RAPID: Collecting Field Data in Support of LiDAR Acquisition During Maximum Snow Conditions and Maximum Leaf Out in the Boulder Creek Critical Zone Observatory

RAPID：在 Boulder Creek 关键区域观测站的最大雪况和最大落叶情况下收集现场数据以支持 LiDAR 采集

• 批准号: 1036598
• 负责人: Suzanne Anderson
• 金额: $ 3.32万
• 依托单位: University of Colorado at Boulder
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-06-15 至 2011-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1036598&HistoricalAwards=false
• 关键词: RAPID; Collecting; Field; Data; Support

This project will provide measurements of snow depth and vegetation characteristics of Boulder Creek watershed in Colorado that will be used to calibrate and validate airborne LiDAR (Light Detection And Ranging) data acquisition for the Critical Zone Observatories that will take place in May and August. The research team will measure snow conditions on the ground at the time of the LiDAR data acquisition in April-May, since snow conditions change rapidly. In addition, the team will collect control point data so that the two LiDAR flights can be carefully georeferenced, reducing errors in snow pack due to location errors. The team will also measure vegetation characteristics for the full leaf-on flights in late August-early September. The measurements made during the "bare-ground" season will also be used to calculate the snow depths that existed across the watershed during the earlier LiDAR flight.LiDAR is a powerful tool that provides detailed information concerning topography and landform characteristics at high resolution. Having such data available is crucial to the mission of the Critical Zone Observatories, which are exploring the processes in the region of the Earth's surface that important to sustaining life. This project will enable the LiDAR data to be used with extreme accuracy so that processes within the Boulder Creek watershed can be analyzed more effectively. The effort will help train a graduate student in spatial data acquisition, and several undergraduate students in the details of LiDAR processing and surveying.

该项目将提供科罗拉多的博尔德溪流域的积雪深度和植被特征的测量结果，这些测量结果将用于校准和验证将于5月和8月进行的临界区观测站的机载LiDAR（光探测和测距）数据采集。 研究小组将在4月至5月的LiDAR数据采集时测量地面上的雪况，因为雪况变化很快。此外，该团队将收集控制点数据，以便两次LiDAR飞行可以仔细地进行地理参考，减少由于位置错误而导致的积雪误差。研究小组还将在8月底至9月初测量全叶飞行的植被特征。在“裸地”季节所作的测量，亦会用来计算较早时激光雷达飞行时横跨分水岭的积雪深度。激光雷达是一个强大的工具，可以提供高分辨率的地形和地貌特征的详细资料。掌握这类数据对于临界区观测站的使命至关重要，这些观测站正在探索地球表面区域对维持生命至关重要的过程。该项目将使激光雷达数据能够以极高的精度使用，以便更有效地分析博尔德溪流域内的过程。 这项工作将有助于培训一名研究生进行空间数据采集，并培训几名本科生进行LiDAR处理和测量的细节。