Leveraging the NEON Airborne Observation Platform for socio‐environmental systems research
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. 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..
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2021 |
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| Erschienen: |
2021 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:12 |
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| Enthalten in: |
Ecosphere - 12(2021), 6 |
| Anmerkungen: |
© 2021 Ecological Society of America |
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| Umfang: |
19 |
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| doi: |
10.1002/ecs2.3640 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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WLY004823389 |
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| 520 | |a 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. 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. | ||
| 700 | 1 | |a Elmore, Andrew J. |4 aut | |
| 700 | 1 | |a Kolstoe, Sonja |4 aut | |
| 700 | 1 | |a Quinn, John E. |4 aut | |
| 700 | 1 | |a Swanwick, Rachel |4 aut | |
| 700 | 1 | |a Cattau, Megan |4 aut | |
| 700 | 1 | |a Taillie, Dylan |4 aut | |
| 700 | 1 | |a Guinn, Steven M. |4 aut | |
| 700 | 1 | |a Chadwick, K. Dana |4 aut | |
| 700 | 1 | |a Atkins, Jeff W. |4 aut | |
| 700 | 1 | |a Blake, Rachael E. |4 aut | |
| 700 | 1 | |a Chapman, Melissa |4 aut | |
| 700 | 1 | |a Cobourn, Kelly |4 aut | |
| 700 | 1 | |a Goulden, Tristan |4 aut | |
| 700 | 1 | |a Helmus, Matthew R. |4 aut | |
| 700 | 1 | |a Hondula, Kelly |4 aut | |
| 700 | 1 | |a Hritz, Carrie |4 aut | |
| 700 | 1 | |a Jensen, Jennifer |4 aut | |
| 700 | 1 | |a Julian, Jason P. |4 aut | |
| 700 | 1 | |a Kuwayama, Yusuke |4 aut | |
| 700 | 1 | |a Lulla, Vijay |4 aut | |
| 700 | 1 | |a O’Leary, Donal |4 aut | |
| 700 | 1 | |a Nelson, Donald R. |4 aut | |
| 700 | 1 | |a Ocón, Jonathan P. |4 aut | |
| 700 | 1 | |a Pau, Stephanie |4 aut | |
| 700 | 1 | |a Ponce‐Campos, Guillermo E. |4 aut | |
| 700 | 1 | |a Portillo‐Quintero, Carlos |4 aut | |
| 700 | 1 | |a Pricope, Narcisa G. |4 aut | |
| 700 | 1 | |a Rivero, Rosanna G. |4 aut | |
| 700 | 1 | |a Schneider, Laura |4 aut | |
| 700 | 1 | |a Steele, Meredith |4 aut | |
| 700 | 1 | |a Tulbure, Mirela G. |4 aut | |
| 700 | 1 | |a Williamson, Matthew A. |4 aut | |
| 700 | 1 | |a Wilson, Cyril |4 aut | |
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