Grant: Discovery Grants Program - Individual

In the face of climate change, adaptive management has risen to prominence as a method to ensure the sustainability and resilience of ecosystems. However, no single observational technology yet exists that can provide timely measurements of environmental systems at sufficient spatiotemporal scales to drive the analyses necessary to enable adaptive management of complex ecosystems. Remote sensing by remotely piloted aircraft systems (RPASs) has immense potential for filling this data gap, however, three key advancements must be made. First, methods must be developed to correct for errors inherent in acquiring high-spatial-resolution imagery using lightweight aerial platforms. Second, the spatial extent of these data must be increased by fusing them with satellite data, and third, methods must be developed to cope with the immense data volume constituted by high spatial, spectral, and temporal resolution imagery. The long-term objective of this program is to explore how high-resolution RPAS remote sensing can best enable ecosystem management. At the crux of this question is the ability to efficiently derive land cover information from high-resolution RPAS-acquired remote sensing data. As the field of ecosystem management is broad, in the near-term, my research program will focus on rangeland management, and will be organized around the following research question: "Can high spatial/spectral/temporal resolution data acquired by RPAS technology be used alone or fused with satellite-based remote sensing to achieve highly-resolved, accurate spectral measurements that can be used to quantify rangeland characteristics at the pasture scale?" Specifically, the short-term objectives of this research are: �To evaluate methods for noise reduction in RPAS-acquired imagery �To fuse these data with satellite-acquired data to increase coverage �To identify strategies to accelerate the processing of high-resolution imagery The proposed work will provide benefits to society by providing insights on how rangeland can be managed adaptively to balance the objectives of increasing forage productivity and grazing potential, and thus, increase the efficiency of the ranching industry. The proposed work will also enhance infrastructure for research through the creation of a program for real-time sensing of coupled natural, built, and social systems using consumer-grade sensing equipment. Finally, it will promote teaching and learning of science, technology, engineering and math (STEM) by integrating leading-edge research into STEM education for Thompson Rivers University's diverse student population and by training highly qualified personnel who will bring both scientific excellence and an inclusive orientation to STEM into the Canadian research sphere.