首页|基于连续小波变换算法的多阶段小麦生长智能遥感监测研究

基于连续小波变换算法的多阶段小麦生长智能遥感监测研究

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遥感技术的应用显著提升了对小麦生长监测的效率,但在对遥感图像的分析中,仍然缺乏有效方法.因此,此次研究引入了连续小波变换来更好地对遥感图像进行分析,从而对小麦生长状态进行有效监测.在性能分析中,研究提出的方法能够在200 nm～2 000 nm的范围内对小麦不同阶段的生长状态进行准确判断;进一步研究发现,在4-6尺度下,研究所提出方法能够显著反映小麦叶片的光谱反射率差异;在对小麦产量预测分析中,连续小波变换处理下,以返青期-抽穗期-花后期为标准的产量预测最为准确,其相关系数为0.86,均方根误差为58.6 g/m2,平均绝对百分比误差为10.6％.明显优于比较算法.研究为有效监测小麦生长状况的研究提供了有价值的研究方向.
Intelligent remote sensing monitoring of multi-stage wheat growth based on continuous wavelet transform algorithm
The application of remote sensing technology has significantly improved the efficiency of monitoring wheat growth,but there is still a lack of effective methods in analyzing remote sensing images.Therefore,this article introduces continuous wavelet trans-form to better analyze remote sensing images and effectively monitor the growth status of wheat.In performance analysis,the proposed method can accurately determine the growth status of wheat at different stages within the range of 200-2000nm.Further research has found that the proposed method can significantly reflect the spectral reflectance differences of wheat leaves at the 4-6 scale.In the a-nalysis of wheat yield prediction,continuous wavelet transform processing is the most accurate,with a correlation coefficient of 0.86,a root mean square error of 58.6g/m2,and an average absolute percentage error of 10.6％,based on the standard of returning to green stage heading stage late flowering stage.Significantly superior to comparative algorithms.The research provides valuable re-search directions for effectively monitoring the growth status of wheat.

remote sensingcontinuous wavelet transformwheatmonitoringspectral reflectance

王法景、董拴涛、冯旭

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杨凌职业技术学院,陕西杨凌 712100

遥感 连续小波变换 小麦 监测 光谱反射率

陕西省重点研发计划陕西省重点研发计划陕西省重点研发计划陕西省林业科技重大专项陕西省教育厅科研计划项目杨凌职业技术学院校内基金项目杨凌职业技术学院校内基金项目杨凌职业技术学院校内基金项目杨凌职业技术学院校内基金项目

2023-YBNY-0422023-YBNY-2232024-YBNY-0806SXLK2023-02-4122JK0747JD22-02ZK21-37JG2022001JB2023-001

2024

10.14016/j.cnki.1001-9227.2024.06.273

自动化与仪器仪表
重庆工业自动化仪表研究所,重庆市自动化与仪器仪表学会

自动化与仪器仪表

CSTPCD
影响因子：0.327
ISSN：1001-9227
年,卷(期)：2024.(6)
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