Cite as:
Schulz, M.; Thies, B.; Chang, S. &amp; Bendix, J. (2016): <b>Detection of ground fog in mountainous areas from MODIS (Collection 051) daytime data using a statistical approach</b>. <i>Atmospheric Measurement Techniques</i> <b>9</b>, 1135 - 1152.

Resource Description

Title: Detection of ground fog in mountainous areas from MODIS (Collection 051) daytime data using a statistical approach
FOR816dw ID: 159
Publication Date: 2016-03-18
License and Usage Rights: CC Attribution 3.0 License.
Resource Owner(s):
Individual: Martin Schulz
Individual: Boris Thies
Individual: Shih-Chieh Chang
Individual: Jörg Bendix
The mountain cloud forest of Taiwan can be delimited<br/> from other forest types using a map of the ground<br/> fog frequency. In order to create such a frequency map from<br/> remotely sensed data, an algorithm able to detect ground fog<br/> is necessary. Common techniques for ground fog detection<br/> based on weather satellite data cannot be applied to fog occurrences<br/> in Taiwan as they rely on several assumptions regarding<br/> cloud properties. Therefore a new statistical method<br/> for the detection of ground fog in mountainous terrain from<br/> MODIS Collection 051 data is presented. Due to the sharpening<br/> of input data using MODIS bands 1 and 2, the method<br/> provides fog masks in a resolution of 250 m per pixel. The<br/> new technique is based on negative correlations between optical<br/> thickness and terrain height that can be observed if<br/> a cloud that is relatively plane-parallel is truncated by the<br/> terrain. A validation of the new technique using camera data<br/> has shown that the quality of fog detection is comparable to<br/> that of another modern fog detection scheme developed and<br/> validated for the temperate zones. The method is particularly<br/> applicable to optically thinner water clouds. Beyond a cloud<br/> optical thickness of ? 40, classification errors significantly<br/> increase.
| Fog detection | Taiwan | fog | ground fog | ground fog detection | fog remote sensing |
Literature type specific fields:
Journal: Atmospheric Measurement Techniques
Volume: 9
Page Range: 1135 - 1152
Metadata Provider:
Individual: Martin Schulz
Online Distribution:
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