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.