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| نشریه دانشکده فنی | ||
| Article 9, Volume 41, Issue 2 - Serial Number 1434, April 2007 PDF (2.04 M) | ||
| Abstract | ||
| Short-time detection and forecasting of fog and low stratus clouds have wide application in aviation. Meteorological satellites have created vast hopes for meteorologists. The present number of observing stations in land and sea are not adequate in determination of actual fog corona. To compensate for the lack of information, deployment of remote sensing technology especially at nighttime seems necessary. During the daytime, due to the high contrast of fog and low St Albedos, their detection is relatively simple. In the nighttime and in the absence of sunlight, however, the contrast due to thermal radiation and consequently different brightnesses could be a tool in distinction of these kinds of clouds. Due to the same temperature of fogs and land surfaces, their distinctions in the thermal channels are not always possible. Consequently, differences in their spectral emissivities will be used in distinguishing fogs from land and water surfaces. In this research, five techniques in detection of fogs and low clouds using different channels of SEVIRI sensor on board of Meteosat Second Generation (MSG-1) have been offered. These techniques are 1-Brightness Temperature Difference Technique, 2- Band 4 and 5 day and night technique, 3- Daytime band 1 and 3 indices, 4- Ratio of band 3 to band 1 and band 9 during the daytime, 5- Ratio of band 4 to band 1 and band 9 during the daytime. The percentages of low cloud and fogs coverage in the scene detected in these techniques are 91, 76.8, 81.66, 95.85 and 88.95 respectively. Results of different methods are in an acceptable agreement with each other. As a result, 2nd technique for the nighttime and 4th technique for the daytime is recommended. A satellite of this kind will be flying soon over Indian Ocean over 63E longitude on a geostationary orbit, that the use of its images in extracting meteorological parameters over Iran’s plateau is strongly recommended. In this paper, a new method for detection of snow-covered surfaces is also introduced. | ||
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