Effective ecosystem management relies on accurate and timely evaluations of environmental trends, often equating to costly, time intensive survey efforts. Rapid advances in technology are constantly improving sampling methods, robust statistical inference, and thus cost and time efficiency. Perhaps one of the greatest steps in broad-scale habitat and wildlife monitoring has been advances in remote sensing technology. The Columbia River Basin is a major target for habitat restoration, working towards the de-listing of endangered Chinook salmon and Steelhead. Multi-scale habitat characteristics are critical to understanding what defines quality habitat and where to focus restoration efforts. We developed the DASH protocol to collect data at the channel unit scale in a rapid manner, which is then paired to multispectral imagery collected via drone. Thanks to the time and cost efficiency of drone surveys, this approach can be easily applied to larger (tributary, watershed) scales with minimal additional on-the-ground sampling. Furthermore, we have developed tools that automate the post-processing of drone imagery, substantially increasing the cost efficiency and ease of post-processing. The multi-scale approach also allows for the pairing of fish and habitat data as small as the channel-unit, which can be used to populate quantile regression forest (QRF) capacity models at the channel unit, reach, and watershed scale. In the Lemhi River, Salmon ID, we have applied DASH and QRF to define quality juvenile Chinook salmon and steelhead habitat, identify current capacity limitations, and monitor the effectiveness of restoration actions. Taken together, the two-pronged DASH and QRF approach is a comparatively inexpensive tool to prioritize, direct, and monitor habitat restoration in near real-time.