| 引用本文: | 林人财,陈 鹤,张宝忠,等.基于多源遥感数据的河套灌区玉米植株氮素浓度诊断及污染风险评估[J].灌溉排水学报,2023,42(2):66-72. |
| LIN Rencai,CHEN He,ZHANG Baozhong,et al.基于多源遥感数据的河套灌区玉米植株氮素浓度诊断及污染风险评估[J].灌溉排水学报,2023,42(2):66-72. |
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| 摘要: |
| 【目的】利用多源遥感数据对河套灌区玉米生育期氮素浓度进行诊断并进行氮素污染风险评估，为施肥决策及农业面源污染溯源提供参考。【方法】基于无人机多光谱遥感数据和实测玉米植株氮素浓度数据，利用多种植被指数量化玉米植株氮素浓度，建立玉米生育期氮素浓度诊断模型。对玉米不同生育阶段的植被指数诊断模型进行评价，得到临界氮素浓度，并对玉米各生育阶段的氮素污染风险进行评估。【结果】2020年河套灌区玉米种植面积最大，为27.5万hm2，在玉米各生育阶段中，拔节期、小喇叭口期、大喇叭口期和花粒期分别以GBNDVI、RVI、NRI、NDVI建立的氮素浓度诊断模型为最优模型；基于氮素浓度诊断模型的遥感监测发现，小喇叭口期、花粒期植株氮素浓度较低，拔节期、大喇叭口期植株氮素浓度较高；玉米氮素污染风险主要发生在拔节期、大喇叭口期，小喇叭口期存在少量的Ⅳ级污染风险，花粒期不存在氮素污染风险。【结论】根据玉米植株氮素浓度诊断模型得到的氮素浓度值，获得以灌溉单元为基础的氮素污染风险等级分布，可为施肥决策和农业面源污染溯源提供合理参考。 |
| 关键词: 氮素浓度；玉米；遥感；污染风险；河套灌区 |
| DOI：10.13522/j.cnki.ggps.2022349 |
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| Diagnosing Nitrogen Content in Maize Canopy in Hetao Irrigation District Using Multi-source Remote Sensing Data |
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LIN Rencai, CHEN He, ZHANG Baozhong, WEI Zheng1, LI Yinong1, SANG Honghui
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1. State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100038, China; 2. Nanchang Institute of Technology, Nanchang 330029, China
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| Abstract: |
| 【Objective】Precision agriculture needs a rapid diagnosis of water and nutrient deficits, which is challenging at large scales in the field. Taking maize as an example, this paper proposes to estimate nitrogen content in maize canopy using remote sensing data.【Method】The study was carried out at Hetao Irrigation District using UAV multi-spectral imagery data measured in 2020. A variety of vegetation indices extracted from the imageries were used to calculate nitrogen content in the canopy when the crop grew to different stages. The model was validated against ground-truth data and was then used to evaluate critical nitrogen concentration and potential nitrogen pollution at different growth stages.【Result】The planted area of maize in Hetao Irrigated District in 2020 was 275 000 hm2. The suitable vegetation indices for calculating canopy nitrogen varied with growing stages; the canopy nitrogen at elongation, early and late tasseling stage and flowering stage was best estimated by GBNDVI, RVI, NRI, and NDVI, respectively. It was found that nitrogen concentration in the canopy was low at the flowering stage, and high at the elongation and later tasseling stage, during which nitrogen pollution could occur. Analysis showed that the risk of nitrogen pollution was Grade 4 in early tasseling stage and zero in flowering stage.【Conclusion】The UAV multispectral image data can be used to estimate nitrogen content in plant and assess the potential of nitrogen pollution at different growing stages at large scales in the field. It can help improve fertilization and reduce the potential of non-point source pollution. |
| Key words: nitrogen concentration; maize; remote sensing; pollution risk; the Hetao Irrigation District |
