From UAV Data Acquisition to Decision-Led Geospatial Monitoring: Stakeholder Perspectives from Scottish Peatland Restoration

Peatland restoration requires reliable monitoring across spatial scales, yet the expanding availability of unmanned aerial vehicles (UAVs), satellite Earth observation, geospatial analytics and field-based methods creates an important practical question: where do UAVs provide greatest value within an integrated environmental monitoring workflow? This study explores that question through qualitative stakeholder evidence collected during the development of a geospatial monitoring concept for Scottish peatland restoration. Semi-structured interviews with stakeholders involved in peatland monitoring, hydrology, land management, GIS and remote sensing were analysed thematically to examine current monitoring practices, perceived limitations and opportunities for UAV-supported approaches. The findings indicate that UAVs are valued for providing detailed, site-specific and repeatable observations, but their usefulness is strongly dependent on monitoring purpose and spatial scale. Participants identified limitations associated with weather, data-processing requirements, specialist expertise and the feasibility of repeatedly surveying large numbers of sites. The evidence also indicates that UAV observations cannot replace direct field measurements for several peatland variables and therefore require integration with ground-based and environmental evidence. At larger spatial scales, satellite Earth observation was perceived as offering advantages through systematic and repeatable coverage, while UAVs can provide a higher-resolution layer for selected locations and uncertainties. The study therefore proposes a decision-led geospatial monitoring framework in which satellite observation, GIS, targeted UAV acquisition and field validation are deployed according to spatial scale, environmental variable, uncertainty and decision need. The findings suggest that the future value of UAVs in environmental monitoring lies not simply in acquiring more high-resolution data, but in their targeted integration within multi-source geospatial intelligence workflows.