Schulz, M.; Thies, B.; Chang, S. & 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
email:
bendix <at> staff.uni-marburg.de
Deutschhausstraße 12
Room No. 02 A 48
35032 Marburg
Faculty of Geography
Germany
Abstract:
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.
Keywords:
| Fog detection | Taiwan | fog | ground fog | ground fog detection | fog remote sensing |
