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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union

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Atmos. Meas. Tech., 9, 1135-1152, 2016
https://doi.org/10.5194/amt-9-1135-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
Research article
18 Mar 2016
Detection of ground fog in mountainous areas from MODIS (Collection 051) daytime data using a statistical approach
Hans Martin Schulz1, Boris Thies1, Shih-Chieh Chang2, and Jörg Bendix1 1Laboratory for Climatology and Remote Sensing, Faculty of Geography, Philipps University, Marburg, Germany
2Department of Natural Resources and Environmental Studies, National Dong Hwa University, Hualien, Taiwan
Abstract. The mountain cloud forest of Taiwan can be delimited from other forest types using a map of the ground fog frequency. In order to create such a frequency map from remotely sensed data, an algorithm able to detect ground fog is necessary. Common techniques for ground fog detection based on weather satellite data cannot be applied to fog occurrences in Taiwan as they rely on several assumptions regarding cloud properties. Therefore a new statistical method for the detection of ground fog in mountainous terrain from MODIS Collection 051 data is presented. Due to the sharpening of input data using MODIS bands 1 and 2, the method provides fog masks in a resolution of 250 m per pixel. The new technique is based on negative correlations between optical thickness and terrain height that can be observed if a cloud that is relatively plane-parallel is truncated by the terrain. A validation of the new technique using camera data has shown that the quality of fog detection is comparable to that of another modern fog detection scheme developed and validated for the temperate zones. The method is particularly applicable to optically thinner water clouds. Beyond a cloud optical thickness of  ≈ 40, classification errors significantly increase.

Citation: Schulz, H. M., Thies, B., Chang, S.-C., and Bendix, J.: Detection of ground fog in mountainous areas from MODIS (Collection 051) daytime data using a statistical approach, Atmos. Meas. Tech., 9, 1135-1152, https://doi.org/10.5194/amt-9-1135-2016, 2016.
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Short summary
The mountain cloud forest of Taiwan can be delimited from other forest using a map of the ground fog frequency. An algorithm able to detect ground fog from satellite data is necessary for the creation of such a map. Common fog detection algorithms are not applicable in Taiwan as they rely on assumptions that are not met by most fog occurrences in Taiwan. Therefore a new statistical method for ground fog detection in mountainous areas that is based only on a few basic assumptions is presented.
The mountain cloud forest of Taiwan can be delimited from other forest using a map of the ground...
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