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

Observing 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 t...

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Veröffentlicht in:Journal of geophysical research. Biogeosciences 2022-02, Vol.127 (2), p.n/a
Hauptverfasser: Nelson, Peter R., Maguire, Andrew J., Pierrat, Zoe, Orcutt, Erica L., Yang, Dedi, Serbin, Shawn, Frost, Gerald V., Macander, Matthew J., Magney, Troy S., Thompson, David R., Wang, Jonathan A., Oberbauer, Steven F., Zesati, Sergio Vargas, Davidson, Scott J., Epstein, Howard E., Unger, Steven, Campbell, Petya K. E., Carmon, Nimrod, Velez‐Reyes, Miguel, Huemmrich, K. Fred
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container_issue 2
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container_title Journal of geophysical research. Biogeosciences
container_volume 127
creator Nelson, Peter R.
Maguire, Andrew J.
Pierrat, Zoe
Orcutt, Erica L.
Yang, Dedi
Serbin, Shawn
Frost, Gerald V.
Macander, Matthew J.
Magney, Troy S.
Thompson, David R.
Wang, Jonathan A.
Oberbauer, Steven F.
Zesati, Sergio Vargas
Davidson, Scott J.
Epstein, Howard E.
Unger, Steven
Campbell, Petya K. E.
Carmon, Nimrod
Velez‐Reyes, Miguel
Huemmrich, K. Fred
description Observing 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 dynamics. Plain Language Summary Remote sensing has a long history of characterizing the distribution and dynamics of vegetation in a wide variety of biomes, including the Arctic tundra which is experiencing warming more rapidly than the global average. Imaging spectroscopy (IS)—a rapidly advancing field of remote sensing that measures reflected light in narrow, contiguous “colors” from satellites, aircraft, or towers—has demonstrated great promise to “watch” how key land surface properties vary across space and over time. Because they are vast, remote, and have relatively little infrastructure, currently available IS data from the Arctic tundra are sporadic and intermittent. Hence, it has been challenging to study and characterize these ecosystems across broad spatial scales and through
doi_str_mv 10.1029/2021JG006697
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E. ; Carmon, Nimrod ; Velez‐Reyes, Miguel ; Huemmrich, K. Fred</creator><creatorcontrib>Nelson, Peter R. ; Maguire, Andrew J. ; Pierrat, Zoe ; Orcutt, Erica L. ; Yang, Dedi ; Serbin, Shawn ; Frost, Gerald V. ; Macander, Matthew J. ; Magney, Troy S. ; Thompson, David R. ; Wang, Jonathan A. ; Oberbauer, Steven F. ; Zesati, Sergio Vargas ; Davidson, Scott J. ; Epstein, Howard E. ; Unger, Steven ; Campbell, Petya K. E. ; Carmon, Nimrod ; Velez‐Reyes, Miguel ; Huemmrich, K. Fred ; Brookhaven National Lab. (BNL), Upton, NY (United States)</creatorcontrib><description>Observing 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 dynamics. Plain Language Summary Remote sensing has a long history of characterizing the distribution and dynamics of vegetation in a wide variety of biomes, including the Arctic tundra which is experiencing warming more rapidly than the global average. Imaging spectroscopy (IS)—a rapidly advancing field of remote sensing that measures reflected light in narrow, contiguous “colors” from satellites, aircraft, or towers—has demonstrated great promise to “watch” how key land surface properties vary across space and over time. Because they are vast, remote, and have relatively little infrastructure, currently available IS data from the Arctic tundra are sporadic and intermittent. Hence, it has been challenging to study and characterize these ecosystems across broad spatial scales and through time. Furthermore, the climate and ecology of these ecosystems pose unique challenges for employing and interpreting IS data. Inspired by a forthcoming National Aeronautics and Space Administration satellite‐based IS mission, we present an overview of the current opportunities and challenges for the use of spectroscopy to study Arctic tundra, informed by novel