High-Resolution Seagrass Species Mapping and Propeller Scars Detection in Tanjung Benoa, Bali through UAV Imagery

IF 1.3 Q4 ENGINEERING, ENVIRONMENTAL
Wayan Gede, Astawa Karang, Ni Luh, Putu Ratih Pravitha, Wayan Nuarsa, Basheer Ahammed, P. Wicaksono
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Abstract

As a part of the marine ecosystem, seagrass plays a significant role in the coastal environment. However, due to increased threats from natural causes and anthropogenic pressures, seagrass decline will likely begin in many areas of the world. Therefore, several studies have been carried out to observe seagrass distribution to help resolve the issue. Remote sensing is often used due to its ability to achieve high accuracy when distinguishing seagrass dis - tribution. Still, this method lacks in species classification because not all satellites and similar aerial vehicles have fine spatial resolution to distinguish distinct species of seagrass. In this study, we aim to address the issue by utiliz - ing unmanned aerial vehicles (UAV), which are known for providing finer resolution and better imagery. Samuh Beach at Tanjung Benoa, Bali, Indonesia, was chosen as the study site location because it experiences high levels of marine tourism and anthropogenic activities. From the UAV flight mission, the images obtained were processed. The result’s accuracy was also tested with an error matrix. The species found in this study are Enhalus acoroides , Halodule pinifolia , Thalassia hemprichii , Cymodocea rotundata , and Syringodium isoetifolium , with 65% overall accuracy of the species classification map. This result indicates that UAVs can be a strong option for similar studies in the future. In addition to that, this study was able to observe the scars on the seagrass beds left by boat propeller activities from marine tourism. However, further research is needed to gain a better understanding of these objects.
通过无人机图像对巴厘岛丹戎贝诺阿的海草物种进行高分辨率绘图和螺旋桨疤痕检测
作为海洋生态系统的一部分,海草在沿海环境中发挥着重要作用。然而,由于自然原因和人为压力造成的威胁日益严重,世界许多地区的海草很可能开始减少。因此,已经开展了多项研究来观察海草的分布情况,以帮助解决这一问题。由于遥感技术在区分海草分布时能够达到很高的精度,因此经常被使用。不过,这种方法在物种分类方面仍有不足,因为并非所有卫星和类似航空飞行器都具有精细的空间分辨率来区分不同的海草物种。在本研究中,我们旨在利用无人飞行器(UAV)来解决这一问题,众所周知,无人飞行器能提供更精细的分辨率和更好的图像。之所以选择印度尼西亚巴厘岛丹戎贝诺阿的 Samuh 海滩作为研究地点,是因为这里有大量的海洋旅游和人为活动。对无人机飞行任务中获得的图像进行了处理。结果的准确性也通过误差矩阵进行了测试。本研究发现的物种有 Enhalus acoroides 、Halodule pinifolia 、Thalassia hemprichii 、Cymodocea rotundata 和 Syringodium isoetifolium,物种分类图的总体准确率为 65%。这一结果表明,无人机是未来类似研究的有力选择。此外,这项研究还能观察到海洋旅游业的螺旋桨活动给海草床留下的伤痕。不过,要更好地了解这些物体,还需要进一步的研究。
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来源期刊
Journal of Ecological Engineering
Journal of Ecological Engineering ENGINEERING, ENVIRONMENTAL-
CiteScore
2.60
自引率
15.40%
发文量
379
审稿时长
8 weeks
期刊介绍: - Industrial and municipal waste management - Pro-ecological technologies and products - Energy-saving technologies - Environmental landscaping - Environmental monitoring - Climate change in the environment - Sustainable development - Processing and usage of mineral resources - Recovery of valuable materials and fuels - Surface water and groundwater management - Water and wastewater treatment - Smog and air pollution prevention - Protection and reclamation of soils - Reclamation and revitalization of degraded areas - Heavy metals in the environment - Renewable energy technologies - Environmental protection of rural areas - Restoration and protection of urban environment - Prevention of noise in the environment - Environmental life-cycle assessment (LCA) - Simulations and computer modeling for the environment
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