基于动态背景场沙尘覆盖度指数的Himawari-8沙尘判识及强度估算方法

针对沙尘遥感监测开展的研究很多，但对于一些强度较弱的沙尘，在不同地表状态下呈现的复杂状况，传统方法识别效果较差。采用Himawari-8卫星数据，提出一种针对性的识别方法，基于动态亮温差底图引入了沙尘覆盖度指数(fractional dust cover index, FDCI)。该指数在一个较确定范围内对不同强度沙尘都可进行有效判识，并能提升弱沙尘识别效果。在此基础上构建了基于指数判识结果的沙尘强度指数(enhanced dust intensity index, EDII)估算方法。文中列举了4次沙尘过程的判识结果，并结合地面观测数据进行了验证。其中对2017年5月3日沙尘强度的地面验证表明，位于观测区的27个站中有22个站的地面观测沙尘强度与估算结果一致。对于各种地表及强度条件下的沙尘监测，该方法是对分裂窗亮温差法的有效改进。

An algorithm for dust detection and intensity estimation based on Himawari-8 using Fractional Dust Cover Index by dynamic background

As the main component of tropospheric aerosols, dust has a complex influence on global weather and climate ecosystems. At the same time, as an air pollutant, it is harmful to human health. Dust weather usually erupts in spring and has great influence on productions and lives in arid and semi-arid areas in northern China. Many studies on dust detection by remote sensing have been carried out in the past and a lot of accomplishments have been achieved. However, for some thin dust and complex conditions under various surface, the effect of traditional methods is poor. In our paper, Himawari-8 data were used to propose a targeted identification method, thus the Fractional Dust Cover Index (FDCI) is introduced based on the dynamic brightness temperature background map.