Over the last three years, researchers have piloted the use of remotely piloted vehicles (RPVs, aka drones) to accurately measure stream surface water velocities, water surface temperatures, and grain size distributions in streams ecosystems. Further developing these methods will improve a wide range of scientific research, such as hydrology, geomorphology, ecology, and water resources management. For example, the potential application of drone-based sensing are rapid documentation of pre- and post- river restoration actions, enumerating salmon and salmon egg nests (redds), and quantifying both in-stream and riparian habitat, to name a few. Integration of drone technologies in river research remains nascent and will require further methodological development and evaluation to be readily available for water resource application. For this reason, we propose to further develop drone-based tools to support low-cost process-based environmental monitoring. Specifically, we will advance three drone-based methods and integrate them into a simple model to predict Pacific salmon spawning habitat. We will evaluate the spawning habitat map using summer chinook salmon redds in the Wenatchee River together with the Washington Department of Fish and Wildlife. The proposed research is part of Daniel Auerbach’s doctoral dissertation, and we will train at least two WSU undergraduate students. Our methods will be transferable across river systems, and we will share protocols with resource management agencies and researchers. The main contribution of the proposed work is the development and application of drone methods for quantifying stream processes and patterns, and importantly, the integration of new methodologies into monitoring of natural resources.