| 基于高光谱分数阶微分的烟叶SPAD值估测 |
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| 引用本文： | 吕小艳,薛琳,竞霞,张超,徐海清,朱启法.基于高光谱分数阶微分的烟叶SPAD值估测[J].中国农学通报,2021,37(24):54-59. |
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| 作者姓名： | 吕小艳 薛琳 竞霞 张超 徐海清 朱启法 |
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| 作者单位： | 1.西安科技大学测绘科学与技术学院,西安 710054;2.中国农业大学土地科学与技术学院,北京 100083;3.安徽皖南烟叶有限责任公司,安徽宣城 242000 |
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| 基金项目： | 安徽皖南烟叶有限责任公司科技项目“基于多源卫星数据的烟草长势判断与估产模型构建”(20190563005);国家自然科学基金“反射率与叶绿素荧光协同的小麦白粉病早期探测机理与方法研究”(41601467) |
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| 摘 要： | 基于高光谱分数阶微分估测烟叶SPAD值,旨在提升高光谱数据估测烟叶SPAD值的准确度。首先,确定估测烟叶SPAD值的最优变换方式,并进行分数阶微分处理;然后,基于相关性分析、袋外数据(OOB)重要性、随机森林(RF)相结合的方法,筛选特征波长;最后构建烟叶SPAD值估测模型。结果表明：（1）估测烟叶SPAD值的特征波长主要有绿波段(499、500 nm),红边波段(634、636、702、703、732 nm)、近红外波段(972、1286、1289、1295、1298、1316 nm)、短红外波段(1450、1453、1456、1806 nm)。（2）以1.9阶次的特征波长所构建的RF-SPAD模型的精度最高,R2=0.690,较0、1、2阶次分别提高了22.1%、42.6%、87%,RMSE=2.799,比0、1、2阶分别减少了13.5%,20.2%,27.8%。利用1.9阶次特征波长构建的RF-SPAD模型较整数阶次模型有效提高了烟叶SPAD值的估测精度,为高光谱分数阶微分技术估测SPAD值提供了新的思路。
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| 关 键 词： | 高光谱分数阶微分 SPAD值 烟叶 袋外数据重要性 随机森林 |
| 收稿时间： | 2020-10-26 |
SPAD Value Estimation of Tobacco Leaves Based on Hyperspectral Fractional Differential |
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| Lv Xiaoyan,Xue Lin,Jing Xia,Zhang Chao,Xu Haiqing,Zhu Qifa.SPAD Value Estimation of Tobacco Leaves Based on Hyperspectral Fractional Differential[J].Chinese Agricultural Science Bulletin,2021,37(24):54-59. |
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| Authors: | Lv Xiaoyan Xue Lin Jing Xia Zhang Chao Xu Haiqing Zhu Qifa |
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| Institution: | 1.College of Geomatics, Xi’an University of Science and Technology, Xi’an 710054;2.College of Land Science and Technology, China Agricultural University, Beijing 100083;3.Anhui Wannan Tobacco Leaf Co., Ltd., Xuancheng Anhui 242000 |
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| Abstract: | Tobacco SPAD value was estimated based on hyperspectral fractional differential, and the aim was to improve the accuracy of hyperspectral data estimating tobacco SPAD value. Firstly, the optimal transformation method was determined to estimate the SPAD value of tobacco leaves, and fractional differential processing was carried out. Then, the characteristic wavelengths were selected based on correlation analysis, out-of-bag(OOB) data importance, and random forest (RF). Finally, the SPAD value estimation model of tobacco leaves was constructed. The results showed that: (1) The characteristic wavelengths used to estimate the SPAD value of tobacco leaves mainly included the green band (499 nm, 500 nm), the red edge band (634 nm, 636 nm, 702 nm, 703 nm, 732 nm), the near-infrared band (972 nm, 1286 nm, 1289 nm, 1295 nm, 1298 nm, 1316 nm), short infrared bands (1450 nm, 1453 nm, 1456 nm, 1806 nm). (2) The RF-SPAD model constructed with the characteristic wavelength of order 1.9 had the highest accuracy, R 2= 0.690, which was 22.1%, 42.6%, 87% higher than the 0, 1 and 2 orders respectively; RMSE= 2.799, which was reduced by 13.5%, 20.2% and 27.8% compared with 0, 1, and 2 orders, respectively. Compared with the integer order model, the RF-SPAD model constructed by using the characteristic wavelength of order 1.9 effectively improved the estimation accuracy of tobacco SPAD value, and provided a new idea for the hyperspectral fractional order differential technology to estimate SPAD value. |
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| Keywords: | hyperspectral fractional differential SPAD value tobacco leaves importance of out-of-bag data random forest |
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