| 摘要: |
| 【目的】 利用我国第二代风云极轨卫星（FY-3C与FY-3D）的归一化植被指数（NDVI）数据，对乌克兰农作物长势进行持续监测，为及时且准确掌握乌克兰作物生长状况提供科学依据。【方法】 文章基于当旬NDVI值与过去多年历史平均值构建的NDVI差值模型、以及当旬NDVI值与历史平均值绘制的时间序列曲线，动态监测2022年3—7月乌克兰冬季作物生长状况。基于NDVI差值模型，从3月上旬开始，以旬为尺度绘制作物长势分布图，并根据NDVI差值模型计算结果，将作物长势划分为5个等级：差、较差、正常、较好和好。同时，乌克兰全境，尤其是俄罗斯相邻的北部和东部5个州的NDVI平均值被用于绘制作物生长时间序列曲线。【结果】 结果显示，2022年3—7月初，乌克兰的农作物长势呈“前期较差，后期较好”的状态，整体优于多年均值。生成的NDVI时间序列曲线显示，4月上升略有滞后，4月底到6月底逐步升高，7月初NDVI值略有下降，但仍高于过去多年的平均值。【结论】 上述结果证明乌克兰冬季作物的生长状况并未因俄乌冲突的发生和持续受到严重影响。 |
| 关键词: 作物长势 风云气象卫星 差值模型 乌克兰 |
| DOI：10.12105/j.issn.1672-0423.20220503 |
| 分类号: |
| 基金项目:科技创新2030——重大项目课题“多模式协同的农情反演、预测及智能计算”（2021ZD0113704）；龙计划项目（58944） |
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| Ukrainian crop growth monitoring with the Chinese meteorological satellite data |
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Li Yuxuan1,2, Leng Pei1, Fan Jinlong2
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1.Chinese Academy of Agricultural Sciences，Beijing 100081，China;2.National Satellite Meteorological Center，Beijing 100089，China
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| Abstract: |
| [Purpose] Thanks to the global coverage of the second generation FENGYUN polar orbiting satellite，the normalized difference of vegetation index NDVI retrieved from FY3C VIRR and FY3D MERSI were used to monitor the crop growth condition in Ukraine，which provides a scientific basis for timely and accurate information on crop growth in Ukraine.[Method] The NDVI difference model between the current value and the historical mean in the past few years and the time series of NDVI at present and the historical mean were used to closely monitor the changes of the crop vegetation from March to June when was the winter crop growth season in 2022. Based on the NDVI difference model，the spatial condition of crop growth was mapped every dekad since the early March and the crop growth condition was categorized into five classes，such as worse，poor，normal，favorable，and good. The NDVI value averaged for the entire country of Ukraine and five states in the north and east neighboring with Russia were used for following the crop growth cycle.[Result] The results showed that the crop growth in Ukraine from March to early July 2022 was in a condition of “poor in the early season and better in the late season” that was better than the multi-year average. The generated NDVI time series curve presented a slight lag in April，a gradual increase from the end of April to the end of June，and a slight decrease in NDVI values in the beginning of July but still higher than the past few years average.[Conclusion] It proofs that the growth of winter crops in Ukraine was not seriously affected. |
| Key words: crop growth Fengyun meteorological satellite difference model Ukraine |
