Unraveling the intricate spatial and temporal complexities of vegetation represents a crucial key to understanding ecosystem functioning. Drones, as cutting-edge technology, hold immense potential in bridging the gap between on-ground measurements and satellite remote sensing data. Nonetheless, a multitude of challenges still looms, with one of the foremost being the nuanced identification of scales that strike a balance between capturing maximum complexity while minimizing measurement errors. To explore how current research deals with the above-mentioned challenges, we carried out a literature survey on research studies employing drones to characterize natural and semi-natural vegetation. We selected papers related to the role of spatial and/or temporal complexity in ecosystem state, function and/or services. Our result showed that most studies focused on ecosystem state, whereas function and services were barely addressed. Similarly, the effects of spatial or temporal scales on vegetation heterogeneity (complexity) are rarely studied even though drone technology seems ideal for this task. Since heterogeneity differs between ecosystems and its comprehension is greatly influenced by the features of the survey, careful design is important to maximize the efficiency and the range of complexity captured by the survey. However, in reality, most studies do not follow any specific planning of the drone survey according to the case study characteristics. In fact, we found a positive trend between spatial resolution and extent of the study area, and no significant relationship between spatial resolution and accuracy, regardless of the characteristics of the given ecosystem type. Specifically designed studies need to be carried out to further explore the effects of changing spatial and temporal resolution on complexity captured across ecosystem gradients, and establish the optimal resolution for different ecosystem types to assure transferability and operational use in land management. Despite the mentioned challenges and research gaps, drones represent a powerful and effective tool to explore vegetation complexity in new ways and dimensions. Nevertheless, there is an urgent need to define the appropriate methods for each scope.
How to cite: Mullerova, J.; R. Kent; J. Bruna; M. Bucas; J. Estrany; S. Manfreda; A. Michez; M. Mokros; M. A. Tsiafouli; X. Gago, Understanding spatio-temporal complexity of vegetation using drones, what could we improve?, Journal of Environmental Management, (doi: https://doi.org/10.1016/j.jenvman.2024.123656) 2024. [pdf]