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Abstract Given the critical importance of freshwater for human well‐being and the myriad threats altering water quality and quantity, monitoring lakes and reservoirs is necessary to identify where, how, and why freshwater ecosystems are changing globally. Satellite remote sensing tools hold great promise for improving water quality monitoring to advance research and management objectives, but “ready‐to‐use” solutions are not yet available for navigating the decisions required to collect, process, and analyze quality remote sensing data. While new products and techniques are continuously being developed, their use for research and management remains challenging. Aspiring users of satellite data face key decisions among many different options to select, process, and use these data to estimate surface water quality parameters. These decisions have important downstream consequences for inference, but knowledge gaps remain in how to navigate them to match project goals, particularly for interdisciplinary teams. We point to key considerations for how users can evaluate the spatiotemporal requirements for their specific project and identify essential decision points in how to process and interpret the acquired satellite data to estimate water quality parameters, using cyanobacterial blooms as a focal example. Well‐considered front‐end decisions are crucial for matching satellite and in situ data and fully leveraging satellite data to address the specific question and system. Importantly, the science and tools underlying remote sensing methods are evolving quickly and the “best” choices depend on the study or monitoring objective. We provide information for nonspecialists and questions for interdisciplinary teams to consider to aid in the wise use of this transformative technology. We conclude by identifying five priorities for further development and emphasizing the importance of reciprocal knowledge exchange and engagement between the aquatic ecology and remote sensing communities.
Trout‐Haney et al. (Wed,) studied this question.