StrucNet:一个用于自动化植被结构监测的全球网络
Kim Calders1,2, Benjamin Brede3, Glenn Newnham4
1CAVElab - Computational & Applied Vegetation Ecology, Department of Environment Ghent University Coupure links 653 Ghent 9000 Belgium.
Remote sensing in ecology and conservation
|March 20, 2024
概括
高频地面激光扫描提供了一种用于系统监测植被结构变化的新方法. 这种方法为了解生态系统动态和告知保护工作提供了关键数据.
科学领域:
- 生态生态学 生态生态学
- 遥感 遥感 遥感 遥感
- 林业林业 林业 林业 林业
背景情况:
- 气候变化和人类活动威胁着生态系统和生物多样性.
- 基本生物多样性变量 (EBV) 和气候变量对于监测和政策评估至关重要.
- 生态系统结构是生物多样性评估,息地质量和物种组成分析的关键.
研究的目的:
- 为了证明高频地面激光扫描用于系统的植被结构监测的潜力.
- 使用地面激光扫描 (TLS) 呈现生态系统结构的5年时间序列.
- 引入自动化激光扫描,用于升级植被结构数据.
主要方法:
- 在一个温带森林中,在5年内利用了高时间陆地激光扫描 (TLS).
- 开发了自动化激光扫描技术,以克服机会主义TLS的局限性.
- 在当地尺度上收集了详细的3D植被结构数据.
主要成果:
- 建立了一个概念验证的高时间生态系统结构时间序列.
- 证明了自动激光扫描用于持续监控的可行性.
- 突出了太空中测量的局限性,以详细地了解当地植被结构.
结论:
- 高频地面激光扫描对于监测植被结构变化是有效的.
- 自动监控网络对于校准卫星任务至关重要.
- 这种方法支持大规模的植被动态监测和保护战略.
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