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


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Can UAV-based NIR remote sensing support restoration monitoring of cut-over bogs by providing valid information on species distribution and surface structure?


Restored polders of the Uchter Moor, a bog complex in NW Germany.


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 spp., Eriophorum vaginatum and Betula pubescens. An independent validation procedure was performed to evaluate the accuracy of the classification.


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 Sphagnum-covered surfaces, revealing producer accuracies of 95% and 91%, respectively. Lower but still feasible accuracy levels were obtained for Eriophorum vaginatum and Betula pubescens individuals (89% and 84%, respectively).


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 in size, highly flexible, easy to handle, non-emissive and available at a comparatively low cost.

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