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Light detection and ranging (LiDAR) for sustainable community forest management

Light detection and ranging (LiDAR) for sustainable community forest management
用于可持续社区森林管理的光探测和测距 (LiDAR)
批准号:
471058-2014
负责人:
Coops, Nicholas
金额:
$1.43万
依托单位国家:
加拿大
项目类别:
Collaborative Research and Development Grants
财政年份:
2016
资助国家:
加拿大
项目状态:
已结题
起止时间:
2016-01-01 至 2017-12-31

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中文摘要
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英文摘要
In many areas on the coast of British Columbia (BC), sustainable forest management is becoming a major focus to ensure the maintenance of forest ecosystem function (Natural Resource Canada 2007). Traditionally, aerial photography, digital elevation models (DEMs), and ground based surveys are used as tools in forest management. However, Light Detection And Ranging (LiDAR), also known as airborne laser scanning (ALS), is a recent remote sensing technology that has been shown to be extremely valuable in the development of detailed management plans. ALS technology has the ability to penetrate the vertical profile of a forest canopy so that measurements of forest height, predictions of stand volume and biomass, as well as underlying terrain information can be gathered remotely (Bater et al., 2007; Gatziolis and Andersen, 2008). With both the advancement and increased accessibility of ALS technology it has become an important aspect in the development of forest inventory for forest planning. As a result, many forestry companies, both industrial and community-based, have been increasingly receptive to using ALS to provide accurate assessments of the timber harvesting land base (THLB). ALS technology can augment current forest inventory methods in a number of unique ways, including: providing estimates of attributes usually assessed using traditional inventory (e.g., volume basal area, mean DBH, height and volume; provide estimates of additional and more advanced inventory attributes (e.g., stem distribution and piece size; and estimating additional forest ecosystem services (e.g., terrain, watershed and stream features, viewsheds, and carbon assessment.
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Remote Sensing of Forest Carbon Accumulation
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