杜娟, 李维, 张鹏林. 夜间陆地辐射雾的遥感时序数据检测[J]. 武汉大学学报 ( 信息科学版), 2019, 44(8): 1162-1168. DOI: 10.13203/j.whugis20170258
引用本文: 杜娟, 李维, 张鹏林. 夜间陆地辐射雾的遥感时序数据检测[J]. 武汉大学学报 ( 信息科学版), 2019, 44(8): 1162-1168. DOI: 10.13203/j.whugis20170258
DU Juan, LI Wei, ZHANG Penglin. Nighttime Terrestrial Radiation Fog Detection Using Time Series Remote Sensing Data[J]. Geomatics and Information Science of Wuhan University, 2019, 44(8): 1162-1168. DOI: 10.13203/j.whugis20170258
Citation: DU Juan, LI Wei, ZHANG Penglin. Nighttime Terrestrial Radiation Fog Detection Using Time Series Remote Sensing Data[J]. Geomatics and Information Science of Wuhan University, 2019, 44(8): 1162-1168. DOI: 10.13203/j.whugis20170258

夜间陆地辐射雾的遥感时序数据检测

Nighttime Terrestrial Radiation Fog Detection Using Time Series Remote Sensing Data

  • 摘要: 针对目前单时相遥感夜间陆地辐射雾检测不能有效分离雾和地表、低云的问题,利用日本第2代多功能卫星数据的高时间分辨率特性,提出了基于时序特征和支持向量机的夜间陆地辐射雾检测模型。该模型首先在单时相夜间陆地辐射雾检测基础上,使用第1和第4波段亮温差时序曲线构造的亮温差累积特征将夜间地表与陆地辐射雾和低云分离,然后利用第1波段亮温时序曲线构造的亮温变化累积特征、斜率匹配特征和频域奇异性特征,结合支持向量机进行夜间雾和低云的分类,从而实现基于时序数据的夜间陆地辐射雾检测。对两期遥感时序数据进行实验发现,与单时相夜间陆地辐射雾检测相比,利用时序数据的方法较好地提高了夜间陆地辐射雾的检测精度。

     

    Abstract: In this paper, we propose a nighttime terrestrial radiation fog detection model using time series data of Multifunctional Transport Satellite-2 (MTSAT-2), which addresses the difficulty in nighttime fog detection with mono-temporal remote sensing data. The nighttime fog is firstly extracted by using monotemporal image. To take advantage of high temporal resolution of MTSAT-2, the temporal curves of brightness temperature difference between band 1 and band 4 and the temporal curves of brightness temperature of band 1 are built based on the nighttime fog detection result of mono-temporal image. The land surface were separated from the nighttime fog and the low clouds by the bright temperature difference accumulate characteristic established by the temporal curves of brightness temperature difference. The nighttime fog are detected by combining three temporal characteristics with support vector classification. The three temporal characteristics are the bright temperature change accumulate characteristic, slope match characteristic and frequency domain singularity characteristic, which are established by the temporal curves of brightness temperature. The experiment results of two days show that the nighttime terrestrial radiation fog detection using time series data has a higher accuracy than the mono-temporal method.

     

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