RAPID: Acquisition of high resolution LiDAR for Barro Colorado Nature Monument, Panama

RAPID：为巴拿马巴罗科罗拉多自然纪念碑采购高分辨率激光雷达

• 批准号: 0939907
• 负责人: James Dalling
• 金额: $ 6.2万
• 依托单位: University of Illinois at Urbana-Champaign
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-06-15 至 2010-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0939907&HistoricalAwards=false
• 关键词: RAPID; Acquisition; resolution; LiDAR; Barro

Light Detection and Ranging (LiDAR) is an effective, rapid, remote-sensing technology for describing the structure of forest canopies, height of individual trees, and the size and location of forest disturbances. These data can also provide estimates of standing carbon stocks of entire forests at landscape scales. When used in conjunction with LiDAR, hyperspectral imagery, which measures the wavelength of light reflected from a canopy, can provide identification of individual forest species. At present, the cost of deploying LiDAR and hyperspectral imagery has limited its application mostly to temperate forests. A time-limited opportunity has arisen to acquire this imagery at a greatly reduced cost for Barro Colorado Nature Monument (BCNM), Panama, one of the best-studied tropical forests in the world.LiDAR and hyperspectral imagery provide an exceptionally powerful tool for integrating data on the structure and biodiversity of tropical forests. These data will provide a valuable resource for diverse projects conducted at BCNM, and will stimulate new research aimed at translating existing ground-based research up to landscape scales relevant to forest management and conservation. The wealth of existing data at BCNM allow for a rigorous evaluation of LiDAR's potential to provide large-scale forest carbon estimates, which will play a key role in implementation of proposed carbon dioxide (CO2) emission control through Reduced Emissions from Deforestation and Degradation. Data will be maintained by Smithsonian's Environmental Science Program and made available online and as an Ecological Archives publication one year after acquisition. These data will contribute to the training and research of students at numerous collaborating institutions.

光检测和范围（LIDAR）是一种有效，快速，遥远的技术，用于描述森林檐篷的结构，单个树木的高度以及森林干扰的大小和位置。这些数据还可以提供景观量表整个森林的常驻碳库存的估计。当与LIDAR结合使用时，高光谱图像测量了冠层反射的光的波长，可以提供单个森林物种的识别。目前，部署LiDAR和高光谱图像的成本主要限制了其在温带森林中的应用。出现了一个时间限制的机会，以大大降低了Barro Colorado Nature Monument（BCNM）的成本，巴拿马是世界上研究最佳的热带森林之一。Lidarand Hyperspectral Imagery为在热带森林的结构和生物多样性中融合了数据的异常强大的工具。这些数据将为BCNM进行的不同项目提供宝贵的资源，并将刺激旨在将现有基于地面研究的新研究转化为与森林管理和保护有关的景观量表。 BCNM上现有的大量数据允许对Lidar提供大规模森林碳估计的潜力进行严格的评估，这将在实施拟议的二氧化碳（CO2）排放控制方面发挥关键作用，通过减少侵犯和退化的排放。数据将由Smithsonian的环境科学计划维护，并在网上提供，作为收购后一年的生态档案出版物。这些数据将有助于众多合作机构的学生的培训和研究。