Unmanned Aerial Vehicles as innovative remote sensing platforms for high-resolution infrared imagery to support restoration monitoring in cut-over bogs

Knoth C, Klein B, Prinz T, Kleinebecker T

Zusammenfassung

Question: Can UAV-based NIR remote sensing support restoration monitoring of cutover bogs by providing valid information on species distribution and surface structure? Location: Restored polders of the Uchter Moor, a bog complex in NW-Germany. 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, Sphagnum spec., Eriophorum vaginatum, and Betula pubescens). An independent validation procedure was performed to evaluate the accuracy of the classification. Results: A setup of decision rules for reflectance, geometry and texture features was applied for the 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 Sphagnum-covered surfaces revealing producers accuracies of 95 and 91%. Lower but still feasible accuracy levels were obtained for Eriophorum vaginatum and Betula bubescens 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. UAVs may increasingly play a significant role in future ecological monitoring studies, since they are small sized, highly flexible, easy to handle, non-emissive and available at a comparatively low cost.