来自LiDAR的森林库存数据用于绘制和量化跨大空间范围的生态重要大树
Douglas G Pitt1, Lisa A Venier2, Greg W Adams3
1DeltaForest Ltd., Goulais River, Ontario, Canada.
概括
我们开发了一种使用LiDAR数据绘制和计数森林中大老树的新方法. 这种方法有助于量化树木分布,以维护大面积的景观中的生物多样性.
科学领域:
- 森林生态 森林生态
- 遥感 遥感 遥感 遥感
- 生物多样性保护 生物多样性保护
背景情况:
- 大型老树对森林生物多样性至关重要.
- 它们的下降日益令人担忧,需要有效的库存方法.
- 现有的大树量化方法通常在范围或灵活性上是有限的.
研究的目的:
- 开发和介绍使用空中LiDAR数据绘制和量化大型树木的方法.
- 创建一个灵活和高效的解决方案,集成在R统计软件中.
- 解决对生态重要大型树木进行大规模库存的需求.
主要方法:
- 利用空中LiDAR数据和天花板高度模型进行映射.
- 开发了一个基于R的算法,集成现有包.
- 使用本地高度和冠状直径数据进行校准树木计数.
- 从库存图片中定义的高度-dbh曲线,以使用高度作为dbh值的替代品.
主要成果:
- 成功地绘制和量化了加拿大新不伦瑞克1.65万公的大型树木分布.
- 据估计,在研究区域内广泛分布着超过3700万棵大树.
- 根据省级林业管理指南提出了空间地图和频率统计.
结论:
- 开发的方法有效地绘制和量化大型树木分布在广泛的森林地区.
- 这种方法作为评估景观层面维持生物多样性的指标.
- 该方法可适应各种森林特定的大树定义,以高度或dbh.bh.为基础.
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