Unmanned Aircraft Systems (UAS) have made dramatic technical advances in the past decade. Currently, their domestic use is tightly constrained by Federal Aviation Administration (FAA) regulations. Within the next few years, the FAA is expected to provide a regulatory framework allowing for a greatly expanded role for UAS in domestic airspace in a wide variety of applications, including remote sensing for land and natural resource monitoring.
In an investigation on the fidelity with which regional climate models (RCMs) simulate temperature extremes, large-scale meteorological patterns (LSMPs) associated with extreme-temperature days are evaluated for a suite of RCMs that are part of the North American Regional Climate Change Assessment Program (NARCCAP).
Dr. Calvert will present his research on the following three topics: 1) Improving site-suitability and land-use impact models for optimal spatial implementation of ground-mount solar photovoltaic (PV) systems in the Northeast U.S. 2) Pairing wine with wind, solar and biomass energy? An integrated assessment of opportunities and impacts related to renewable energy development in viniculture regions. 3) SolarPVAnalyst 2.0: Toward advanced geospatial decision-support for renewable energy implementation.
Land surface and anthropogenic processes shape and modify land surface forms and cover types. Multitemporal remote sensing, the collection, processing and analysis of image data collected from airborne and satellite sensors, enables monitoring of land surface forms and cover types over time. Underlying processes may be inferred and better understood through such monitoring. Professor Stow will provide an overview of multitemporal remote sensing approaches along with application examples from almost 40 years of his and his colleagues' and students' research. Development of end-to-end monitoring systems, environmental monitoring and land cover and land use change analyses will be emphasized.
While the concept of Adaptive Management has existed for more than 40 years and is widely accepted in natural resource management circles, few examples of its full implementation in the real world can be found. Why? One step in the Adaptive Management process stands out as an obstacle to full implementation: the development and use of models. According to the Adaptive Management literature, models should capture the hypothesis of how the system responsible for the problematic behavior works and be capable of testing interventions designed to produce a more desirable outcome. While a variety of modeling tools are available to natural resource managers, they generally come up short in achieving the Adaptive Management modeling requirements. The complex and dynamic nature of natural systems are largely to blame.