Demography with drones: detecting growth and survival of shrubs with unoccupied aerial systems
Demography with drones: detecting growth and survival of shrubs with unoccupied aerial systems
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DOI：
10.1111/rec.14106
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发表时间：
2024-01-25
影响因子：
3.2
通讯作者：
Caughlin，T. Trevor
中科院分区：
文献类型：
--
作者：
Olsoy，Peter J.;Zaiats，Andrii;Caughlin，T. Trevor
大规模的骚乱，例如特大火灾，也会在很大程度上促进恢复。测量单个植物的存活和生长在当前监测恢复成功的努力中发挥着关键作用。然而，现代恢复的规模（例如，>10,000 公顷）对利用实地数据测量人口比率提出了挑战。在这项研究中，我们展示了无人航空系统（UAS）飞行如何为从空中检测人口统计率时的精度和空间范围之间的权衡提供有效的解决方案。我们在两个山艾树（Artemisia tridentata）公共花园连续进行了两次无人机飞行，以测量单个植物的存活和生长情况。对单个灌木冠层进行贝叶斯优化分割的准确性很高（73-95%，取决于年份和地点），遥感生存估计与地面真实生存普查的误差在 10% 以内。林龄结构影响遥感生长估计；在第一个拥有较老林分的花园中，相对于基于实地的估计，生长被高估了 57%，但在第二个拥有较年轻林分的花园中，一致性很高。此外，具有较短、较小植物的较年轻林分（类似于刚刚受到干扰后的林分）有时会与其他灌木物种和丛生草混淆，这表明需要整合光谱分类方法，这些方法越来越多地可在负担得起的无人机平台上使用。较旧的看台有几个合并的树冠，这导致了对丰度的低估，但并没有影响遥感的生存估计。运动摄影测量在分割和无人机系统结构方面的进步将使人口统计率测量能够在管理相关范围内实现。
Large‐scale disturbances, such as megafires, motivate restoration at equally large extents. Measuring the survival and growth of individual plants plays a key role in current efforts to monitor restoration success. However, the scale of modern restoration (e.g., >10,000 ha) challenges measurements of demographic rates with field data. In this study, we demonstrate how unoccupied aerial system (UAS) flights can provide an efficient solution to the tradeoff of precision and spatial extent in detecting demographic rates from the air. We flew two, sequential UAS flights at two sagebrush (Artemisia tridentata) common gardens to measure the survival and growth of individual plants. The accuracy of Bayesian‐optimized segmentation of individual shrub canopies was high (73–95%, depending on the year and site), and remotely sensed survival estimates were within 10% of ground‐truthed survival censuses. Stand age structure affected remotely sensed estimates of growth; growth was overestimated relative to field‐based estimates by 57% in the first garden with older stands, but agreement was high in the second garden with younger stands. Further, younger stands (similar to those just after disturbance) with shorter, smaller plants were sometimes confused with other shrub species and bunchgrasses, demonstrating a need for integrating spectral classification approaches that are increasingly available on affordable UAS platforms. The older stand had several merged canopies, which led to an underestimation of abundance but did not bias remotely sensed survival estimates. Advances in segmentation and UAS structure from motion photogrammetry will enable demographic rate measurements at management‐relevant extents.