| Technology and Methodology |
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Automatic detection of night time radiation fog based on SBDART radiative transfer model and the analysis of time series |
| ZHANG Weikang, MA Huiyun, ZOU Zhengrong, HE Zhuochen, ZHAO Guoqing |
| Department of Surveying and Geo-informatics, Central South University, Changsha 410083, China |
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Abstract How to obtain suitable threshold to distinguish radiation fog,clear sky surface and clouds is the focus of the study of fog detection. The Santa Barbara DISORT atmospheric radiative transfer(SBDART)model can simulate the fog top brightness temperature. In this paper,the authors obtained the brightness temperature difference(BTD)between MODIS B20 and MODIS B31 bands based on the model and applied it to the detection of radiation fog at night. The data used for feasibility test were from EOS MODIS satellite in the North China Plain on November 25, 2007,and ground validation data were from the National Satellite Meteorological Center. The varification results show that the accuracy of using the model to monitor the night time radiation fog (POD)is 78.3%,the false alarm rate (FAR)is 21.7%, the reliability index(CSI)is 0.643,and the Kappa factor is 0.730. To further validate the stability of the method,the authors selected the sequence of eight satellite images in northern China for the time series analysis. The results show that the mean value of reliability index is 0.744,suggesting that the proposed method can serve as the foundation of night time fog forecasting and parameter inversion.
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| Keywords
remote sensing
vegetation cover
trend analysis
dynamic change
Bashang Area of Hebei Province
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Issue Date: 28 March 2014
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2014,
Vol. 26
