Unmanned aerial vehicles as innovative remote sensing platforms for high‐resolution infrared imagery to support restoration monitoring in cut‐over bogs

Question Can UAV ‐based NIR remote sensing support restoration monitoring of cut‐over bogs by providing valid information on species distribution and surface structure? Location Restored polders of the U chter M oor, a bog complex in NW G ermany. Methods We used autonomously flying quadrocopters, supplied with either a panchromatic or colour infrared calibrated small frame digital camera to generate high resolution images of the restored bog surface. We performed a two‐step classification process of automatic image segmentation and object‐based classification to distinguish between four pre‐defined classes (waterlogged bare peat, S phagnum spp., E riophorum vaginatum and B etula pubescens . An independent validation procedure was performed to evaluate the accuracy of the classification. Results A set‐up composed of decision rules for reflectance, geometry and textural features was applied for identification of the four classes. The presented classification revealed an overall accuracy level of 91%. Most reliable attribution was obtained for waterlogged bare peat and S phagnum ‐covered surfaces, revealing producer accuracies of 95% and 91%, respectively. Lower but still feasible accuracy levels were obtained for E riophorum vaginatum and B etula pubescens individuals (89% and 84%, respectively). Conclusions UAV ‐based NIR remote sensing is a promising tool for monitoring the restoration of cut‐over bogs and has the potential to significantly reduce laborious field surveys. UAV s may increasingly play a significant role in future ecological monitoring studies, since they are small in size, highly flexible, easy to handle, non‐emissive and available at a comparatively low cost.