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Seismic lines – linear exploration corridors constructed for petroleum exploration – bisect the forests of northern Alberta and influence a host of ecosystem processes. There are an estimated 1.8 million kilometers of seismic lines in Alberta alone. Unfortunately, many of these lines are in a state of arrested succession and are unlikely to recover without active intervention. This problem is particularly common in wetlands where the equipment used to construct seismic lines has compressed the soil, creating conditions that are unsuitable for ‘normal’ vegetation communities. A complete inventory of seismic line age and era of construction does not yet exist. My proposed research project aims to validate and calibrate machine learning algortihms with the help of spatial covariates to create large scale datasets of line era construction conditions. The approach will be based on remote sensing data (LiDAR) and a reference dataset as well as additional data from field trips to Lower Athabasca regions of Alberta. If succesful, this information may be of high value to eternal stakeholders and influence best forest recovery management practices.
Greg McDermid
Ludwig-Maximilians-Universität München
Physics
Education
University of Calgary
Globalink Research Award
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