Remote Sensing of Tundra Ecosystems Using High Spectral Resolution Reflectance: Opportunities and Challenges

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dc.contributor.authorNelson, Peter R.
dc.contributor.authorMaguire, Andrew J.
dc.contributor.authorPierrat, Zoe
dc.contributor.authorOrcutt, Erica L.
dc.contributor.authorYang, Dedi
dc.contributor.authorSerbin, Shawn
dc.contributor.authorFrost, Gerald V.
dc.contributor.authorMacander, Matthew J.
dc.contributor.authorMagney, Troy S.
dc.contributor.authorThompson, David R.
dc.contributor.authorWang, Jonathan A.
dc.contributor.authorOberbauer, Steven F.
dc.contributor.authorZesati, Sergio Vargas
dc.contributor.authorDavidson, Scott J.
dc.contributor.authorEpstein, Howard E.
dc.contributor.authorUnger, Steven
dc.contributor.authorCampbell, Petya Entcheva
dc.contributor.authorCarmon, Nimrod
dc.contributor.authorVelez-Reyes, Miguel
dc.contributor.authorHuemmrich, Karl
dc.date.accessioned2022-12-22T20:17:00Z
dc.date.available2022-12-22T20:17:00Z
dc.date.issued2022-02-03
dc.description.abstractObserving the environment in the vast regions of Earth through remote sensing platforms provides the tools to measure ecological dynamics. The Arctic tundra biome, one of the largest inaccessible terrestrial biomes on Earth, requires remote sensing across multiple spatial and temporal scales, from towers to satellites, particularly those equipped for imaging spectroscopy (IS). We describe a rationale for using IS derived from advances in our understanding of Arctic tundra vegetation communities and their interaction with the environment. To best leverage ongoing and forthcoming IS resources, including National Aeronautics and Space Administration’s Surface Biology and Geology mission, we identify a series of opportunities and challenges based on intrinsic spectral dimensionality analysis and a review of current data and literature that illustrates the unique attributes of the Arctic tundra biome. These opportunities and challenges include thematic vegetation mapping, complicated by low-stature plants and very fine-scale surface composition heterogeneity; development of scalable algorithms for retrieval of canopy and leaf traits; nuanced variation in vegetation growth and composition that complicates detection of long-term trends; and rapid phenological changes across brief growing seasons that may go undetected due to low revisit frequency or be obscured by snow cover and clouds. We recommend improvements to future field campaigns and satellite missions, advocating for research that combines multi-scale spectroscopy, from lab studies to satellites that enable frequent and continuous long-term monitoring, to inform statistical and biophysical approaches to model vegetation dynamicsen_US
dc.description.sponsorshipPeter R. Nelson and Matthew J. Macander were supported by NASA Arctic Boreal Vulnerability Experiment (ABoVE) Grant 80NSSC19M0112. Andrew J. Maguire was supported by an appointment to the NASA Postdoctoral Program at the Jet Propulsion Laboratory, administered by Universities Space Research Association under contract with NASA. Zoe Pierrat was supported by the National Science Foundation (NSF) Graduate Research Fellowship under Grant Nos. DGE-1650604 and DGE-2034835. Any opinion, findings, and conclusions or recommendations expressed in this material are those of the authors(s) and do not necessarily reflect the views of the NSF. Erica L. Orcutt and Troy S. Magney were supported by NASA ABoVE project 80NSSC19M0129. Dedi Yang and Shawn Serbin were supported by the Next-Generation Ecosystem Experiment in the Arctic (NGEE Arctic) project that is supported by the Office of Biological and Environmental Research in the United States Department of Energy, Office of Science, and through the Department of Energy Contract No. DE-SC0012704 to Brookhaven National Laboratory, and Shawn Serbin was also partially supported by the NASA Surface Biology and Geology mission study (under contract #NNG20OB24A). Gerald V. Frost was partially supported by NASA ABoVE Grant NNH16CP09C. Steven F. Oberbauer and Steven Unger were partially supported by NSF Office of Polar Programs award number 1836898. Sergio Vargas Zesati, Petya K. E. Campbell, and K. Fred Huemmrich were partially supported by NASA ABoVE grant NNX17AC58A, and Sergio Vargas Zesati was also partially supported by NSF ITEX-AON 1836861. Miguel Velez-Reyes was partially supported by NOAA NA16SEC4810008. AVIRIS-NG data was supported by the National Aeronautics and Space Administration, Earth Science Division, and acquired by the NASA ABoVE project. The data shown in Figure 5 were collected under a project funded by the OPP of the NSF awarded to Donatella Zona (award number 1204263) with additional logistical support funded by the NSF OPP, and Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE), an Earth Ventures (EV-1) investigation, under contract with NASA. A portion of this research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with NASA (80NM0018D0004).en_US
dc.description.urihttps://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2021JG006697en_US
dc.format.extent32 pagesen_US
dc.genrejournal articlesen_US
dc.identifierdoi:10.13016/m2ppsg-2eg0
dc.identifier.citationNelson, P. R., Maguire, A. J., Pierrat, Z., Orcutt, E. L., Yang, D., Serbin, S., et al. (2022). Remote sensing of tundra ecosystems using high spectral resolution reflectance: Opportunities and challenges. Journal of Geophysical Research: Biogeosciences, 127, e2021JG006697. https://doi.org/10.1029/2021JG006697en_US
dc.identifier.urihttps://doi.org/10.1029/2021JG006697
dc.identifier.urihttp://hdl.handle.net/11603/26508
dc.language.isoen_USen_US
dc.publisherAGUen_US
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Joint Center for Earth Systems Technology
dc.relation.ispartofUMBC Faculty Collection
dc.relation.ispartofUMBC GESTAR II
dc.relation.ispartofUMBC Geography and Environmental Systems Department
dc.rightsThis work was written as part of one of the author's official duties as an Employee of the United States Government and is therefore a work of the United States Government. In accordance with 17 U.S.C. 105, no copyright protection is available for such works under U.S. Law.en_US
dc.rightsPublic Domain Mark 1.0*
dc.rights.urihttp://creativecommons.org/publicdomain/mark/1.0/*
dc.titleRemote Sensing of Tundra Ecosystems Using High Spectral Resolution Reflectance: Opportunities and Challengesen_US
dc.typeTexten_US
dcterms.creatorhttps://orcid.org/0000-0002-0505-4951en_US
dcterms.creatorhttps://orcid.org/0000-0003-4148-9108en_US

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