基于时间序列MODIS影像的暴雨后作物淹没历时提取方法

作物淹没历时是作物洪水淹没减产损失精分析的一个重要指标,由于受作物分布,地形差异等因素影响,直接获取作物淹没历时数据存在困难。作物淹没历时由暴雨期作物淹没历时与暴雨后作物淹没历时两部分构成。现有的暴雨后作物淹没历时提取主要通过流域内的排涝能力和洪涝积水量来估算整个退水历时,因流域排涝数据获取困难,排涝能力以点带面,不能有效表达流域特征,亦不能反映暴雨后作物淹没历时的空间分布,对降雨淹没历时估计能力有限。因此,提出了应用暴雨后长时间序列MODIS数据,结合洪水退去过程有序渐变特点,构建具有稳健性与一致性特点的作物淹没历时指数,并结合最优二分算法分界点提取大范围暴雨后作物淹没历时的新方法。最后以2003年6~8月淮河暴雨洪水及2010年7~9月辽河暴雨洪水为例,通过以实验样田为单位的点比较以及以流域分布为单位的整体对比验证了该方法的准确性和可行性。同时该方法具有数据获取容易,算法实现简单,结果直观可靠,空间特征明显等特点,易于推广应用。

Method on Crop Inundated Time Extraction after Rainstorm Using Time Series MODIS Images

Crop inundated time is one of the most important index for accurate evaluation of crop reduction in flooded area.However,it is difficult to get inundated time directly due to the crop distribution,terrain differences,and other factors.Crop inundated time is consist of the period in rainstorms and after.The current extraction method of crop inundated time after rainstorms applies the ratio between the flood accumulation and the drainage capacity in a watershed to estimate the inundated time.This method application is limited because of the difficulty of getting the basins drainage data,what's more,the drainage capacity is usually replaced by observation points which not only can not represent the watershed characteristics effectively but also can not describe the spatial distribution of crop after rainstorms.Therefore,a new method is proposed based on time-series MODIS data to extract crop inundated time after rainstorms in large scale,which constructs a robust and consistency inundated time index combined with the characteristics of flood receding process ,and then obtains the right time point by the optimal two-part segmentation algorithm.Finally,Huaihe flood in 2003 and Liaohe flood in 2010 are taken as examples to testify this new method.The results showed that the method is reliable.At the same time,this method is simple to implement and intuitive spatially,and applies widely.