| 引用本文: | 哈布热,张宝忠,李思恩,等.基于冠层光谱特征的冬小麦植株含水率诊断研究[J].灌溉排水学报,2018,37(10):9-15. |
| Habure,ZHANG Baozhong,LI Sien,et al.基于冠层光谱特征的冬小麦植株含水率诊断研究[J].灌溉排水学报,2018,37(10):9-15. |
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| 摘要: |
| 【目的】快速、精确地获得作物水分状况。【方法】采用高光谱采样数据分析方法，研究了北京大兴冬小麦不同生育期不同水分条件下的冠层光谱变化特点，筛选了水分光谱敏感波段，构建了冬小麦水分状况诊断模型。【结果】①在750～1 075 nm近红外反射平台拔节—抽穗期、抽穗—灌浆期冬小麦冠层光谱反射率随植株含水率的增大而上升，在350～750 nm 的可见光区域灌浆—成熟期冬小麦冠层光谱反射率随植株含水率的增大而降低；②不同生育期冬小麦植株水分状况均与650～775 nm波段密切相关，其中对冬小麦植株含水率变化最为敏感的波段为661 nm和771 nm；③通过筛选光谱参数模型、构建基于敏感波段回归模型并综合分析2类模型对冬小麦植株含水率的监测效果发现，冬小麦不同生育期植株含水率监测最佳模型均为光谱参数模型。【结论】在利用光谱技术监测冬小麦植株含水率时，包含661 nm及771 nm附近波段的水分监测光谱参数模型效果最佳。 |
| 关键词: 光谱； 植株含水率； 敏感波段； 光谱特征参数； 水分 |
| DOI：10.13522/j.cnki.ggps.20180021 |
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| Estimating Water Content of Winter Wheat Canopy Based on Its Spectral Characteristics |
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Habure, ZHANG Baozhong, LI Sien, PENG Zhigong, HAN Nana, LIU Lu
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1. China Agricultural University, Beijing 100083, China; 2. China Institute of Water Resources and Hydropower Research, Beijing 100038, China; 3. Beijing Forestry University, Beijing 100083, China
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| Abstract: |
| 【Objective】 Knowing the change in water content of crops is imperative in agronomical management, and the purpose of this paper is to present a quick yet accurate method to diagnose real-time dynamics of water content of winter wheat canopy. 【Method】 We used high spectral sampling data measured from a winter wheat field in Daxing District of Beijing. The spectral characteristics of the canopy under different water conditions were analyzed. The spectrum band sensitive to water was screened and a diagnosis model was developed to estimate the canopy water content.【Result】①During the jointing-heading and the heading-milk-filling stages, the spectral reflectance of the canopy in wavelength of 750~1 075 nm near the infrared reflection increased with canopy water content, while during the milk-filling-mature stage the spectral reflectance of the canopy in the visible wavelength of 350~750 nm decreased as the canopy water content increased. ②The canopy water content during different growth periods of the crop was related to the wavelength in the range of 650~775 nm, with wavelength of 661 nm and 771 nm most sensitive. ③We presented an regressive model to link the sensitive band on the canopy water content.【Conclusion】When using the spectral technology to monitor canopy water content of winter wheat, the regressive model using the wavelength of 661 nm and 771 nm is most accurate. |
| Key words: spectrum; water content of plants; sensitive band; spectral characteristic parameter; moisture |
