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Linking traditional forest inventory data with airborne laser scanning (ALS) measurements******

Linking traditional forest inventory data with airborne laser scanning (ALS) measurements******
将传统森林清查数据与机载激光扫描 (ALS) 测量联系起来******
批准号:
537504-2018
负责人:
Achim, Alexis
金额:
$1.82万
依托单位:
依托单位国家:
加拿大
项目类别:
Engage Grants Program
财政年份:
2018
资助国家:
加拿大
项目状态:
已结题
起止时间:
2018-01-01 至 2019-12-31

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中文摘要
翻译
Domtar在魁北克南部拥有一块面积超过16万公顷的大片森林。总共建立了2250多个永久样地(PSPs)并定期测量,目的是监测(并不断改进)应用于该森林庄园的造林系统的效果。作为魁北克省森林、野生动物和公园部开展的全省调查活动的一部分,Domtar最近获得了覆盖整个森林产业的机载激光扫描(ALS)数据。这项“参与资助”的目的是制定一项科学合理、最先进的战略,以尽可能充分利用他们的ALS数据。工作将按以下顺序进行:生成选定的als衍生的森林庄园“墙到墙”指标;2. 审查当前的现场规划和测量,并评估其对ALS衍生模型的效用;3. 采用结构导向的抽样方法,以评估目前地面地块网络的代表性;4. 为Domtar提供一个技术转移研讨会,员工将在研讨会上展示如何使用r中的免费和开源lidR包。这将帮助员工不仅对如何有效使用ALS数据有一个大致的了解,而且还能提高他们使用和分析可用ALS数据的能力。
英文摘要
Domtar is the owner of a vast forest estate totalling over 160,000 ha in southern Quebec. In total, more than 2,250 permanent sample plots (PSPs) have been established and measured periodically with the objective to monitor the effects of (and continuously improve) the silvicultural systems applied to this forest estate. As part of a province-wide surveying campaign conducted by Quebec's Ministry of Forests, Wildlife and Parks, Domtar have recently gained access to Airborne Laser Scanning (ALS) data covering their entire forest estate. The aim of this Engage Grant will be to develop a scientifically sound, state of the art, strategy to make the best possible use of their ALS data. The work will be conducted in the following sequence: 1. Generation of selected ALS-derived "wall-to-wall" metrics over the forest estate; 2. Review current field plot program and measurements and assess their utility for ALS derived models; 3. Undertake a structurally guided sampling approach to assess the representiveness of the current network of ground plots; 4. Present a tech transfer workshop for Domtar in which staff will be shown how to use the free and open-source lidR package in R. This will help employees develop not only a general understanding of how ALS data can be used effectively, but also their ability to use and analyze the available ALS data.
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