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Leveraging the NEON Airborne Observation Platform for socio-environmental systems research

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dc.contributor.authorOrdway, Elsa M.en
dc.contributor.authorElmore, Andrew J.en
dc.contributor.authorKolstoe, Sonjaen
dc.contributor.authorQuinn, John E.en
dc.contributor.authorSwanwick, Rachelen
dc.contributor.authorCattau, Meganen
dc.contributor.authorTaillie, Dylanen
dc.contributor.authorGuinn, Steven M.en
dc.contributor.authorChadwick, K. Danaen
dc.contributor.authorAtkins, Jeff W.en
dc.contributor.authorBlake, Rachael E.en
dc.contributor.authorChapman, Melissaen
dc.contributor.authorCobourn, Kelly M.en
dc.contributor.authorGoulden, Tristanen
dc.contributor.authorHelmus, Matthew R.en
dc.contributor.authorHondula, Kellyen
dc.contributor.authorHritz, Carrieen
dc.contributor.authorJensen, Jenniferen
dc.contributor.authorJulian, Jason P.en
dc.contributor.authorKuwayama, Yusukeen
dc.contributor.authorLulla, Vijayen
dc.contributor.authorO'Leary, Donalen
dc.contributor.authorNelson, Donald R.en
dc.contributor.authorOcon, Jonathan P.en
dc.contributor.authorPau, Stephanieen
dc.contributor.authorPonce-Campos, Guillermo E.en
dc.contributor.authorPortillo-Quintero, Carlosen
dc.contributor.authorPricope, Narcisa G.en
dc.contributor.authorRivero, Rosanna G.en
dc.contributor.authorSchneider, Lauraen
dc.contributor.authorSteele, Meredith K.en
dc.contributor.authorTulbure, Mirela G.en
dc.contributor.authorWilliamson, Matthew A.en
dc.contributor.authorWilson, Cyrilen
dc.date.accessioned2021-11-18T17:41:58Zen
dc.date.available2021-11-18T17:41:58Zen
dc.date.issued2021-06en
dc.description.abstractDuring 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. In addition to providing an overview of NEON AOP datasets and outlining specific applications for addressing SES questions, we 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 yr, 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 SES research community to further explore questions and theories in social and economic disciplines that might leverage NEON AOP data.en
dc.description.notesThis article emerged from a workshop titled People, Land, & Ecosystems: Leveraging NEON for SocioEnvironmental Synthesis that was held at the National Socio-Environmental Synthesis Center (SESYNC). This work was supported by SESYNC under funding received from the National Science Foundation DBI1639145. The National Ecological Observatory Network is a program sponsored by the National Science Foundation and operated under cooperative agreement by Battelle Memorial Institute. This material is based in part upon work supported by the National Science Foundation through the NEON Program. The conclusions in this publication are those of the authors and should not be construed to represent any official USDA or U.S. Government determination or policy.en
dc.description.sponsorshipSESYNC under National Science Foundation [DBI-1639145]; National Science FoundationNational Science Foundation (NSF); National Science Foundation through the NEON Programen
dc.description.versionPublished versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.doihttps://doi.org/10.1002/ecs2.3640en
dc.identifier.issn2150-8925en
dc.identifier.issue6en
dc.identifier.othere03640en
dc.identifier.urihttp://hdl.handle.net/10919/106680en
dc.identifier.volume12en
dc.language.isoenen
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.subjectCHANSen
dc.subjectimaging spectroscopyen
dc.subjectLiDARen
dc.subjectNEON AOPen
dc.subjectremote sensingen
dc.subjectsocio-ecological systemsen
dc.subjectsocio-environmental systemsen
dc.subjectSpecial Featureen
dc.subjectHarnessing the NEON Data Revolutionen
dc.titleLeveraging the NEON Airborne Observation Platform for socio-environmental systems researchen
dc.title.serialEcosphereen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten

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