measurements across a range of spatial and temporal scales. We share recommendations for how researchers could leverage IS to resolve pressing ecological questions and advance the design and sampling scheme of future instruments and campaigns. Key Points Imaging spectroscopy (IS) can help to measure the critical Arctic tundra properties, physiological function, and temporal dynamics Upcoming IS satellite missions including National Aeronautics and Space Administration’s Surface Biology and Geology will make IS data widely available for Arctic tundra regions To properly interpret IS data users must consider spectral complexity of tundra driven by composition, sensitivity to climate, and phenology</description><identifier>ISSN: 2169-8953</identifier><identifier>EISSN: 2169-8961</identifier><identifier>DOI: 10.1029/2021JG006697</identifier><language>eng</language><publisher>Washington: Blackwell Publishing Ltd</publisher><subject>Aeronautics ; Algorithms ; Analytical methods ; Arctic tundra ; Biology ; Composition ; Current data ; Dynamics ; Ecosystems ; ENVIRONMENTAL SCIENCES ; Geology ; Growing season ; Heterogeneity ; imaging spectroscopy ; Imaging techniques ; Instruments ; intrinsic dimensionality ; Plant cover ; Plants (botany) ; Reflectance ; Remote observing ; Remote sensing ; Satellite imagery ; Satellites ; Snow cover ; Spectral resolution ; Spectroscopic analysis ; Spectroscopy ; Spectrum analysis ; surface biology and geology ; Surface properties ; Taiga &amp; tundra ; Towers ; Tundra ; Vegetation ; Vegetation growth ; Vegetation mapping ; Vegetation surveys ; Work platforms</subject><ispartof>Journal of geophysical research. 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E.</creatorcontrib><creatorcontrib>Carmon, Nimrod</creatorcontrib><creatorcontrib>Velez‐Reyes, Miguel</creatorcontrib><creatorcontrib>Huemmrich, K. Fred</creatorcontrib><creatorcontrib>Brookhaven National Lab. (BNL), Upton, NY (United States)</creatorcontrib><title>Remote Sensing of Tundra Ecosystems Using High Spectral Resolution Reflectance: Opportunities and Challenges</title><title>Journal of geophysical research. Biogeosciences</title><description>Observing 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 dynamics. Plain Language Summary Remote sensing has a long history of characterizing the distribution and dynamics of vegetation in a wide variety of biomes, including the Arctic tundra which is experiencing warming more rapidly than the global average. Imaging spectroscopy (IS)—a rapidly advancing field of remote sensing that measures reflected light in narrow, contiguous “colors” from satellites, aircraft, or towers—has demonstrated great promise to “watch” how key land surface properties vary across space and over time. Because they are vast, remote, and have relatively little infrastructure, currently available IS data from the Arctic tundra are sporadic and intermittent. Hence, it has been challenging to study and characterize these ecosystems across broad spatial scales and through time. Furthermore, the climate and ecology of these ecosystems pose unique challenges for employing and interpreting IS data. Inspired by a forthcoming National Aeronautics and Space Administration satellite‐based IS mission, we present an overview of the current opportunities and challenges for the use of spectroscopy to study Arctic tundra, informed by novel measurements across a range of spatial and temporal scales. We share recommendations for how researchers could leverage IS to resolve pressing ecological questions and advance the design and sampling scheme of future instruments and campaigns. Key Points Imaging spectroscopy (IS) can help to measure the critical Arctic tundra properties, physiological function, and temporal dynamics Upcoming IS satellite missions including National Aeronautics and Space Administration’s Surface Biology and Geology will make IS data widely available for Arctic tundra regions To properly