近红外波段为显著正相关,725~735nm为相关系数转变的位置。拔节期(Dy、Ro、SDr)、大喇叭口期(Rg、SDr/SDb、GNDVI)、吐丝期(DI、DVI、NDVI1)和灌浆期(SDr/SDb、GNDVI、NDVI1)的参量与叶片全氮含量具有较高的相关系数。拔节期、大喇叭口期、吐丝期和灌浆期玉米叶片氮素含量的最适反演模型参量分别为SDr、GNDVI、NDVI1和NDVI1。2.夏玉米叶片全磷含量随着施磷量增加而升高,在不同生育时期均有相似规律。在可见光波段,夏玉米冠层光谱反射率与不同磷肥水平响应不一致。在近红外波段(740~1380nm),光谱反射率随施磷量的增加而增加,但光谱响应曲线差异不明显;在此区域,相关系数较为稳定,9个归一化光谱波段(830nm、880 nm、940 nm、1100 nm、1430 nm、1580 nm、1650 nm、1740 nm、2200 nm)为敏感波段,双波段组合参量具有更高的相关系数。拔节期(R830、R880、R830+880、R830+940)、大喇叭口期(R830、R880、R830+880、R830+940)、灌浆期(R940、R1100、R880+1100、R940+1100)归一化参量具有较高的相关系数,灌浆期的参量均未达到显著相关。拔节期、大喇叭口期和灌浆期的R830+880、R830+940和R880+1100归一化参量的模型为玉米叶片磷素含量反演最适模型。3.在夏玉米大喇叭口期、吐丝期、灌浆期和成熟期,在同一施磷水平下,冠层叶面积指数随施氮量的增加而增加;在同一施氮水平下,随施磷量的增加,叶面积指数也明显的增加。冠层叶面积指数和光谱反射率的相关性在可见光波段(420~680nm)为负相关,在近红外波段(740~1120nm)为正相关,各生育时期相关系数曲线走势基本一致,但相关系数普遍不高。利用原始冠层反射光谱构建21个植被指数,大喇叭口期(PSSRb、NDVI1、N DVI2)、吐丝期(PSSRc、MTCI、MSR705)、灌浆期(MSR705)和成熟期(DI)构建的拟合方程具有较高的决定系数和F值。大喇叭口期、吐丝期、灌浆期和成熟期的植被指数NDVI2、MSR705、MSR705、DI可较好的应用于夏玉米冠层叶面积指数监测。4.从大喇叭口期到成熟期,不同氮磷水平下夏玉米地上干物质量均表现为逐渐增加的趋势,且都符合典型的“S”型生长曲线,生长速率为“慢-快-慢”。在夏玉米的各生育时期,在同一施磷水平下,地上干物质量随施氮量的增加而增加;在同一施氮水平下,随施磷量的增加,干物质积累量也有明显的升高。在可见光波段,夏玉米冠层原始光谱反射率与地上干物质量为较高且稳定的负相关;在近红外波段,夏玉米冠层原始光谱反射率与地上干物质量具有较高的正相关性。大喇叭口期、吐丝期、灌浆期和成熟期的植被指数GNDVI、PSSRc、NDVI4和DI可较好的用于估算夏玉米地上干物质量。5.从拔节期到灌浆期,叶片水分含量呈逐渐下降趋势,在吐丝期水分含量差异最大,拔节期水分含量差异最小。夏玉米的拔节期、大喇叭口期、吐丝期和灌浆期的叶片光谱反射率与叶片水分含量为负相关,不同生育时期具有较大差异。拔节期和大喇叭口期,叶片光谱反射率与水分含量在740~1340nm为稳定负相关,但相关系数不高;大喇叭口期、吐丝期和灌浆期的1370~2500nm波段,除1900nm波段附近,其他波段为稳定负相关,且相关系数较高。选择9个敏感波段和18个水分植被指数与叶片水分含量进行相关性分析。在大喇叭口期、吐丝期和灌浆期,敏感波段1450nm和1650nm、植被指数NDWI2和SIWSI的相关系数较高。大喇叭口期、吐丝期和灌浆期的R1450、NDWI2和NDWI2建立的回归拟合模型可用于夏玉米叶片水分含量的监测。6.夏玉米籽粒蛋白含量及产量均随施肥量的增加而升高,且不同氮磷肥力处理间差异多为显著。选择灌浆期的14个植被指数与籽粒蛋白含量和产量进行回归分析。在籽粒蛋白含量拟合方程中,植被指数RVI和OSAVI拟合方程具有较高的决定系数;在籽粒产量拟合方程中,植被指数RVI、GRVI和NDVI具有较高的决定系数及F值。模型精度精度检验结果表明,植被指数RVI可较好的预测夏玉米籽粒蛋白含量和产量,具有较好的稳定性和抗背景干扰性。
[Abstract]:Hyperspectral remote sensing technology is an important research direction of modern agricultural information technology. High-efficiency and low-consumption crop nutrition diagnosis and growth monitoring technology is of great significance to accurate crop management and rational fertilization. Nutrition diagnosis, growth monitoring, yield and quality prediction. The physiological and ecological parameters, such as canopy spectral reflectance, leaf nitrogen and phosphorus content, leaf area index, aboveground dry matter, leaf water content, grain quality and yield, were measured under different summer maize varieties, different nitrogen and phosphorus nutrition levels and different growth stages. The effects of different growth stages and nitrogen and phosphorus levels on the spectral reflectance of summer maize canopy and the correlation between spectral reflectance and physiological and ecological parameters were analyzed. Hyperspectral diagnostic and monitoring physiological and ecological parameters models suitable for different summer maize varieties and different growth stages were screened to provide theoretical and practical basis for nutritional diagnosis and growth monitoring of summer maize. The spectral reflectance of summer maize canopy decreased with the increase of nitrogen application in the light band, and increased with the increase of nitrogen application in the near infrared band. The total nitrogen content in summer maize leaves was negatively correlated with the original spectrum from 350 nm to 725 nm, positively correlated with the near infrared spectrum from 740 nm to 1400 nm, and positively correlated with the position of correlation coefficient change from 725 nm to 735 nm. The parameters of I, NDVI1 and grain filling (SDr/SDb, GNDVI, NDVI1) had higher correlation coefficients with leaf total nitrogen content. The optimum parameters of the model were SDr, GNDVI, NDVI1 and NDVI1.2 at jointing stage, big trumpet stage, silking stage and grain filling stage, respectively. In the near infrared band (740 ~ 1380 nm), the spectral reflectance increased with the increase of phosphorus application, but the spectral response curves were not significantly different; in this region, the correlation coefficient was relatively stable, and nine normalized spectral bands (830 n) M, 880 nm, 940 nm, 1100 nm, 1430 nm, 1580 nm, 1650 nm, 1740 nm, 2200 nm are sensitive bands, and the combined parameters of the two bands have higher correlation coefficients. The normalized parameters of jointing stage (R830, R880, R830 + 880, R830 + 940), large trumpet stage (R830, R880, R830 + 880, R830 + 940, R830 + 940), grouting stage (R940, R1100, R880 + 1100, R940) have higher correlation coefficients. The models of R830+880, R830+940 and R880+1100 normalized parameters at jointing stage, big trumpet stage and filling stage were the most suitable models for inversion of phosphorus content in Maize leaves. The correlation between canopy leaf area index and spectral reflectance was negative in the visible band (420 ~ 680 nm), positive in the near infrared band (740 ~ 1120 nm), and the trend of correlation coefficient curve was basically the same in all growth stages, but the correlation coefficient of canopy leaf area index and spectral reflectance was negative in the visible band (420 ~ 680 nm) and positive in the near infrared band (740 ~ 1120 nm). The fitting equations of 21 vegetation indices, PSSRb, NDVI1, NDVI2, PSSRc, MTCI, MSR705, MSR705, MSR705 and DI constructed by the original canopy reflectance spectra have higher determinant coefficients and F values. SR705, MSR705, DI can be better used to monitor the canopy leaf area index of summer maize. 4. From the big trumpet stage to the mature stage, the above-ground dry matter of summer maize showed a gradual increase trend under different nitrogen and phosphorus levels, and all accorded with the typical "S" growth curve, the growth rate was "slow-fast-slow". Under the same phosphorus application level, the above-ground dry matter increased with the increase of nitrogen application rate, and the dry matter accumulation also increased with the increase of phosphorus application rate. The vegetation indices GNDVI, PSSRc, NDVI4 and DI of big trumpet stage, silking stage, filling stage and mature stage could be used to estimate the above-ground dry matter of summer maize. 5. From jointing stage to filling stage, the leaf water content decreased gradually, and the water content of summer maize during silking stage was decreased. The spectral reflectance of summer maize leaves at jointing stage, big trumpet stage, silking stage and grain filling stage was negatively correlated with leaf moisture content, and there were significant differences at different growth stages. But the correlation coefficient is not high; the 1370-2500 nm band of big trumpet stage, silking stage and filling stage, except near 1900 nm band, the other bands are stable negative correlation, and the correlation coefficient is high. The correlation coefficients of NDWI2 and SIWSI were higher at 1450nm and 1650nm. The regression models of R1450, NDWI2 and NDWI2 at Bell stage, silking stage and grain filling stage could be used to monitor the water content of summer maize leaves. 6. The protein content and yield of summer maize grain increased with the increase of fertilizer application, and the nitrogen and phosphorus fertility treatments were different. In the grain protein content fitting equation, the vegetation index RVI and OSAVI fitting equation have higher determinant coefficient; in the grain yield fitting equation, the vegetation index RVI, GRVI and NDVI have higher determinant coefficient and F value. The precision test results showed that the vegetation index RVI could better predict the protein content and yield of summer maize grain, and had better stability and anti-background interference.
