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MODIS遥感数据在我国台湾海峡海雾监测中的应用
The Application of Monitoring Sea Fog in Taiwan Strait Using MODIS Remote Sensing Data
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摘要: 海雾是一种常见的灾害性天气现象。以我国台湾海峡为示范研究区, 利用新一代卫星传感器MODIS的可见光和红外探测通道数据, 在分析海洋、中高云、低云和海雾等不同下垫面的MODIS光谱辐射特征基础上, 选择对海雾具有敏感反应的探测通道, 通过综合判识建立台湾海峡海雾遥感监测模型。利用该模型对2004-2007年我国台湾海峡海雾事件进行监测, 并用福建沿海5个地面气象观测站的能见度数据对监测结果进行验证分析。结果表明:基于MODIS数据的海雾遥感监测模型能够较准确地对台湾海峡海雾分布和发展过程进行监测, 从地面观测数据与卫星监测结果对比验证来看, 海雾监测的准确率可达80 %以上, 具有较高的业务化应用前景。Abstract: The sea fog is a frequent severe weather phenomenon, there are many advantages in monitoring the temporal and spatial change of sea fog using remote sensing technology. The visible light channel data and infrared channel data of new MODIS sensors are used to identify and monitor sea fog in Taiwan Strait. Spectrum radiation characteristics of MODIS data on various earth surface, such as ocean, middle-high-level cloud, low-level cloud and sea fog are analyzed, the results show that there are notable spectrum radiation characteristics differences between the sea fog, low-level cloud and ocean, middle-high-level cloud in the Taiwan Strait region.There are also notable spectrum radiation characteristics distinguish in some channels of visible light and middle infrared bands between sea fog and low-level cloud. On the basis of results, the MODIS channels which are sensitive to sea fog are chosen, and the sea fog remote sensing monitoring model in Taiwan Strait region is established by using compositive method, meanwhile the channels combination and digital monitoring indexes which are fit for the sea fog in Taiwan Strait region are validated.The sea fog events in Taiwan Strait region during 2004-2007 are monitored by using the model which has been established, and the sea fog monitoring results are verified and analyzed using the visibility data measured in five meteorological observing stations in Fujian coastal region.The results show that the veracity of sea fog monitoring model is 83.3 % in the mass, and the monitoring model veracity of strong sea fog is better than that of weak sea fog. The monitoring model veracity of night sea fog is relatively low because there are fewer remote sensing channels in the night on MODIS. After the inconsistent samples between remote sensing monitoring and meteorological observing are analyzed, the result shows that the existence of multi-layer cloud has notable influence to the veracity of sea fog. Research result shows:In the view of the sea fog monitoring results which are verified and analyzed between meteorological observing and remote sensing monitoring, the sea fog remote sensing monitoring model in Taiwan Strait region which is established using MODIS data can reasonably describe the distribution status of sea fog, and can dynamically monitor the distribution and developing process of sea fog, the model is very suitable to apply in the future operational work. But because the fog and cloud remote sensing monitoring is very complex, the variety of digital monitoring indexes of sea fog must be noticed in the practical operational work.
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Key words:
- remote sensing;
- sea fog;
- TaiwanS trait;
- MODIS
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图 1 MODIS卫星影像中海雾区和云区的不同纹理特征
(a) 2007年5月24日, (b)2007年1月12日
Fig. 1 The different texture characteristic of sea fog and cloud in MODIS images
on May 24, 2007 (a) and January 12, 2007(b)
图 2 不同下垫面在MODIS探测通道的反射特性
Fig. 2 The reflect characteristic of different earth surface on MODIS channels
图 3 不同下垫面在MODIS探测通道的辐射特性
Fig. 3 The radiation characteristic of different earth surface on MODIS channels
图 4 台湾海峡海雾MODIS卫星遥感监测流程图
Fig. 4 The flowchart of sea fog monitoring in Taiwan Strait using MODIS data
图 5 台湾海峡海雾MODIS卫星遥感监测结果
Fig. 5 The images of sea fog monitoring in Taiwan Strait using MODIS data
图 6 2004年2月19-20日厦门海域海雾MODIS遥感动态监测结果
Fig. 6 The images of fog MODIS dynamic monitoring in Xiamen sea during February 19-20, 2004
表 1 台湾海峡海雾MODIS遥感监测与地面观测对比验证结果
Table 1 The validation of sea fog MODIS monitoring in Taiwan Strait by meteorology observation data
表 2 台湾海峡海雾MODIS遥感监测准确率统计结果(单位:%)
Table 2 The statistical results of sea fog monitoring precision in Taiwan Strait using MODIS data (unit:%)
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