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\begin{document}

\title{Patterns, Places, People: Leveraging the NEON Airborne Observation
Platform for scalable observation of Socio-Environmental Systems}



\author[1]{Elsa Ordway}%
\author[2]{Andrew Elmore}%
\author[3]{Megan Cattau}%
\author[4]{Donald Nelson}%
\author[5]{Meredith Steele}%
\author[6]{Cathlyn Stylinski}%
\author[3]{Matthew Williamson}%
\affil[1]{UCLA}%
\affil[2]{University of Maryland Center (UMCES) for Environmental Science}%
\affil[3]{Boise State University}%
\affil[4]{University of Georgia}%
\affil[5]{Virginia Polytechnic Institute and State University}%
\affil[6]{University of Maryland Center for Environmental Science Appalachian Laboratory}%


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  \date{June 13, 2024}


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\begin{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.%
\end{abstract}%



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