The reproducibility of remotely piloted aircraft systems to monitor seasonal variation in submerged seagrass and estuarine habitats

IF 2.9 3区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES Facets Pub Date : 2023-01-01 DOI:10.1139/facets-2022-0149
T. Prystay, G. Adams, B. Favaro, R. Gregory, A. Le Bris
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引用次数: 1

Abstract

Seasonal variation in seagrass growth and senescence affects the provision of ecosystem services and restoration efforts, requiring seasonal monitoring. Remotely piloted aircraft systems (RPAS) enable frequent high-resolution surveys at full-meadow scales. However, the reproducibility of RPAS surveys is challenged by varying environmental conditions, which are common in temperate estuarine systems. We surveyed three eelgrass ( Zostera marina) meadows in Newfoundland, Canada, using an RPAS equipped with a three-color band (red, green, blue [RGB]) camera, to evaluate the seasonal reproducibility of RPAS surveys and assess the effects of flight altitude (30–115 m) on classification accuracy. Habitat percent cover was estimated using supervised image classification and compared to corresponding estimates from snorkel quadrat surveys. Our results revealed inconsistent misclassification due to environmental variability and low spectral separability between habitats. This rendered differentiating between model misclassification versus actual changes in seagrass cover infeasible. Conflicting estimates in seagrass and macroalgae percent cover compared to snorkel estimates could not be corrected by decreasing the RPAS altitude. Instead, higher altitude surveys may be worth the trade-off of lower image resolution to avoid environmental conditions shifting mid-survey. We conclude that RPAS surveys using RGB imagery alone may be insufficient to discriminate seasonal changes in estuarine subtidal vegetated habitats.
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遥控飞机系统监测水下海草和河口生境季节变化的可重复性
海草生长和衰老的季节性变化影响生态系统服务的提供和恢复工作,需要进行季节性监测。遥控飞机系统(RPAS)能够在全草地尺度上进行频繁的高分辨率调查。然而,RPAS调查的再现性受到不同环境条件的挑战,这在温带河口系统中很常见。我们使用配备有三个色带(红、绿、蓝[RGB])相机的RPAS调查了加拿大纽芬兰的三个鳗草(Zostera marina)草地,以评估RPAS调查的季节再现性,并评估飞行高度(30–115米)对分类精度的影响。使用监督图像分类估计栖息地覆盖率,并与浮潜象限调查的相应估计值进行比较。我们的结果显示,由于环境变异性和栖息地之间的低光谱可分性,错误分类不一致。这使得区分模型错误分类与海草覆盖率实际变化是不可行的。与浮潜估计相比,海草和大型藻类覆盖率的估计存在冲突,无法通过降低RPAS海拔来纠正。相反,更高的海拔调查可能值得在较低的图像分辨率之间进行权衡,以避免环境条件在调查中期发生变化。我们的结论是,仅使用RGB图像的RPAS调查可能不足以区分河口潮下植被栖息地的季节变化。
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来源期刊
Facets
Facets MULTIDISCIPLINARY SCIENCES-
CiteScore
5.40
自引率
6.50%
发文量
48
审稿时长
28 weeks
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