Development of multi-scale remote sensing methodologies to classify and monitor riparian vegetation structure and composition to improve agricultural sustainability

Sustainable agriculture in Washington State (WA) pushes to be economically viable while being environmentally responsible through improvements made to both on- and off-farm practices. Riparian (streamside) conservation measures are a primary off-farm field strategy to protect and enhance ecosystem functions and values, such as improving water quality and creating wildlife habitat. Two significant state administered programs incentivize these actions – the USDA Conservation Reserve Enhancement Program (CREP) and Voluntary Stewardship Program (VSP) overseen by the WA State Conservation Commission (SCC). Both programs require monitoring and reporting to reflect compliance and participation. Yet, to date, few states, including WA, take full advantage of available remotely sensed data, such as NAIP (National Agriculture Imagery Program) or Sentinel (satellite) imagery, or data collected from UAVs (Unpiloted Aerial Vehicles, a.k.a. drones). We hypothesize that underutilization of remotely sensed data in these programs is due to the lack of specific technical methods for monitoring riparian and natural vegetation in the agricultural setting and setting up a pipeline to integrate these methods into existing VSP and CREP monitoring programs. We propose to develop a transferable multi-scale methodology for monitoring riparian structure and composition as a proxy for ecosystem function that utilizes publicly available satellite and NAIP imagery, combined with field data collected by UAVs and on the ground. We will use BIOAg funding as a seed grant to develop this approach in Whitman County in cooperation with the Palouse Conservation District (PCD). With this approach, we will demonstrate the potential to improve the monitoring methods for large-scale conservation oriented programs.