Remote Sensing Inversion of Leaf and Canopy Water Content in Different Growth Stages of Summer Maize
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摘要: 高光谱遥感技术监测作物含水量是了解作物生长状况的重要技术。为实现夏玉米不同生育期叶片和冠层含水量的快速、精细化、无损监测,本文基于2014年和2015年的6—10月华北夏玉米不同生育期不同灌水量干旱模拟试验数据构建了植被水分指数(WI,MSI,GVMI)、复比指数(WNV和WCG)和红边反射率曲线面积(Darea)的夏玉米冠层等效水厚度(EWTC)和叶片可燃物含水量(FMC)的反演模型。结果表明:6个指标反演夏玉米三叶期的EWTC模型均未达到0.05显著性水平,三叶期后各指标反演EWTC模型均达到0.01的显著性水平,且总体而言模型精度从高到低为抽雄期、拔节期、灌浆期、成熟期和七叶期。6个指标反演七叶期和拔节期的FMC均达到0.01显著性水平。因此,同一光谱指标反演夏玉米不同生育期叶片和冠层含水量的精度差异较大。光谱指标反演夏玉米叶片和冠层含水量指标的精度与夏玉米生育期有很大关系,进而提出了夏玉米不同生育期含水量反演模型。研究结果可为准确模拟夏玉米不同生育期含水量提供技术支撑。Abstract: Hyperspectral remote sensing technology is an important method for crop water monitoring, aiming to understand crop growth status. In order to achieve rapid, refined and comprehensive monitoring for the leaf and canopy water content of summer maize in different growth stages, controlled experiments are implemented during different growth stages of the summer maize with different irrigation water drought simulation test in North China. The water content of vegetation index (WI), water stress index (MSI), global vegetation moisture index (GVMI), compound ratio index (WNV and WCG) and reflectance curve area (Darea) of summer maize are defined for inversion models of equivalent water thickness for canopy (EWTC) and fuel moisture content for leaf (FMC). The hyperspectral remote sensing inversion models of moisture content of summer maize in 2014 are verified by using drought simulation data of different irrigation water amount during different growth periods in 2015. Results show that WI, MSI, GVMI, WNV, WCG and Darea for inversion EWTC of summer maize at the three-leaf stage doesn't pass the significance test of 0.05 level, but all the indices estimation EWTC models after the three-leaf stage pass the significance test of 0.01 level. The model accuracy for different stages from high to low are as follows: Tasseling stage, knotting stage, filling stage, mature stage, and seven-leaf stage. FMC at the seven-leaf stage and jointing stage is retrieved by 6 special indicators and all of them pass the significance test of 0.01 level. FMC at the three-leaf stage is retrieved by WNV index, but 6 spectral indicators after jointing stage cannot retrieve FMC of summer maize. In summary, the difference of precision of the same spectral indicator to retrieve the water content of summer maize is obvious in different growth stages. The retrieved water content precision is higher for middle summer maize growth period, but relatively lower for early and late remote sensing. Although canopy and leaf scale water content indices can reflect the drought situation of summer maize, considering the precision of spectral indicator retrieval of two scale water content indices of summer maize is closely related to the growth period of summer maize, a retrieval model of water content is proposed for different growth stages of summer maize to provide accurate simulation of water content in summer maiz growth.
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表 1 2014年夏玉米生长季灌水设置
Table 1 Irrigation treatments of summer maize growth in 2014
处理 占7月降水量的百分比/% 灌水量/mm A 20 30 B 40 60 C 60 90 D 80 120 E 100 150 表 2 2015年夏玉米生长季灌水设置
Table 2 Irrigation treatments of summer maize growth in 2015
处理 土壤相对湿度 A1 全生育期55%±5% B1 全生育期35%±5% C1 拔节前保持75%±5%, 拔节后加灌16 mm D1 拔节前保持75%±5%, 拔节后不再灌水 E1 全生育期75%±5% 表 3 不同光谱指数反演夏玉米冠层和叶片尺度含水量模型精度(R2)
Table 3 The model precision of canopy and leaf level water content of summer maize using different spectral indices (R2)
光谱指数 尺度 三叶期 七叶期 拔节期 抽雄期 灌浆期 成熟期 WI 冠层 0.02 0.50* 0.80* 0.95* 0.71* 0.72* 叶片 0.67* 0.59* 0.02 0.06 0.06 MSI 冠层 0.10 0.56* 0.82* 0.91* 0.80* 0.64* 叶片 0.08 0.58* 0.59* 0.02 0.06 0.04 GVMI 冠层 0.31 0.51* 0.83* 0.91* 0.77* 0.67* 叶片 0.32 0.58* 0.58* 0.03 0.05 0.02 WNV 冠层 0.36 0.67* 0.91* 0.89* 0.87* 0.75* 叶片 0.54* 0.58* 0.53* 0.009 0.05 0.01 WCG 冠层 0.28 0.61* 0.92* 0.88* 0.82* 0.71* 叶片 0.45 0.59* 0.55* 0.001 0.05 0.06 Darea 冠层 0.35 0.59* 0.87* 0.91* 0.78* 0.72* 叶片 0.41 0.61* 0.59* 0.02 0.06 0.07 注:*表示达到0.01显著性水平。 表 4 不同生育期夏玉米含水量光谱指数模型验证
Table 4 Model verification in summer maize growth stages
生育期 光谱指数 模拟值(x)与观测值(y)拟合方程 R2 均方根误差 拔节期 WI y=1.12x-0.0018 0.65* 0.0054 MSI y=1.37x-0.0021 0.66* 0.0059 GVMI y=1.30x-0.0015 0.66* 0.0058 WNV y=1.06x+0.002 0.65* 0.0062 WCG y=1.15x+0.0024 0.63* 0.0067 Darea y=1.2388x-0.002 0.64* 0.0056 抽雄期 WI y=0.73x+0.0016 0.63* 0.0057 MSI y=1.01x-0.0016 0.72* 0.0041 GVMI y=0.87x+0.003 0.67* 0.0045 WNV y=0.78x+0.0005 0.67* 0.0041 WCG y=1.09x-0.0033 0.72* 0.0042 Darea y=0.858x-0.0012 0.69* 0.0057 灌浆期 WI y=0.74x-0.0025 0.69* 0.0084 MSI y=1.19x-0.0064 0.74* 0.0058 GVMI y=1.46x-0.0079 0.72* 0.0056 WNV y=0.93x+0.0010 0.71* 0.0054 WCG y=0.92x+0.0013 0.74* 0.0050 Darea y=1.11x+0.0014 0.68* 0.0050 成熟期 WI y=1.25x-0.0014 0.54* 0.0051 MSI y=1.60x-0.0032 0.55* 0.0059 GVMI y=1.57x-0.0071 0.55* 0.0060 WNV y=1.28x+0.0011 0.56* 0.0059 WCG y=1.16x+0.0013 0.55* 0.0056 Darea y=1.02x+0.0053 0.55* 0.0072 注:*表示达到0.01显著性水平。 -
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