Theses and Dissertations Collection

Position, Navigation and Timing (PNT) technologies have rapidly become an integral part of our everyday lives, through mobile applications, activity sharing, global navigation satellite system (GNSS) supported devices, real-time monitoring of consumer goods and the Internet of Things (IoT). Further, remote sensing data provide unique solutions for aiding PNT methods and techniques in the planning and assessment of active land management through the derivation of site and stand metrics used to develop models. Increased ease of access to a wide range of data sources has supported the expansion of network infrastructures and availability for data sharing and transfer at local and global scales. High-resolution, remotely sensed data and mobile, off-the-grid data collection and interpretation methods provide valuable solutions for production analysis, treatment analysis and data sharing in natural resource management scenarios. Precision forestry and production analytics for industrial forest and fire operations are rapidly transforming through the integration of global navigation satellite system and radio frequency (GNSS-RF) enabled devices, smartphone-based inertial sensors, and high resolution remotely sensed data. Consumer available technologies and data provide the means to collect, share and analyze spatially explicit data using multi-transponder mesh networks and activity recognition models. However, the application of these technologies in operational forest management scenarios for activity recognition and production analysis has received very little attention in formal research. By evaluating operational applications of PNT technologies in forest management, mangers may be able to maximize their effective mobilization effort to manage land and improve on optimization of the operations themselves. Additionally, coupled use of high resolution remotely sensed data with real-time location and activity analytics may provide insight into management effectiveness and post-treatment stand conditions at landscape scales to assist managers in the strategic planning and implementation of future operations.