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Schulz, M.; Li, C.; Thies, B.; Chang, S. &amp; Bendix, J. (2017): <b>Mapping the montane cloud forest of Taiwan using 12 year MODIS-derived ground fog frequency data</b>. <i>PLOS ONE</i> <b>12</b>(2), 1-17.

Resource Description

Title: Mapping the montane cloud forest of Taiwan using 12 year MODIS-derived ground fog frequency data
FOR816dw ID: 288
Publication Date: 2017-02-28
License and Usage Rights: Creative Commons Attribution License
Resource Owner(s):
Individual: Martin Schulz
Contact:
Individual: Ching-Feng Li
Contact:
Individual: Boris Thies
Contact:
Individual: Shih-Chieh Chang
Contact:
Individual: Jörg Bendix
Contact:
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.<br/> <br/>
Keywords:
| Taiwan | cloud forest | ground fog | satellite climatology of fog | fog remote sensing | Mountain forest | vegetation mapping | vegetation plots | fog studies | Random forests | Vegetation cover |
Literature type specific fields:
ARTICLE
Journal: PLOS ONE
Volume: 12
Issue: 2
Page Range: 1-17
Metadata Provider:
Individual: Martin Schulz
Contact:
Online Distribution:
Download File: http://www.lcrs.de/publications.do?citid=288


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