Delineating the mountain cloud forest of Taiwan by means of topographic cloud immersion with moderate resolution satellite data and ground based observations

利用中等分辨率卫星数据和地面观测的地形云浸描绘台湾山地云林

• 批准号: 202216100
• 负责人: Dr. Boris Thies
• 金额: --
• 依托单位: Department of Natural Resources and Environmental Studies
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2012
• 资助国家: 德国
• 起止时间: 2011-12-31 至 2015-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/202216100?language=en
• 关键词: Delineating; mountain; cloud; forest; Taiwan

Mountain cloud forests (MCF), which directly depend on frequent cloud immersion, are very important habitats with regard to biodiversity and ecosystem services as e.g. water supply. At the same time, they are especially threatened by Global Change. This also holds for Taiwan where to date, almost no information on the spatial distribution of MCF is available. This (also global) lack of information is mainly due to missing spatio-temporal data on mountain cloud immersion. Based on the recommendations of the UNEP cloud forest agenda, the current project aims on developing a methodology to delineate cloud immersion and cloud forest of Taiwan in high spatial resolution. This will be conducted by combining satellite data exploitation based on different sensors (German counterpart) with on-site observations of cloud geometrical, optical and microphysical properties as well as transect surveys (Taiwanese counterpart). The result will be maps of the potential and current extension of MCF in Taiwan.

山地云雾林（MCF）直接依赖于频繁的云浸没，是生物多样性和生态系统服务（如供水）的重要栖息地。与此同时，它们尤其受到全球变化的威胁。这也适用于台湾，到目前为止，几乎没有关于MCF空间分布的信息。这种（也是全球性的）信息缺乏主要是由于缺少关于山区云浸没的时空数据。本计画根据联合国环境规划署云雾森林议程的建议，致力于发展一套方法，以高空间解析度描绘台湾地区的云雾淹没与云雾森林。这将通过将基于不同传感器的卫星数据利用（德国对应方）与云的几何、光学和微物理特性的现场观测以及样带调查（台湾对应方）相结合来进行。其结果将是地图的潜力和目前的扩展MCF在台湾。

项目成果

Detection of ground fog in mountainous areas from MODIS (Collection 051) daytime data using a statistical approach

使用统计方法从 MODIS（集合 051）白天数据检测山区地面雾

• DOI: 10.5194/amt-9-1135-2016
• 发表时间: 2016
• 期刊: Atmospheric Measurement Techniques
• 影响因子: 3.8
• 作者: Schulz;Bendix
• 通讯作者: Bendix

Frequency of Low Clouds in Taiwan Retrieved from MODIS Data and Its Relation to Cloud Forest Occurrence

MODIS数据反演台湾低云频率及其与云林发生的关系

• DOI: 10.3390/rs71012986
• 发表时间: 2015
• 期刊: Remote. Sens.
• 作者: Schulz;Bendix
• 通讯作者: Bendix

Automatic cloud top height determination in mountainous areas using a cost-effective time-lapse camera system

使用经济高效的延时摄像系统自动确定山区云顶高度

• DOI: 10.5194/amt-7-4185-2014
• 发表时间: 2014
• 期刊: Atmospheric Measurement Techniques
• 影响因子: 3.8
• 作者: Schulz;Bendix
• 通讯作者: Bendix