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Determination of optimal point spacing for reliable RPAS-mounted LiDAR inventory of regenerating forest stands in Saskatchewan

Determination of optimal point spacing for reliable RPAS-mounted LiDAR inventory of regenerating forest stands in Saskatchewan
确定萨斯喀彻温省再生林的可靠 RPAS 安装 LiDAR 清单的最佳点间距
批准号:
555474-2020
负责人:
Blum, Susan
金额:
$1.82万
依托单位:
依托单位国家:
加拿大
项目类别:
Applied Research and Development Grants - Level 1
财政年份:
2020
资助国家:
加拿大
项目状态:
已结题
起止时间:
2020-01-01 至 2021-12-31

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中文摘要
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英文摘要
The boreal forest makes up 11.7 million hectares of land in Saskatchewan, of which 5.3 million hectares is considered productive forest accounting for over $1 billion in commodity sales annually. Saskatchewan manages this industry through environmentally-sound industry standards that target long-term sustainability of the boreal forest ecosystem. Technology is an integral component of this management system. In this regard, light detection and ranging (LiDAR) scanners are a notable innovation that permits foresters to document, measure, and identify key attributes of the forest from an aerial platform faster and with better accuracy than ground-based alternatives. LiDAR data is still relatively expensive for large tracts of forested land; specialized data-processing systems are required to evaluate forest performance indicators (i.e. height, volume, species). Forsite Consultants Ltd. (Forsite) is looking to optimize regeneration (regen) surveys for stands in the 'free to grow' stage (8-14 years). Forsite therefore approached Saskatchewan Polytechnic with a research proposal aimed at determining optimal point spacing for regenerating trees using remotely piloted aircraft system (RPAS) mounted LiDAR. The objective of this research is to employ a series of trials at varying point densities over previously measured forest stands. The research would permit determination of optimal point spacing for reliable forest inventory information with respect to regenerating stands. This in turn would facilitate recalibration of existing models and more efficient forest management.
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