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Multi-Temporal UAV Data and Object-Based Image Analysis (OBIA) for Estimation of Substrate Changes in a Post-Bleaching Scenario on a Maldivian Reef

机译:用于绘制Maldivivian Reef的漂白场景中基板的多时间UAV数据和基于对象的图像分析(OBIA)

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摘要

Coral reefs are declining worldwide as a result of the effects of multiple natural and anthropogenic stressors, including regional-scale temperature-induced coral bleaching. Such events have caused significant coral mortality, leading to an evident structural collapse of reefs and shifts in associated benthic communities. In this scenario, reasonable mapping techniques and best practices are critical to improving data collection to describe spatial and temporal patterns of coral reefs after a significant bleaching impact. Our study employed the potential of a consumer-grade drone, coupled with structure from motion and object-based image analysis to investigate for the first time a tool to monitor changes in substrate composition and the associated deterioration in reef environments in a Maldivian shallow-water coral reef. Three key substrate types (hard coral, coral rubble and sand) were detected with high accuracy on high-resolution orthomosaics collected from four sub-areas. Multi-temporal acquisition of UAV data allowed us to compare the classified maps over time (February 2017, November 2018) and obtain evidence of the relevant deterioration in structural complexity of flat reef environments that occurred after the 2016 mass bleaching event. We believe that our proposed methodology offers a cost-effective procedure that is well suited to generate maps for the long-term monitoring of changes in substrate type and reef complexity in shallow water.
机译:由于多种天然和人为压力源的影响,包括区域规模温度诱导的珊瑚漂白,珊瑚礁正在全世界下降。此类事件导致了大量的珊瑚死亡率,导致珊瑚礁的明显结构崩溃和相关的终身社区中的转变。在这种情况下,合理的映射技术和最佳实践对于改善数据收集至关重要,以描述在显着的漂白撞击后描述珊瑚礁的空间和时间模式。我们的研究采用了消费级无人机的潜力,与来自运动和基于物体的图像分析的结构相结合,以调查Matrivivian浅水中的衬底成分的变化和珊瑚礁环境中的相关劣化的工具。珊瑚礁。以高精度从四个子区域收集的高分辨率正轨的高精度检测到三种键衬底类型(硬珊瑚,珊瑚碎石和沙子)。多时间收购UAV数据允许我们将分类的地图相比(2017年11月,2018年11月),并获得2016年大规模漂白事件后发生的扁平礁环境结构复杂性的相关恶化。我们认为,我们的提议方法提供了一种成本效益的程序,非常适合为浅水中的底物类型和珊瑚礁复杂性的长期监测产生地图。

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