interpret IS data users must consider spectral complexity of tundra driven by composition, sensitivity to climate, and phenology</description><subject>Aeronautics</subject><subject>Algorithms</subject><subject>Analytical methods</subject><subject>Arctic tundra</subject><subject>Biology</subject><subject>Composition</subject><subject>Current data</subject><subject>Dynamics</subject><subject>Ecosystems</subject><subject>ENVIRONMENTAL SCIENCES</subject><subject>Geology</subject><subject>Growing season</subject><subject>Heterogeneity</subject><subject>imaging spectroscopy</subject><subject>Imaging techniques</subject><subject>Instruments</subject><subject>intrinsic dimensionality</subject><subject>Plant cover</subject><subject>Plants (botany)</subject><subject>Reflectance</subject><subject>Remote observing</subject><subject>Remote sensing</subject><subject>Satellite imagery</subject><subject>Satellites</subject><subject>Snow cover</subject><subject>Spectral resolution</subject><subject>Spectroscopic analysis</subject><subject>Spectroscopy</subject><subject>Spectrum analysis</subject><subject>surface biology and geology</subject><subject>Surface properties</subject><subject>Taiga &amp; tundra</subject><subject>Towers</subject><subject>Tundra</subject><subject>Vegetation</subject><subject>Vegetation growth</subject><subject>Vegetation mapping</subject><subject>Vegetation surveys</subject><subject>Work platforms</subject><issn>2169-8953</issn><issn>2169-8961</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>24P</sourceid><recordid>eNp9kE9LAzEQxRdRsNTe_ABBr1aT7G66601K3SqFQv-cQ5rMtinbZE2ySL-9qRXx5FxmePNjePOS5JbgR4Jp-UQxJe8VxoyVo4ukRwkrh0XJyOXvnKfXycD7PY5VRImQXtIs4GADoCUYr80W2RqtOqOcQBNp_dEHOHi0_l5N9XaHli3I4ESDFuBt0wVtTRzrJqrCSHhG87a1LnRGBw0eCaPQeCeaBswW_E1yVYvGw-Cn95P162Q1ng5n8-pt_DIbyozkbChLsVGUAYxImhOR15SSOitqBZipvGQFFUpkWNGipLlIFWOZ3IBUSow2GQac9pO7813rg-Ze6gByJ60x0SUnRUYIPkH3Z6h19qMDH_jeds5EX5yylNKYJ80i9XCmpLPeO6h56_RBuCMnmJ9y539zj3h6xj91A8d_Wf5eLar4WcbSL6IVhEA</recordid><startdate>202202</startdate><enddate>202202</enddate><creator>Nelson, Peter R.</creator><creator>Maguire, Andrew J.</creator><creator>Pierrat, Zoe</creator><creator>Orcutt, Erica L.</creator><creator>Yang, Dedi</creator><creator>Serbin, Shawn</creator><creator>Frost, Gerald V.</creator><creator>Macander, Matthew J.</creator><creator>Magney, Troy S.</creator><creator>Thompson, David R.</creator><creator>Wang, Jonathan A.</creator><creator>Oberbauer, Steven F.</creator><creator>Zesati, Sergio Vargas</creator><creator>Davidson, Scott J.</creator><creator>Epstein, Howard E.</creator><creator>Unger, Steven</creator><creator>Campbell, Petya K. 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Biogeosciences</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Nelson, Peter R.</au><au>Maguire, Andrew J.</au><au>Pierrat, Zoe</au><au>Orcutt, Erica L.</au><au>Yang, Dedi</au><au>Serbin, Shawn</au><au>Frost, Gerald V.</au><au>Macander, Matthew J.</au><au>Magney, Troy S.</au><au>Thompson, David R.</au><au>Wang, Jonathan A.</au><au>Oberbauer, Steven F.</au><au>Zesati, Sergio Vargas</au><au>Davidson, Scott J.</au><au>Epstein, Howard E.</au><au>Unger, Steven</au><au>Campbell, Petya K. E.</au><au>Carmon, Nimrod</au><au>Velez‐Reyes, Miguel</au><au>Huemmrich, K. Fred</au><aucorp>Brookhaven National Lab. (BNL), Upton, NY (United States)</aucorp><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Remote Sensing of Tundra Ecosystems Using High Spectral Resolution Reflectance: Opportunities and Challenges</atitle><jtitle>Journal of geophysical research. Biogeosciences</jtitle><date>2022-02</date><risdate>2022</risdate><volume>127</volume><issue>2</issue><epage>n/a</epage><issn>2169-8953</issn><eissn>2169-8961</eissn><abstract>Observing 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 dynamics. Plain Language Summary Remote sensing has a long history of characterizing the distribution and dynamics of vegetation in a wide variety of biomes, including the Arctic