Spatially Balanced Sampling, Route Optimization and Drone Imagery to Advance Restoration Monitoring

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Michael F. Curran

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As we enter the UN Decade on Ecosystem Restoration, the importance of ecological restoration is of broad global interest. To understand the outcomes of ecological restoration efforts, sound monitoring plans which are time- and cost effective are necessary. However, many existing monitoring techniques are focused mainly at answering regulatory criteria and do not give a full understanding to the outcome of the restoration effort in place. Additionally, many commonly used monitoring techniques are expensive and considered burdensome to companies required to perform ecological restoration. Here, we present a study which compares small unmanned aircraft system (sUAS) imagery to handheld imagery to monitor vegetation on natural gas well pads undergoing restoration. These methods have numerous benefits over traditional techniques. In addition to showing these image-based techniques, we couple a spatially balanced sampling design, called balanced acceptance sampling, with the traveling salesperson algorithm to optimize the route of the sUAS and technician using a handheld camera. We find the sUAS can obtain images similar in quality to handheld images in ~7.5 minutes per location, whereas handheld image acquisition takes ~30 minutes per site. Both of these methods are significantly faster than typical line point transect which are subject to various forms of sampling error. We conclude that the use of sUAS should be considered as a viable option to monitor restoration efforts moving forward due to the time- and cost-saving, the improved statistical power and the ability to answer multiple regulatory criteria and while providing information to improve future restoration efforts.

Resource Type:
Conference Presentation, SER2021

Pre-approved for CECs under SER's CERP program