【学位授予单位】：西北农林科技大学
【学位级别】：博士
【学位授予年份】：2016
【分类号】：S513
，
本文编号：2224135
[Abstract]:Hyperspectral remote sensing technology is an important research direction of modern agricultural information technology. High-efficiency and low-consumption crop nutrition diagnosis and growth monitoring technology is of great significance to accurate crop management and rational fertilization. Nutrition diagnosis, growth monitoring, yield and quality prediction. The physiological and ecological parameters, such as canopy spectral reflectance, leaf nitrogen and phosphorus content, leaf area index, aboveground dry matter, leaf water content, grain quality and yield, were measured under different summer maize varieties, different nitrogen and phosphorus nutrition levels and different growth stages. The effects of different growth stages and nitrogen and phosphorus levels on the spectral reflectance of summer maize canopy and the correlation between spectral reflectance and physiological and ecological parameters were analyzed. Hyperspectral diagnostic and monitoring physiological and ecological parameters models suitable for different summer maize varieties and different growth stages were screened to provide theoretical and practical basis for nutritional diagnosis and growth monitoring of summer maize. The spectral reflectance of summer maize canopy decreased with the increase of nitrogen application in the light band, and increased with the increase of nitrogen application in the near infrared band. The total nitrogen content in summer maize leaves was negatively correlated with the original spectrum from 350 nm to 725 nm, positively correlated with the near infrared spectrum from 740 nm to 1400 nm, and positively correlated with the position of correlation coefficient change from 725 nm to 735 nm. The parameters of I, NDVI1 and grain filling (SDr/SDb, GNDVI, NDVI1) had higher correlation coefficients with leaf total nitrogen content. The optimum parameters of the model were SDr, GNDVI, NDVI1 and NDVI1.2 at jointing stage, big trumpet stage, silking stage and grain filling stage, respectively. In the near infrared band (740 ~ 1380 nm), the spectral reflectance increased with the increase of phosphorus application, but the spectral response curves were not significantly different; in this region, the correlation coefficient was relatively stable, and nine normalized spectral bands (830 n) M, 880 nm, 940 nm, 1100 nm, 1430 nm, 1580 nm, 1650 nm, 1740 nm, 2200 nm are sensitive bands, and the combined parameters of the two bands have higher correlation coefficients. The normalized parameters of jointing stage (R830, R880, R830 + 880, R830 + 940), large trumpet stage (R830, R880, R830 + 880, R830 + 940, R830 + 940), grouting stage (R940, R1100, R880 + 1100, R940) have higher correlation coefficients. The models of R830+880, R830+940 and R880+1100 normalized parameters at jointing stage, big trumpet stage and filling stage were the most suitable models for inversion of phosphorus content in Maize leaves. The correlation between canopy leaf area index and spectral reflectance was negative in the visible band (420 ~ 680 nm), positive in the near infrared band (740 ~ 1120 nm), and the trend of correlation coefficient curve was basically the same in all growth stages, but the correlation coefficient of canopy leaf area index and spectral reflectance was negative in the visible band (420 ~ 680 nm) and positive in the near infrared band (740 ~ 1120 nm). The fitting equations of 21 vegetation indices, PSSRb, NDVI1, NDVI2, PSSRc, MTCI, MSR705, MSR705, MSR705 and DI constructed by the original canopy reflectance spectra have higher determinant coefficients and F values. SR705, MSR705, DI can be better used to monitor the canopy leaf area index of summer maize. 4. From the big trumpet stage to the mature stage, the above-ground dry matter of summer maize showed a gradual increase trend under different nitrogen and phosphorus levels, and all accorded with the typical "S" growth curve, the growth rate was "slow-fast-slow". Under the same phosphorus application level, the above-ground dry matter increased with the increase of nitrogen application rate, and the dry matter accumulation also increased with the increase of phosphorus application rate. The vegetation indices GNDVI, PSSRc, NDVI4 and DI of big trumpet stage, silking stage, filling stage and mature stage could be used to estimate the above-ground dry matter of summer maize. 5. From jointing stage to filling stage, the leaf water content decreased gradually, and the water content of summer maize during silking stage was decreased. The spectral reflectance of summer maize leaves at jointing stage, big trumpet stage, silking stage and grain filling stage was negatively correlated with leaf moisture content, and there were significant differences at different growth stages. But the correlation coefficient is not high; the 1370-2500 nm band of big trumpet stage, silking stage and filling stage, except near 1900 nm band, the other bands are stable negative correlation, and the correlation coefficient is high. The correlation coefficients of NDWI2 and SIWSI were higher at 1450nm and 1650nm. The regression models of R1450, NDWI2 and NDWI2 at Bell stage, silking stage and grain filling stage could be used to monitor the water content of summer maize leaves. 6. The protein content and yield of summer maize grain increased with the increase of fertilizer application, and the nitrogen and phosphorus fertility treatments were different. In the grain protein content fitting equation, the vegetation index RVI and OSAVI fitting equation have higher determinant coefficient; in the grain yield fitting equation, the vegetation index RVI, GRVI and NDVI have higher determinant coefficient and F value. The precision test results showed that the vegetation index RVI could better predict the protein content and yield of summer maize grain, and had better stability and anti-background interference.
【学位授予单位】：西北农林科技大学
【学位级别】：博士
【学位授予年份】：2016
【分类号】：S513
，
本文编号：2224135
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