tundra which is experiencing warming more rapidly than the global average. Imaging spectroscopy (IS)—a rapidly advancing field of remote sensing that measures reflected light in narrow, contiguous “colors” from satellites, aircraft, or towers—has demonstrated great promise to “watch” how key land surface properties vary across space and over time. Because they are vast, remote, and have relatively little infrastructure, currently available IS data from the Arctic tundra are sporadic and intermittent. Hence, it has been challenging to study and characterize these ecosystems across broad spatial scales and through time. Furthermore, the climate and ecology of these ecosystems pose unique challenges for employing and interpreting IS data. Inspired by a forthcoming National Aeronautics and Space Administration satellite‐based IS mission, we present an overview of the current opportunities and challenges for the use of spectroscopy to study Arctic tundra, informed by novel measurements across a range of spatial and temporal scales. We share recommendations for how researchers could leverage IS to resolve pressing ecological questions and advance the design and sampling scheme of future instruments and campaigns. Key Points Imaging spectroscopy (IS) can help to measure the critical Arctic tundra properties, physiological function, and temporal dynamics Upcoming IS satellite missions including National Aeronautics and Space Administration’s Surface Biology and Geology will make IS data widely available for Arctic tundra regions To properly interpret IS data users must consider spectral complexity of tundra driven by composition, sensitivity to climate, and phenology</abstract><cop>Washington</cop><pub>Blackwell Publishing Ltd</pub><doi>10.1029/2021JG006697</doi><tpages>32</tpages><orcidid>https://orcid.org/0000-0003-2817-4486</orcidid><orcidid>https://orcid.org/0000-0002-6726-2406</orcidid><orcidid>https://orcid.org/0000-0002-5134-0334</orcidid><orcidid>https://orcid.org/0000-0002-0052-8580</orcidid><orcidid>https://orcid.org/0000-0003-1100-7550</orcidid><orcidid>https://orcid.org/0000-0003-2839-0699</orcidid><orcidid>https://orcid.org/0000-0003-2808-208X</orcidid><orcidid>https://orcid.org/0000-0001-8327-2121</orcidid><orcidid>https://orcid.org/0000-0003-3277-5209</orcidid><orcidid>https://orcid.org/0000-0003-1705-7823</orcidid><orcidid>https://orcid.org/0000-0002-6983-7250</orcidid><orcidid>https://orcid.org/0000-0002-0505-4951</orcidid><orcidid>https://orcid.org/0000-0001-5539-4914</orcidid><orcidid>https://orcid.org/0000-0003-4136-8971</orcidid><orcidid>https://orcid.org/0000-0002-6334-0497</orcidid><orcidid>https://orcid.org/0000-0002-9033-0024</orcidid><orcidid>https://orcid.org/0000-0003-4148-9108</orcidid><orcidid>https://orcid.org/0000000341368971</orcidid><oa>free_for_read</oa></addata></record>
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identifier ISSN: 2169-8953
ispartof Journal of geophysical research. Biogeosciences, 2022-02, Vol.127 (2), p.n/a
issn 2169-8953
2169-8961
language eng
recordid cdi_osti_scitechconnect_1841100
source Wiley Online Library Journals Frontfile Complete; Wiley Online Library Free Content; Alma/SFX Local Collection
subjects Aeronautics
Algorithms
Analytical methods
Arctic tundra
Biology
Composition
Current data
Dynamics
Ecosystems
ENVIRONMENTAL SCIENCES
Geology
Growing season
Heterogeneity
imaging spectroscopy
Imaging techniques
Instruments
intrinsic dimensionality
Plant cover
Plants (botany)
Reflectance
Remote observing
Remote sensing
Satellite imagery
Satellites
Snow cover
Spectral resolution
Spectroscopic analysis
Spectroscopy
Spectrum analysis
surface biology and geology
Surface properties
Taiga & tundra
Towers
Tundra
Vegetation
Vegetation growth
Vegetation mapping
Vegetation surveys
Work platforms
title Remote Sensing of Tundra Ecosystems Using High Spectral Resolution Reflectance: Opportunities and Challenges
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