| 基于多角度高光谱遥感的冬小麦叶片含水率估算模型 |
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| 引用本文： | 郭建茂,高云峰,李淑婷,白玛仁增,王阳阳,张一甲,刘荣花. 基于多角度高光谱遥感的冬小麦叶片含水率估算模型[J]. 安徽农业大学学报, 2019, 46(1): 124-132 |
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| 作者姓名： | 郭建茂 高云峰 李淑婷 白玛仁增 王阳阳 张一甲 刘荣花 |
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| 作者单位： | 南京信息工程大学气象灾害预报预警与评估协同创新中心/江苏省农业气象重点实验室,南京210044;南京信息工程大学应用气象学院,南京210044;南京信息工程大学应用气象学院,南京,210044;中国气象局/河南省农业气象保障与应用技术重点实验室,郑州,450003 |
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| 基金项目： | 江苏省重点研发计划（现代农业）项目（BE2015365）, 公益性行业（气象）科研专项（GYHY201506018）, 江苏省农业气象重点实验室基金(KYQ201304), 河南省农业气象保障与应用技术重点实验室基金课题(AMF201401)和南京信息工程大学大创项目（201710300115）共同资助。 |
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| 摘 要： | 准确的作物水分监测对于旱情评估具有重要意义。在分析研究区冬小麦多角度光谱特征后,利用不同水分处理下冬小麦实测叶片含水率和实测多角度光谱数据,基于植被光谱指数法,建立不同观测角度下冬小麦光谱植被指数、水分敏感波段光谱指数与叶片含水率之间的数学模型。结果显示,相对方位角与相对天顶角越小时,观测到的光谱指数与叶片含水率的相关关系越优;敏感波段组合构建的光谱指数中,1450nm波段分别与其他波段组合的NDSI、RSI指数与叶片含水率相关性在各观测角度条件下均较好,1 450 nm波段是冬小麦叶片含水率研究的最佳敏感波段;选取常见的4种植被指数(NDVI、EVI、WI和NDII)中WI和NDVI在各观测角度下与叶片含水率的相关性优于其他两种指数,决定系数R2均在0.83以上,P0.01呈极显著相关;综上建立的多角度光谱叶片含水率估算模型,平均相对误差MRE均小于0.154、均方根误差RMSE均小于0.098,拟合效果较好,尤其是光谱指数NDSI1160,1450、NDSI980,1450和植被指数NDVI、WI;基于以上4种指数建立的最优观测角度(0°,30°)模型,其中植被指数WI的估算效果最好,相关系数在各角度均达到5%的相关显著水平,MRE0.03,可作为最优观测角度反演研究的最优植被指数。
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| 关 键 词： | 冬小麦 多角度冠层光谱特征 光谱指数 叶片含水率 |
Estimation model of leaf water content of winter wheat based on multi-angle hyperspectral remote sensing |
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| GUO Jianmao,GAO Yunfeng,LI Shuting,PEMA Rigzin,WANG Yangyang,ZHANG Yijia and LIU Ronghua. Estimation model of leaf water content of winter wheat based on multi-angle hyperspectral remote sensing[J]. Journal of Anhui Agricultural University, 2019, 46(1): 124-132 |
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| Authors: | GUO Jianmao GAO Yunfeng LI Shuting PEMA Rigzin WANG Yangyang ZHANG Yijia LIU Ronghua |
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| Affiliation: | Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/Jiangsu Key Laboratory of Agricultural Meteorology, Nanjing 210044; Nanjing University of Information Science & Technology, Nanjing 210044,Nanjing University of Information Science & Technology, Nanjing 210044,Nanjing University of Information Science & Technology, Nanjing 210044,Nanjing University of Information Science & Technology, Nanjing 210044,Nanjing University of Information Science & Technology, Nanjing 210044,Nanjing University of Information Science & Technology, Nanjing 210044 and CMA/Henan Key Laboratory of Agrometeorological Support and Applied Technique, Zhengzhou 450003 |
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| Abstract: | Accurate crop moisture monitoring is great importance for drought assessment. Based on the analysis of multi-angle spectral characteristics of winter wheat under different water treatments, we analyzed the leaf moisture content and measure the multi-angle spectral data of winter wheat under different water treatments, then by using the vegetation spectral index method, and established the mathematical models of spectral indices and leaf water content under different observation angles. The results showed that the smaller the relative azimuth and relative zenith angle, the better the correlation between the observed spectral index and leaf moisture content. The spectral indexes of the sensitive band combination were the NDSI and RSI index of the 1 450 nm band combined with other bands, and the correlation with the water content of the leaves was good under various observation angles, so the 1 450 nm band was the best sensitive band for the study of leaf water content of winter wheat. The common 4 planting indexes (NDVI, EVI, WI, NDII) were selected for WI and NDVI, the correlation between the water content and the leaf moisture content were better than that of the other two indexes. The determination coefficient R2 was above 0.83, P<0.01 was extremely significant correlation. From the multi-angle spectral leaf moisture estimation model, the error MRE was less than 0.154, the root mean square error RMSE was less than |
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| Keywords: | winter wheat multi-angle canopy spectroscopy spectral index leaf water content |
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