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Automated analysis and classification of landforms using high-resolution digital elevation data: applications and issues

机译:使用高分辨率数字高程数据自动分析和分类地貌:应用和问题

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摘要

This paper describes recent efforts to use fine spatial resolution digital elevation model (DEM) data, including, but not limited to, lidar DEM data, for automated analysis and classification of geomorphic and hydrologic terrain features. The example applications presented are based on a 3-m horizontal resolution lidar DEM for a 6 km by 8 km agricultural watershed in Alberta and on a similar 5-m horizontal resolution conventional DEM for two forested areas of 14 km by 12 km in the Cariboo Forest Region of British Columbia. The applications illustrate efforts to produce meaningful classifications of ecological and landform spatial entities and to automatically extract hydrological spatial entities required for input into the WEPP water erosion model. Fine spatial resolution DEMs present some unique problems for which solutions are still lacking or are insufficient. Errors of apparently minor extent or degree can seriously affect some forms of analysis, especially analyses that involve hydrological calculations of paths of surface water flow. A need is recognized for improved methods and tools for interpolating and editing fine spatial resolution DEMs to remove or reduce localized errors.
机译:本文介绍了最近使用精细空间分辨率数字高程模型(DEM)数据(包括但不限于激光雷达DEM数据)进行地貌和水文地形特征的自动分析和分类的工作。呈现的示例应用程序基于艾伯塔省6 km x 8 km农业流域的3 m水平分辨率激光雷达DEM和Cariboo的14 km x 12 km的两个林区的类似5 m水平分辨率常规DEM。不列颠哥伦比亚省的森林地区。这些应用程序说明了如何对生态和地形空间实体进行有意义的分类以及自动提取输入WEPP水蚀模型所需的水文空间实体的努力。精细的空间分辨率DEM提出了一些独特的问题,而这些问题仍然缺乏或不足。明显较小程度或程度的误差会严重影响某些形式的分析,尤其是涉及涉及地表水流动路径的水文计算的分析。认识到需要用于内插和编辑精细空间分辨率DEM的改进方法和工具,以消除或减少局部误差。

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