title: Mapping the montane cloud forest of Taiwan using 12 year MODIS-derived ground fog frequency data.
abstract: Up until now montane cloud forest (MCF) in Taiwan has only been mapped for selected areas of vegetation plots. This paper 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 derived from the Moderate Resolution Imaging Spectroradiometer. While the DEM parameters and Landsat data predicted much of the cloud forest's location, local deviations in the altitudinal distribution of MCF linked to the monsoonal influence as well as the Massenerhebung effect (causing MCF in atypically low altitudes) were only captured once fog frequency data was included. Therefore, our study suggests that ground fog data are most useful for accurately mapping MCF.
authors.affiliation: Laboratory for Climatology and Remote Sensing, Philipps-Universität Marburg, Marburg, Germany.
authors.forename: Hans Martin
authors.identifier: http://orcid.org/0000-0001-5249-4960
authors.initials: HM
authors.lastname: Schulz
authors.affiliation: School of Forestry and Resource Conservation, National Taiwan University, Taipei, Taiwan.
authors.forename: Ching-Feng
authors.initials: CF
authors.lastname: Li
authors.affiliation: Laboratory for Climatology and Remote Sensing, Philipps-Universität Marburg, Marburg, Germany.
authors.forename: Boris
authors.initials: B
authors.lastname: Thies
authors.affiliation: Department of Natural Resources and Environmental Studies, National Dong Hwa University, Hualien, Taiwan.
authors.forename: Shih-Chieh
authors.initials: SC
authors.lastname: Chang
authors.affiliation: Laboratory for Climatology and Remote Sensing, Philipps-Universität Marburg, Marburg, Germany.
authors.forename: Jörg
authors.initials: J
authors.lastname: Bendix
mesh_terms: D004784:Environmental Monitoring; D008962:Models, Theoretical; D013624:Taiwan; D014197:Trees