There is an urgent need for the development of a method that can undertake rapid, effective, and accurate monitoring and identification of fog by satellite remote sensing, since heavy fog can cause enormous disasters ...There is an urgent need for the development of a method that can undertake rapid, effective, and accurate monitoring and identification of fog by satellite remote sensing, since heavy fog can cause enormous disasters to China’s national economy and people's lives and property in the urban and coastal areas. In this paper, the correlative relationship between the reflectivity of land surface and clouds in different time phases is found, based on the analysis of the radiative and satellite-based spectral characteristics of fog. Through calculation and analyses of the relative variability of the reflectivity in the images, the threshold to identify quasi-fog areas is generated automatically. Furthermore, using the technique of quick image run-length encoding, and in combination with such practical methods as analyzing texture and shape fractures, smoothness, and template characteristics, the automatic identification of fog and fog-cloud separation using meteorological satellite remote sensing images are studied, with good results in application.展开更多
Lightning is a typical example of an instantaneous random point source target. It has close connection with severe convective phenomena such as a thunderstorm, whose distribution, variation, position and forecasting c...Lightning is a typical example of an instantaneous random point source target. It has close connection with severe convective phenomena such as a thunderstorm, whose distribution, variation, position and forecasting can be acquired through lightning observation. In this paper, we discuss the way to achieve instantaneous lightning signal intensification and detection from geostationary orbit by using the differences between the lightning signal and the slowly changing background noise such as that of cloud, land and ocean, combining three methods, spectral filtering, spatial filtering and background noise, enabling removal between frames. After six months of operation in orbit, lightning within the coverage of the Geostationary Lightning Imager was effectively detected, strongly supporting the case for shorttime and real-time early warning, forecasting and tracking of severe convective phenomena in China.展开更多
Volcanic ash cloud has serious impacts on aviation.With volcanic ash dispersion,it also has a profound and long-term impact on climate and the environment.A new volcanic ash cloud detecting method (SWIR-TIR Volcanic A...Volcanic ash cloud has serious impacts on aviation.With volcanic ash dispersion,it also has a profound and long-term impact on climate and the environment.A new volcanic ash cloud detecting method (SWIR-TIR Volcanic Ash method,STVA) is presented that uses satellite images of Medium Resolution Spectral Imager (MERSI) and Visible and Infrared Radiometer (VIRR) on board the second generation Polar-Orbiting meteorological satellite of China (FY-3A).STVA is applied in detecting Iceland's Eyjafjallajokull volcano eruption.Compared with the traditional Split Window Temperature Difference method (SWTD),the results show that STVA is more sensitive to volcanic ash cloud than SWTD and can fairly extract volcanic ash information from the background of meteorological cloud and the ocean.Ash Radiance Index (ARI) and Absorbing Aerosol Index (AAI) derived from Metop-A satellite images are used to validate the performance of STVA.It is shown that STVA provides similar results with ARI and AAI.FY-3A/MERSI,VIRR and Terra /MODIS data are used to test STVA and SWTD.It is demonstrated that STVA derived from FY-3A satellite data is more effective in complicated meteorological conditions.This study shows great potential of using China's own new generation satellite data in future global volcanic ash cloud monitoring operation.展开更多
基金Key research project "Research of Shanghai City and Costal Heavy Fog Remote Sensing Detecting and Warning System" of Science and Technology Commission of Shanghai Municipality (075115011)
文摘There is an urgent need for the development of a method that can undertake rapid, effective, and accurate monitoring and identification of fog by satellite remote sensing, since heavy fog can cause enormous disasters to China’s national economy and people's lives and property in the urban and coastal areas. In this paper, the correlative relationship between the reflectivity of land surface and clouds in different time phases is found, based on the analysis of the radiative and satellite-based spectral characteristics of fog. Through calculation and analyses of the relative variability of the reflectivity in the images, the threshold to identify quasi-fog areas is generated automatically. Furthermore, using the technique of quick image run-length encoding, and in combination with such practical methods as analyzing texture and shape fractures, smoothness, and template characteristics, the automatic identification of fog and fog-cloud separation using meteorological satellite remote sensing images are studied, with good results in application.
文摘Lightning is a typical example of an instantaneous random point source target. It has close connection with severe convective phenomena such as a thunderstorm, whose distribution, variation, position and forecasting can be acquired through lightning observation. In this paper, we discuss the way to achieve instantaneous lightning signal intensification and detection from geostationary orbit by using the differences between the lightning signal and the slowly changing background noise such as that of cloud, land and ocean, combining three methods, spectral filtering, spatial filtering and background noise, enabling removal between frames. After six months of operation in orbit, lightning within the coverage of the Geostationary Lightning Imager was effectively detected, strongly supporting the case for shorttime and real-time early warning, forecasting and tracking of severe convective phenomena in China.
基金supported by National Basic Research Program of China (Grant No. 2010CB950700)
文摘Volcanic ash cloud has serious impacts on aviation.With volcanic ash dispersion,it also has a profound and long-term impact on climate and the environment.A new volcanic ash cloud detecting method (SWIR-TIR Volcanic Ash method,STVA) is presented that uses satellite images of Medium Resolution Spectral Imager (MERSI) and Visible and Infrared Radiometer (VIRR) on board the second generation Polar-Orbiting meteorological satellite of China (FY-3A).STVA is applied in detecting Iceland's Eyjafjallajokull volcano eruption.Compared with the traditional Split Window Temperature Difference method (SWTD),the results show that STVA is more sensitive to volcanic ash cloud than SWTD and can fairly extract volcanic ash information from the background of meteorological cloud and the ocean.Ash Radiance Index (ARI) and Absorbing Aerosol Index (AAI) derived from Metop-A satellite images are used to validate the performance of STVA.It is shown that STVA provides similar results with ARI and AAI.FY-3A/MERSI,VIRR and Terra /MODIS data are used to test STVA and SWTD.It is demonstrated that STVA derived from FY-3A satellite data is more effective in complicated meteorological conditions.This study shows great potential of using China's own new generation satellite data in future global volcanic ash cloud monitoring operation.
