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简化基于无人机的地上碳密度测量以支持社区林业。

Simplifying drone-based aboveground carbon density measurements to support community forestry.

作者信息

Newport Ben, Hales Tristram C, House Joanna, Goossens Benoit, Jumail Amaziasizamoria

机构信息

School of Geographical Sciences, University of Bristol, Bristol, United Kingdom.

School of Earth and Environmental Sciences, Cardiff University, Cardiff, United Kingdom.

出版信息

PLoS One. 2025 Apr 29;20(4):e0322099. doi: 10.1371/journal.pone.0322099. eCollection 2025.

Abstract

Community-based forest restoration has the potential to sequester large amounts of atmospheric carbon, avoid forest degradation, and support sustainable development. However, if partnered with international funders, such projects often require robust and transparent aboveground carbon measurements to secure payments, and current monitoring approaches are not necessarily appropriate due to costs, scale, and complexity. The use of consumer-grade drones in combination with open source structure-from-motion photogrammetry may provide a solution. In this study, we tested the suitability of a simplified drone-based method for measuring aboveground carbon density in heavily degraded tropical forests at a 2 ha restoration site in Sabah, Malaysia, comparing our results against established field-based methods. We used structure-from-motion photogrammetry to generate canopy height models from drone imagery, and applied multiple pre-published plot-aggregate allometric equations to examine the importance of utilising regionally calibrated allometric equations. Our results suggest that this simplified method can produce aboveground carbon density measurements of a similar magnitude to field-based methods, quickly and only with a single input metric. However, there are greater levels of uncertainty in carbon density measurements due to errors associated with canopy height measurements from drones. Our findings also highlight the importance of selecting regionally calibrated allometric equations for this approach. At scales between 1 and 100 ha, drone-based methods provide an appealing option for data acquisition and carbon measurement, balancing trade-offs between accuracy, simplicity, and cost effectiveness and coinciding well with the needs of community-scale aboveground carbon measurement. Of importance, we also discuss considerations relating to the accessibility of this method for community use, beyond purchasing a drone, that must not be overlooked. Nevertheless, the method presented here lays the foundations for a simple workflow for measuring aboveground carbon density at a community scale that can be refined in future studies.

摘要

基于社区的森林恢复有潜力封存大量大气碳、避免森林退化并支持可持续发展。然而,如果与国际资助者合作,此类项目通常需要进行稳健且透明的地上碳测量以确保获得资金,而由于成本、规模和复杂性,当前的监测方法不一定适用。使用消费级无人机结合开源的运动结构摄影测量法可能提供一种解决方案。在本研究中,我们在马来西亚沙巴州一个2公顷的恢复场地测试了一种简化的基于无人机的方法在严重退化的热带森林中测量地上碳密度的适用性,并将我们的结果与既定的实地测量方法进行比较。我们使用运动结构摄影测量法从无人机图像生成树冠高度模型,并应用多个预先发表的样地汇总异速生长方程来检验使用区域校准异速生长方程的重要性。我们的结果表明,这种简化方法能够快速且仅通过单一输入指标得出与实地测量方法量级相似的地上碳密度测量结果。然而,由于与无人机树冠高度测量相关的误差,碳密度测量存在更大程度的不确定性。我们的研究结果还突出了为这种方法选择区域校准异速生长方程的重要性。在1至100公顷的规模范围内,基于无人机的方法为数据采集和碳测量提供了一个有吸引力的选择,平衡了准确性、简单性和成本效益之间的权衡,并且与社区规模地上碳测量的需求非常契合。重要的是,我们还讨论了除购买无人机之外,该方法在社区使用方面的可及性相关考虑因素,这些因素不容忽视。尽管如此,本文提出的方法为社区规模测量地上碳密度的简单工作流程奠定了基础,未来的研究可以对其进行完善。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7341/12040082/fcfe63f38f29/pone.0322099.g001.jpg

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