Data fusion methods for combining remote sensing and wildlife tracking data

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The overall objective of this proposal is to integrate state-of-the-art remote sensing techniques with innovative methods for understanding wildlife movement behavior. Our research is timely given the rapid development of remote sensing technology, combined with new loggers for tracking wildlife locations. In particular, my program will focus on two primary areas of methodological research: 1) models for quantifying wildlife space use and 2) methods for understanding inter-individual interactions, for example human disturbance of wildlife. My team and I will apply the methods we develop to applied research problems in wildlife spatial ecology through local, national, and international collaborations. Understanding space-time patterns in high-resolution wildlife tracking data is a major methodological challenge in GIScience. A key limitation of current methods is the ability to characterize relationships between movement patterns and environmental change. When we fail to capture how wildlife respond to dynamic environmental conditions, we are limited in our ability to make sound decisions for management or conservation activities. Therefore, new methods for combining high resolution wildlife tracking data with remotely sensed data are necessary to better capture and understand how patterns of wildlife movement relate to dynamic, rapidly changing environments. Current methods for integrating wildlife tracking data with remotely sensed data typically use single-date or single-satellite composites, and therefore, remain limited in their ability to capture fine-scale spatial and temporal changes in the environment. Therefore, satellite data fusion - combining satellite data from multiple sensors - represents a major opportunity for improved understanding in wildlife movement studies. My program emphasizes the training of HQP. Specifically, my proposal will support 13 current and future HQP (undergraduate, graduate, technical staff), who will be trained in GIS, remote sensing, and wildlife conservation. My trainees are taught a variety of technical skills which are highly marketable within and outside of academia. Our work will be published in high-impact scientific journals and presented at national and international academic conferences. We will achieve broad societal impact by working with local, national, and international partners in applied wildlife conservation and through the development of free and open source software tools for geospatial analysis.