A Participatory Science Approach to Expanding Instream Infrastructure Inventories

Abstract

Over the past decade, remote sensing data have improved in resolution and become more widely available, bringing new opportunities for its use in environmental science and conservation. One potential application is to identify and map instream infrastructure across the world, with important implications for fisheries, hydrology, flooding, and more. To date, databases of instream infrastructure focus on larger dams with reservoirs that are comparatively easy to detect with remotely sensed imagery. Despite their impact on freshwater ecosystems, smaller infrastructure is often overlooked. To overcome these challenges, we require more systematic approaches, such as the Global River Obstruction Database (GROD) presented here, to map instream infrastructure. We present a participatory approach to identify, map, and validate infrastructure and provide an initial data set for the contiguous United States (n = 4,197). We highlight the value of participatory methods that include the public and suggest ways they could be fused with machine learning for future applications.