Laboratory for
Climatology and Remote Sensing

Abstract:

Up until now montane cloud forest (MCF) in Taiwan has only been mapped for selected areas of vegetation plots. This thesis presents the first comprehensive map of MCF distribution for the entire island. For its creation, a Random Forest model was trained with vegetation plots from the National Vegetation Database of Taiwan that were classified as “MCF” or “non-MCF”. This model predicted the distribution of MCF from a raster data set of parameters derived from a digital elevation model (DEM), Landsat channels and texture measures derived from them as well as ground fog frequency data. The latter have been derived from the Moderate Resolution Imaging Spectroradiometer (MODIS). For the detection of ground fog in MODIS imagery a new algorithm has been developed. It does not rely on cloud microphysical assumptions and was validated using camera data.

Abstract:

The detection of clouds and the analysis of cloud frequency play an important role for operational weather prediction as well as for climate– ecological studies. A threshold technique for cloud detection in the tropical mountainous area of Ecuador is presented which is based on National Oceanic and Atmospheric Administration Advanced Very High Resolution Radiometer (NOAA-AVHRR) data. Cloud classification is performed for both day and night overpasses by applying several threshold tests which also include ancillary terrain information. From a set of 155 images, maps of relative cloud frequency are calculated for Ecuador and adjacent areas as well as the central study area of an ecological project in southern Ecuador (Loja). Results show a clear relation between topography, main airflow and cloudiness due to barrage and lee-effects. The spatial extension of high mountain ecosystems such as the Ecuadorian Pa´ramo has been proven to be significantly influenced by the spatial pattern of cloud frequency.