光谱技术在土壤水分含量检测中的研究进展

doi:10.3964/j.issn.1000-0593(2020)12-3705-06

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摘要：土壤水分是影响农业生产的重要因素之一，对农作物生长发育情况和最终产量起着关键的作用，然而农业用水浪费现象普遍存在，预计至2020年我国灌溉水利用系数仅为0.55，远低于0.7～0.8的世界先进水平，因此准确有效地判断土壤含水量丰缺情况对农业生产实践具有重要意义，光谱技术利用物体特征谱线的不同，能够同时获取目标的图像信息和光谱信息，从而更直观地表达目标的特征，从而精确、快速、无损地对土壤水分的含量进行动态的检测，该技术极大地促进了农业的精准化、智能化和现代化，在土壤水分含量检测中占有重要地位。文章综述了国内外土壤水分含量检测的最新文献，对基于光谱技术的土壤水分含量检测的研究进展进行了系统地讨论，分析了传统方法的不足，并阐述了光谱成像技术的优势：(1）实时性；(2）无损性；(3）精确性；及其在土壤水分含量检测中的局限性：(1）土壤的构造复杂；(2）泛化能力不足；(3）气候条件制约。重点阐述了光谱在土壤水分检测中的三个关键技术：(1）光谱数据预处理技术，重点对比了常见的预处理技术原理及其效果；(2）光谱特征提取技术，对比了常见的特征光谱提取方法，重点分析了土壤水分的敏感波段；(3）光谱建模技术，重点对比了土壤水分含量检测的线性和非线性模型，分析其原理、应用范围及模型精度，得出非线性模型将成为光谱技术在土壤水分含量检测的主流建模方法。最后依据上述分析，对光谱技术在土壤水分检测领域中的应用前景和研究趋势进行了展望：一是要提高该技术的泛化能力和鲁棒性，建立可用于多种土壤类型的水分检测模型；二是要建立大范围区域并动态实时更新的土壤光谱数据库，为提高模型精度做好数据基础。

关键词：光谱技术；土壤水分检测；光谱预处理；光谱特征提取；光谱建模

Abstract：Soil moisture is one of the important factors affecting agricultural production, and plays a key role in crop growth and development and final yield. However, the waste of agricultural water is widespread, and the utilization rate of water is low. It is estimated that by 2020, China’s irrigation water utilization coefficient will only be It is 0.55, far below the advanced world level of 0.7～0.8. Therefore, the accurate and effective judgment of soil water content abundance is of great significance to agricultural production practice. The detection of soil moisture content has gradually become a research hotspot at home and abroad. Spectral technology can obtain the image information and spectral information of the target simultaneously by utilizing the different characteristic lines of the object, thereby more intuitively expressing the characteristics of the target, and can dynamically and accurately detect the soil moisture content accurately and non-destructively. The technology has greatly promoted the precision, intelligence and modernization of agriculture, and plays an important role in the detection of soil moisture content. This paper reviews the latest literature on soil moisture content detection at home and abroad, systematically discusses the research progress of soil moisture content detection based on spectroscopy technology, analyzes the shortcomings of traditional methods, and expounds the advantages of spectral imaging technology: (1) Real-time；(2) non-destructive; (3) accuracy; and its limitations in the detection of soil moisture content: (1) complex soil structure; (2) insufficient generalization ability; (3) climatic conditions. Three key technologies of spectrum in soil moisture detection are highlighted: (1) Spectral data pretreatment technology, which focuses on the common pretreatment technology principles and effects; (2) Spectral feature extraction technology, which compares common feature spectrum extraction and focuses on the sensitive band of soil moisture. (3) Spectral modeling technology, which focuses on the linear and nonlinear models of soil moisture content detection, analyzes its principle, application range and model accuracy, concludes that the nonlinear model will become the mainstream modeling method of spectral technology in soil moisture content detection. Finally, based on the above analysis, the application prospects and research trends of spectroscopy in the field of soil moisture detection have prospected: Firstly, the generalization ability and robustness of the technology should be improved, and a moisture detection model that can be used for various soil types is established. Secondly, establish a large-area field and dynamically update the soil moisture spectrum database to improve the accuracy of the model.

Key words：Spectral technology; Soil moisture content detection; Spectral pretreatment; Spectral feature extraction; Spectral modeling

收稿日期: 2019-10-15 修订日期: 2020-02-19

中图分类号:

O657.3

基金资助: 国家重点研发计划项目(2017YFD0201502)资助

通讯作者: 李娜 E-mail: cdpc_ln@cdpc.edu.cn

作者简介: 李鑫星，1983年生，中国农业大学信息与电气工程学院食品质量与安全北京实验室副教授 e-mail: lxxcau@cau.edu.cn

引用本文:

李鑫星，梁步稳，白雪冰，李娜. 光谱技术在土壤水分含量检测中的研究进展[J]. 光谱学与光谱分析, 2020, 40(12): 3705-3710.
LI Xin-xing, LIANG Bu-wen, BAI Xue-bing, LI Na. Research Progress of Spectroscopy in the Detection of Soil Moisture Content. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2020, 40(12): 3705-3710.

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