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Patterns, Places, People: Leveraging the NEON Airborne Observation Platform for scalable observation of Socio-Environmental Systems
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  • Elsa Ordway,
  • Andrew Elmore,
  • Megan Cattau,
  • Donald Nelson,
  • Meredith Steele,
  • Cathlyn Stylinski,
  • Matthew Williamson
Elsa Ordway
UCLA

Corresponding Author:[email protected]

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Andrew Elmore
University of Maryland Center (UMCES) for Environmental Science
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Megan Cattau
Boise State University
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Donald Nelson
University of Georgia
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Meredith Steele
Virginia Polytechnic Institute and State University
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Cathlyn Stylinski
University of Maryland Center for Environmental Science Appalachian Laboratory
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Matthew Williamson
Boise State University
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Abstract

During the 21st century, human–environment interactions will increasingly expose both systems to risks, but also yield opportunities for improvement as we gain insight into these complex coupled-systems. Human–environment interactions operate over multiple spatial and temporal scales, requiring large data volumes of multi-resolution information for analysis. Climate change, land-use change, urbanization, and wildfires, for example, can affect regions differently depending on ecological and socioeconomic structures. The relative scarcity of data on both humans and natural systems at the relevant extent can be prohibitive when pursuing inquiries into these complex relationships. We explore the value of multitemporal, high-density, and high-resolution LiDAR, imaging spectroscopy, and digital camera data from the National Ecological Observatory Network’s Airborne Observation Platform (NEON AOP) for Socio-Environmental Systems (SES) research. We outline specific applications for addressing SES questions, highlight current challenges, and provide recommendations for the SES research community to improve and expand its use of this platform for SES research. The coordinated, nationwide AOP remote sensing data, collected annually over the next 30 years, offer exciting opportunities for cross-site analyses and comparison, upscaling metrics derived from LiDAR and hyperspectral datasets across larger spatial extents, and addressing questions across diverse scales. Integrating AOP data with other SES datasets will allow researchers to investigate complex systems and provide urgently needed policy recommendations for socio-environmental challenges. We urge the research community to further explore interdisciplinary questions and theories that might leverage NEON AOP data, and present a new Research Coordination Network aimed at supporting these efforts.