基于时空加权KNN算法的1988-2015年渤海海冰空间分布重建

Reconstruction of spatial distribution of sea ice in Bohai Sea from 1988 to 2015 based on space-time weighted KNN algorithm

  • 摘要: 利用AVHRR和MODIS遥感解译数据,结合与渤海海冰面积相关程度高的日平均温度、3 d-1.8 ℃积温、累积冻冰度日和累积融冰度日等气象因子数据,基于时空加权KNN算法构建了空间分辨率为1 km海冰空间补全模型,重建了1988-2015年渤海海冰空间分布连续日数据集。渤海海冰空间分布补全均方误差为0.03,分类正确率均为87%以上,28年平均正确率为91.87%,均方误差与海冰遥感影像数据缺失率呈中度正相关。结果表明,该模型均方误差较小,且分类正确率高,可以用于渤海海冰空间分布数据补全,空间分辨率高且补全速度快,在海洋环境安全管理领域,尤其对有冰海域海冰灾害风险管理方面有重要的价值。

     

    Abstract: This study used AVHRR and MODIS remote sensing interpretation data, combined with meteorological factors such as daily average temperature, accumulated temperature of 3 d-1.8 ℃, accumulated frozen ice days and accumulated melted ice days that are highly correlated with Bohai sea ice area, constructed a spatial completion model with spatial resolution of 1km based on space-time weighted KNN algorithm, and reconstructed the continuous daily data set of Bohai sea ice spatial distribution from 1988 to 2015. The complete mean square error of the spatial distribution of sea ice in Bohai Sea is 0.03 km2, the classification accuracy is above 87%, and the average accuracy in 28 years is 91.87%. The mean square error is positively correlated with the missing rate of sea ice remote sensing image data. As shown by results, the model has small mean square error and high classification accuracy, and can be used to complete the spatial distribution data of sea ice in Bohai Sea, with high spatial resolution and fast completion speed. It is of important practical value in the field of marine environmental safety management, especially in the risk management of sea ice disasters in icy waters.

     

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