RAPID: Airborne LiDAR and Hyperspectral Observations to Support Ecological Characterization of Wildfire Affected Areas in Partnership with BB-FLUX

RAPID：与 BB-FLUX 合作利用机载激光雷达和高光谱观测支持野火受影响地区的生态特征描述

• 批准号: 1842139
• 负责人: Tristan Goulden
• 金额: $ 18.35万
• 依托单位: Battelle Memorial Institute
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-15 至 2020-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1842139&HistoricalAwards=false
• 关键词: RAPID; Airborne; LiDAR; Hyperspectral; Observations

This project will assess the above ground biomass burned during specific wildfires in the Western US during the 2018 fire season. This effort is in support of another NSF-supported project, BB-FLUX (Biomass Burning Flux Measurements of Trace Gases and Aerosols), that is focused on measuring wildfire emission fluxes. Sensors will be flown on the Airborne Observation Platform (AOP) of the National Ecological Observatory (NEON) to quantify the area and above ground biomass burned during wildfires. The project results will help improve understanding of the risk to human and ecosystem health associated with emissions from wildfires. The objectives of this effort are to: (1) Collect post-wildfire burn data with the NEON AOP to support research on wildfire emission and ecosystem relationships; (2) Process the collected NEON AOP data through to the standard set of NEON data products that will provide the basis for estimating the area burned and total fuel burned; and (3) Enhance above ground biomass (AGB) estimation algorithms through fusion of downward-looking laser altimetry (LiDAR) and optical hyperspectral (HS) airborne measurements, using existing publically available NEON data that closely matches the ecosystems captured (northern temperate forests), providing BB-FLUX emission models with high accuracy estimates of AGB (fuel burned). Existing NEON collections in northern temperate forests will be used as candidate sites to develop an enhanced algorithm for predicting biomass using fusion approaches between LiDAR and HS observations.The partnership of the NEON AOP and the BB-FLUX campaign represents a novel synergy between previously disparate observation systems that introduces an inter-disciplinary approach for relating wildfire emission characteristics to the local ecosystems. The general advancement of improved AGB estimates have broad implications for ecological sciences, forestry, agriculture and environmental management.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该项目将评估在2018年火灾季节美国西部特定野火期间燃烧的上述生物质。 这项工作是为了支持另一个NSF支持的项目BB-Flux（痕量气体和气溶胶的生物量燃烧通量测量），该项目的重点是测量野火发射通量。 传感器将在国家生态观测站（NEON）的机载观测平台（AOP）上飞行，以量化野火期间燃烧的面积及以上的地面生物量。该项目的结果将有助于提高对与野火排放相关的人类和生态系统健康风险的理解。 这项工作的目标是：（1）用霓虹灯收集野火后燃烧数据，以支持对野火发射和生态系统关系的研究； （2）处理收集的霓虹灯数据贯穿到标准的霓虹灯数据产品集，这些数据将为估计燃烧的面积和燃烧的总燃料提供基础； （3）通过融合向下的激光高度测定（LIDAR）和光学高光谱（HS）空气降低测量值，通过融合向下的激光高度测定（LIDAR）和使用现有的公共可用的霓虹灯数据，使用与生态系统相匹配（Northern forsemate formister（Northern forse）的BB BRINGISE BROFTEC ACRISS ACRISCACE（AGB），增强了燃料（Northern versemate formife bermistic conterby Bornef Bunder Borge unux），从而增强了高于地面生物量（AGB）的估计算法。北部温带森林中现有的霓虹灯收集将被用作候选场所，以使用LiDar和HS观测之间的融合方法来开发一种增强的算法来预测生物量。NEON AOP和BB-FLUX运动的合作伙伴关系代表了先前分散的观察系统之间的新型协同性，以引入与本地阶段性的相互作用相关性的相关性，以介绍一项相互构想的相关性。 改进的AGB估计值的总体进步对生态科学，林业，农业和环境管理具有广泛的影响。该奖项反映了NSF的法定任务，并被认为是通过基金会的知识分子优点和更广泛影响的评估标准来评估值得支持的。

项目成果

A Comparison of Multitemporal Airborne Laser Scanning Data and the Fuel Characteristics Classification System for Estimating Fuel Load and Consumption

多时相机载激光扫描数据与用于估算燃油负荷和消耗的燃油特性分类系统的比较

• DOI: 10.1029/2021jg006733
• 发表时间: 2022
• 期刊: Journal of Geophysical Research: Biogeosciences
• 作者: McCarley, T. Ryan;Hudak, Andrew T.;Restaino, Joseph C.;Billmire, Michael;French, Nancy H. F.;Ottmar, Roger D.;Hass, Bridget;Zarzana, Kyle;Goulden, Tristan;Volkamer, Rainer
• 通讯作者: Volkamer, Rainer