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Automated identification of potential snow avalanche release areas based on digital elevation models

机译：基于数字高程模型自动识别潜在的雪崩释放区域

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The identification of snow avalanche release areas is a very difficult task. The release mechanism of snow avalanches depends on many different terrain, meteorological, snowpack and triggering parameters and their interactions, which are very difficult to assess. In many alpine regions such as the Indian Himalaya, nearly no information on avalanche release areas exists mainly due to the very rough and poorly accessible terrain, the vast size of the region and the lack of avalanche records. However avalanche release information is urgently required for numerical simulation of avalanche events to plan mitigation measures, for hazard mapping and to secure important roads. The Rohtang tunnel access road near Manali, Himachal Pradesh, India, is such an example. By far the most reliable way to identify avalanche release areas is using historic avalanche records and field investigations accomplished by avalanche experts in the formation zones. But both methods are not feasible for this area due to the rough terrain, its vast extent and lack of time. Therefore, we develop an operational, easy-to-use automated potential release area (PRA) detection tool in Python/ArcGIS which uses high spatial resolution digital elevation models (DEMs) and forest cover information derived from airborne remote sensing instruments as input. Such instruments can acquire spatially continuous data even over inaccessible terrain and cover large areas. We validate our tool using a database of historic avalanches acquired over 56 yr in the neighborhood of Davos, Switzerland, and apply this method for the avalanche tracks along the Rohtang tunnel access road. This tool, used by avalanche experts, delivers valuable input to identify focus areas for more-detailed investigations on avalanche release areas in remote regions such as the Indian Himalaya and is a precondition for large-scale avalanche hazard mapping.
机译：确定雪崩释放区域是一项非常艰巨的任务。雪崩的释放机制取决于许多不同的地形，气象，积雪和触发参数及其相互作用，这是很难评估的。在许多高寒地区，例如印度喜马拉雅山，几乎没有关于雪崩释放区域的信息，这主要是由于地形非常崎and，交通不便，该地区面积巨大以及缺乏雪崩记录所致。但是，雪崩释放信息对于雪崩事件的数值模拟是迫切需要的，以计划缓解措施，进行危害测绘和保护重要道路。例如，印度喜马al尔邦马纳里附近的Rohtang隧道通道。到目前为止，识别雪崩释放区域的最可靠方法是使用历史雪崩记录和由编队中的雪崩专家完成的野外调查。但是由于地形崎,、范围广且缺乏时间，这两种方法都不适合该地区。因此，我们在Python / ArcGIS中开发了一种易于使用的操作性自动潜在释放区域（PRA）检测工具，该工具使用了高空间分辨率数字高程模型（DEM）和来自机载遥感仪器的森林覆盖信息作为输入。这样的仪器甚至可以在难以接近的地形上获取空间连续的数据，并覆盖大面积。我们使用瑞士达沃斯附近地区超过56年的历史雪崩数据库对我们的工具进行了验证，并将此方法应用于Rohtang隧道出入口道路上的雪崩轨道。雪崩专家使用的该工具提供了宝贵的信息，可用于确定重点区域，以便对诸如印度喜马拉雅山等偏远地区的雪崩释放区域进行更详细的调查，这是进行大规模雪崩灾害映射的前提。

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