基于TRMM遥感数据的旱涝时空特征分析
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国家自然科学基金资助项目(41401416、41171336)和江苏省农业科技自主创新资金资助项目(CX(14)5073)


Analysis of Spatial and Temporal Characteristics of Drought and Flood Based on TRMM Remote Sensing Data
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    摘要:

    基于光学遥感数据反演的植被指数和地表温度进行旱涝灾害监测在时间上具有滞后性,降水数据可以更加及时直观地反映地表干湿状态的变化,目前旱涝灾害监测应用地面点上降水观测站点的数据较多,热带降雨测量卫星(TRMM)被动微波遥感为大面积进行旱涝灾害监测提供了可能。利用江苏省1998年1月—2014年3月的TRMM 3B43月降水资料,采用尺度为12的标准化降水指数(SPI12),分析江苏省旱涝时空特征变化规律。分析结果表明:江苏省16年来发生旱涝灾害的几率为34.08%,其中发生旱灾的几率(16.74%)与发生涝灾的几率(17.34%)相接近;江苏省一年四季都易受到旱涝灾害的影响且旱灾与涝灾具有交替出现的特点;1999—2014年间多次出现较严重的旱涝灾害,且江苏中部地区更易受到旱涝灾害的影响。

    Abstract:

    Drought and flood disasters are the main meteorological disasters in China. For the vegetation index and land surface temperature retrieved by optical remote sensing data for drought and flood disaster monitoring has a lag in time, precipitation data can reflect the surface dry and wet state more timely and intuitively. Current methods for monitoring drought and flood disasters based on precipitation extremerely primarily on point-based in situ meteorological stations. Tropical rainfall measurement mission (TRMM) microwave remote sensing offers the possibility of quantifying drought and flood conditions over large spatial extents. This research used scale of 12 standardize precipitation index (SPI12) to explore the spatial and temporal characteristics of flood and drought in Jiangsu Province based on the TRMM 3B43 monthly precipitation data from 1998 to 2014. The month-to-month changes and spatial distributions of SPI12 were got from 1999 to 2014 in Jiangsu Province. It concludes that: the probability of drought and flood disasters happened in Jiangsu Province is 34.08% during 16 years, and the drought (16.74%) is closed to the flood (17.34%). Jiangsu Province is easily influenced by drought and flood disasters in every season of the year, and drought and flood disasters happened alternately. Extreme drought or flood disasters in Jiangsu Province happened many times from 1999 to 2014. Also, central of Jiangsu Province is easily affected by drought and flood disasters. At the same time, this research shows that the TRMM data can be used to monitor the flood and drought disasters in large spatial extents effectively.

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田苗,李卫国.基于TRMM遥感数据的旱涝时空特征分析[J].农业机械学报,2015,46(5):252-257.

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  • 收稿日期:2014-07-30
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  • 在线发布日期: 2015-05-10
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