Abstract Conservation management requires reliable and up-to-date data on land use, wildlife population sizes and resource distribution across highly variable ecosystems. Simultaneously, limited funding in conservation often restrict the assessment and interpretation of these datasets. Unmanned aerial systems (UASs) appear as promising and cost-efficient tools to deliver high-quality data, especially when combined with advanced sensor technologies, e.g. based on specific light features such as spectral signature, short-wave infrared (SWIR) reflection and/or polarization. However, their application rates for conservation purposes remain low, partly because of current technology's inaptitude to extrapolate findings onto large spatial scales due to limited flight ranges of the vehicles and difficulties in animal detection and identification. Particularly, using SWIR cameras and polarization filters combined with thermal cameras may improve animal detection, but only few tests have so far investigated the reliability of these technologies. The analysis of large datasets e.g. from hyperspectral cameras requires skills and time, whereas most interest lies in the results of these surveys. Additionally, legal constraints and high initial investment costs confront their application. Overcoming these challenges requires advancing technological robustness of the tool as well as defining the applicability of unmanned aerial vehicles (UAVs) within conservation management. Moreover, its application needs validation in contrast to ground and/or aerial surveys to recommend protocols in different ecological settings and for different management questions. We conclude that UAVs may not serve as panaceas for monitoring land use changes and wildlife trends, but as additional, intermediary data collection tools to support management decisions.

中文翻译：

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自主无人机系统（UAS）在野生动物保护中的应用发展前景

摘要 保护管理需要有关土地利用、野生动物种群规模和高度可变生态系统资源分布的可靠和最新数据。同时，保护方面的有限资金往往会限制对这些数据集的评估和解释。无人机系统 (UAS) 似乎是提供高质量数据的有前途且具有成本效益的工具，尤其是与先进的传感器技术相结合时，例如基于特定的光特征，如光谱特征、短波红外 (SWIR) 反射和/或极化。然而，它们用于保护目的的应用率仍然很低，部分原因是由于车辆的飞行范围有限以及动物检测和识别的困难，当前技术无法将发现外推到大空间尺度。特别是，使用 SWIR 相机和偏振滤光片与热相机相结合可能会改善动物检测，但迄今为止只有少数测试调查了这些技术的可靠性。分析来自高光谱相机等大型数据集需要技巧和时间，而最感兴趣的是这些调查的结果。此外，它们的应用还面临法律限制和高昂的初始投资成本。克服这些挑战需要提高工具的技术鲁棒性，以及定义无人机 (UAV) 在保护管理中的适用性。此外，与地面和/或空中调查相比，它的应用需要验证，以推荐不同生态环境和不同管理问题的协议。