Journal of Arid Meteorology

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Drought Monitoring in Winter Wheat Planting Area of China Based on FY-3C Microwave Data

LIU Kai, SUN Li, SUN Haiyue, XUE Wanqing, ZHAI Guanghui   

  • Online:2017-12-29 Published:2017-12-29


刘  凯,孙  丽,孙海玥薛婉擎翟光辉   

  1. 农业部耕地利用遥感重点实验室,农业部规划设计研究院,北京 100125
  • 通讯作者: 孙丽,女,博士,高级工程师,主要从事农业灾害遥感监测研究.
  • 作者简介:刘凯,男,硕士,主要从事农业旱情遥感监测方面的研究.。
  • 基金资助:



Microwave data have been widely used to retrieve soil moisture, it is not influenced by clouds. But it can only monitor the surface soil moisture from 0 cm to 5 cm depth, which can’t reflect objectively drought degree of soil at plow layer. Temperature-vegetation drought index (TVDI) based on MODIS data can preferably evaluate the drought of crop. Unfortunately, it is restricted by clouds. So the combination of two methods can effectively perform the all-weather monitoring of crop drought. This research established the relationship between the interval critical values of surface soil moisture retrieved by FY-3C/MWIR data and the corresponding maximum TVDI retrieved by MODIS according to interval division method. Furthermore, the monthly models of FY-3C/SM-TVDI were established during the growing season of winter wheat from 2015 to 2016, which preliminary implemented the soil drought monitoring from 10 cm to 20 cm depths based on the microwave data in main planting area of winter wheat in China. And on this basis these models were validated by FY-3C microwave radiation data with the same periods from 2014 to 2015. The results showed that the difference was not significant (P>0.05) between most simulation values and real values except for the simulation values in October, which indicated that the performance of models on reflecting drought condition was better on the whole.

Key words: drought monitoring, FY-3C microwave radiation data, TVDI, FY-3C/SM-TVDI model


微波数据能有效克服云层影响,实现土壤水分的全天候遥感监测,但仅局限于土壤表层(0~5 cm),无法客观反映耕作层土壤的实际干旱程度。本研究采用区间划分方法,分析逐日风云微波遥感数据(FY-3C/MWRI)反演的表层土壤水分各区间临界值与对应区间基于MODIS数据得到的温度植被干旱指数(TVDI)最大值的关系,建立2015—2016年冬小麦生育期内月尺度的FY-3C/SM-TVDI模型,初步实现冬小麦主要种植区内微波遥感监测10~20 cm深度土层旱情模型。在此基础上,利用2014—2015年数据进行模型验证。结果表明,模型总体构建效果较好,大部分模拟值与真实值差异不显著(P>0.05),10月模拟值较真实值显著偏低(P<0.05)。

关键词: 干旱监测, FY-3C/MWRI数据, 温度植被干旱指数(TVDI), FY-3C/SM-TVDI模型

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