From pixels to riverscapes: How remote sensing and geospatial tools can prioritize riverscape restoration at multiple scales

Abstract

Prioritizing restoration opportunities effectively across entire riverscape networks (i.e., riverine landscape including floodplain and stream channel networks) can be difficult when relying on in-channel, reach-scale monitoring data, or watershed-level summaries that fail to capture riverscape heterogeneity and the information necessary to implement restoration actions. Leveraging remote sensing and geospatial tools to develop spatially continuous information across nested hierarchical scales may support increased understanding of local riverscape reaches in their broader network context. Using riparian (vegetation) and geomorphic (elevation) indicators to assess status of riverscape health, along with a measure of restoration capacity (valley bottom area), could be adapted to fit specific management goals related to riverscape restoration. Frameworks using remotely sensed vegetation and elevation data to prioritize restoration continuously across riverscapes at restoration-relevant, reach-scales may uphold the ecosystem services provided by riverscapes. By incorporating local knowledge and identifying caveats for using these datasets, continuous inferences can be applied at network scales (watershed to regional extent and reach-scale resolution) to prioritize restoration over a wide variety of ecoregions.