Penguins play an essential biochemical role in the Antarctic ecosystem, being the study of their dynamics of utmost importance to understand their environment, behaviour and populational trends in the current climate change scenario. In this study, we used multi-rotor Unmanned Aerial Vehicles (UAVs) along the coast of the chinstrap penguin () colony of Vapour Col (Deception Island, Antarctica) to map potential sites of biochemical interactions with the surrounding sea water. Several runoff discharge points were identified, where a precise placing of environmental sampling station is suggested. Additionally, UAVs were used in combination with Object Detection Architectures to obtain the chinstrap colony population size. Applying a simulation for clutch initiation dates due to our off-laying peak count, we obtained an estimated range of 13,250 to 22,000 breeding pairs in the 2021/2022 breeding season, also suggesting an alternative approach using chinstrap chicks as proxy to estimate adult numbers. This research shows the utility of UAV-deep learning for environment characterization and wildlife monitoring, providing a solid framework for upcoming studies in the area.

中文翻译：

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通过基于无人机的深度学习模型评估南极企鹅群的地形特征和种群丰度


企鹅在南极生态系统中发挥着重要的生化作用，研究它们的动态对于了解它们在当前气候变化情景下的环境、行为和种群趋势至关重要。在这项研究中，我们使用多旋翼无人机 (UAV) 沿 Vapor Col（南极洲迪塞普申岛）的帽带企鹅群落海岸绘制了与周围海水发生生化相互作用的潜在地点的地图。确定了几个径流排放点，建议精确放置环境采样站。此外，无人机与目标检测架构相结合，以获得下颏带群体的规模。根据我们的产蛋高峰数量对产蛋开始日期进行模拟，我们获得了 2021/2022 年繁殖季节 13,250 至 22,000 对繁殖对的估计范围，这也提出了使用下颌带雏鸡作为估计成年数量的替代方法。这项研究展示了无人机深度学习在环境表征和野生动物监测方面的实用性，为该领域即将进行的研究提供了坚实的框架。