Comprehensive comparison of airborne and spaceborne SAR and LiDAR estimates of forest structure in the tallest mangrove forest on earth

A recent suite of new global-scale satellite sensors and regional-scale airborne campaigns are providing a wealth of remote sensing data capable of dramatically advancing our current understanding of the spatial distribution of forest structure and carbon stocks. However, a baseline for forest statu...

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Autores principales:	Atticus E.L. Stovall, Temilola Fatoyinbo, Nathan M. Thomas, John Armston, Médard Obiang Ebanega, Marc Simard, Carl Trettin, Robert Vancelas Obiang Zogo, Igor Akendengue Aken, Michael Debina, Alphna Mekui Me Kemoe, Emmanuel Ondo Assoumou, Jun Su Kim, David Lagomasino, Seung-Kuk Lee, Jean Calvin Ndong Obame, Geldin Derrick Voubou, Chamberlain Zame Essono
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	AfriSAR Carbon ALOS SRTM TanDEM-X ICESat-2 Physical geography GB3-5030 Science Q
Acceso en línea:	https://doaj.org/article/668ebb11030d48ff84fbfdd5a841e76c
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spelling	oai:doaj.org-article:668ebb11030d48ff84fbfdd5a841e76c2021-11-20T05:13:37ZComprehensive comparison of airborne and spaceborne SAR and LiDAR estimates of forest structure in the tallest mangrove forest on earth2666-017210.1016/j.srs.2021.100034https://doaj.org/article/668ebb11030d48ff84fbfdd5a841e76c2021-12-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S2666017221000213https://doaj.org/toc/2666-0172A recent suite of new global-scale satellite sensors and regional-scale airborne campaigns are providing a wealth of remote sensing data capable of dramatically advancing our current understanding of the spatial distribution of forest structure and carbon stocks. However, a baseline for forest stature and biomass estimates has yet to be established for the wide array of available remote sensing products. At present, it remains unclear how the estimates from these sensors compare to one another in terrestrial forests, with a clear dearth of studies in high carbon density mangrove ecosystems. In the tallest mangrove forest on Earth (Pongara National Park, Gabon), we leverage the data collected during the AfriSAR campaign to evaluate 17 state-of-the-art sensor data products across the full range of height and biomass known to exist globally in mangrove forest ecosystems, providing a much-needed baseline for sensor performance. Our major findings are: (Houghton, Hall, Goetz) height estimates are not consistent across products, with opposing trends in relative and absolute errors, highlighting the need for an adaptive approach to constraining height estimates (Panet al., 2011); radar height estimates had the lowest calibration error and bias, with further improvements using LiDAR fusion (Bonan, 2008); biomass variability and uncertainty strongly depends on forest stature, with variation across products increasing with canopy height, while relative biomass variation was highest in low-stature stands (Le Quéréet al., 2017); a remote sensing product's sensitivity to variations in canopy structure is more important than the absolute accuracy of height estimates (Mitchardet al., 2014); locally-calibrated area-wide totals are more representative than generalized global biomass models for high-precision biomass estimates. The findings presented here provide critical baseline expectations for height and biomass predictions across the full range of mangrove forest stature, which can be directly applied to current (TanDEM-X, GEDI, ICESat-2) and future (NISAR, BIOMASS) global-scale forest monitoring missions.Atticus E.L. StovallTemilola FatoyinboNathan M. ThomasJohn ArmstonMédard Obiang EbanegaMarc SimardCarl TrettinRobert Vancelas Obiang ZogoIgor Akendengue AkenMichael DebinaAlphna Mekui Me KemoeEmmanuel Ondo AssoumouJun Su KimDavid LagomasinoSeung-Kuk LeeJean Calvin Ndong ObameGeldin Derrick VoubouChamberlain Zame EssonoElsevierarticleAfriSARCarbonALOSSRTMTanDEM-XICESat-2Physical geographyGB3-5030ScienceQENScience of Remote Sensing, Vol 4, Iss , Pp 100034- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	AfriSAR Carbon ALOS SRTM TanDEM-X ICESat-2 Physical geography GB3-5030 Science Q
spellingShingle	AfriSAR Carbon ALOS SRTM TanDEM-X ICESat-2 Physical geography GB3-5030 Science Q Atticus E.L. Stovall Temilola Fatoyinbo Nathan M. Thomas John Armston Médard Obiang Ebanega Marc Simard Carl Trettin Robert Vancelas Obiang Zogo Igor Akendengue Aken Michael Debina Alphna Mekui Me Kemoe Emmanuel Ondo Assoumou Jun Su Kim David Lagomasino Seung-Kuk Lee Jean Calvin Ndong Obame Geldin Derrick Voubou Chamberlain Zame Essono Comprehensive comparison of airborne and spaceborne SAR and LiDAR estimates of forest structure in the tallest mangrove forest on earth
description	A recent suite of new global-scale satellite sensors and regional-scale airborne campaigns are providing a wealth of remote sensing data capable of dramatically advancing our current understanding of the spatial distribution of forest structure and carbon stocks. However, a baseline for forest stature and biomass estimates has yet to be established for the wide array of available remote sensing products. At present, it remains unclear how the estimates from these sensors compare to one another in terrestrial forests, with a clear dearth of studies in high carbon density mangrove ecosystems. In the tallest mangrove forest on Earth (Pongara National Park, Gabon), we leverage the data collected during the AfriSAR campaign to evaluate 17 state-of-the-art sensor data products across the full range of height and biomass known to exist globally in mangrove forest ecosystems, providing a much-needed baseline for sensor performance. Our major findings are: (Houghton, Hall, Goetz) height estimates are not consistent across products, with opposing trends in relative and absolute errors, highlighting the need for an adaptive approach to constraining height estimates (Panet al., 2011); radar height estimates had the lowest calibration error and bias, with further improvements using LiDAR fusion (Bonan, 2008); biomass variability and uncertainty strongly depends on forest stature, with variation across products increasing with canopy height, while relative biomass variation was highest in low-stature stands (Le Quéréet al., 2017); a remote sensing product's sensitivity to variations in canopy structure is more important than the absolute accuracy of height estimates (Mitchardet al., 2014); locally-calibrated area-wide totals are more representative than generalized global biomass models for high-precision biomass estimates. The findings presented here provide critical baseline expectations for height and biomass predictions across the full range of mangrove forest stature, which can be directly applied to current (TanDEM-X, GEDI, ICESat-2) and future (NISAR, BIOMASS) global-scale forest monitoring missions.
format	article
author	Atticus E.L. Stovall Temilola Fatoyinbo Nathan M. Thomas John Armston Médard Obiang Ebanega Marc Simard Carl Trettin Robert Vancelas Obiang Zogo Igor Akendengue Aken Michael Debina Alphna Mekui Me Kemoe Emmanuel Ondo Assoumou Jun Su Kim David Lagomasino Seung-Kuk Lee Jean Calvin Ndong Obame Geldin Derrick Voubou Chamberlain Zame Essono
author_facet	Atticus E.L. Stovall Temilola Fatoyinbo Nathan M. Thomas John Armston Médard Obiang Ebanega Marc Simard Carl Trettin Robert Vancelas Obiang Zogo Igor Akendengue Aken Michael Debina Alphna Mekui Me Kemoe Emmanuel Ondo Assoumou Jun Su Kim David Lagomasino Seung-Kuk Lee Jean Calvin Ndong Obame Geldin Derrick Voubou Chamberlain Zame Essono
author_sort	Atticus E.L. Stovall
title	Comprehensive comparison of airborne and spaceborne SAR and LiDAR estimates of forest structure in the tallest mangrove forest on earth
title_short	Comprehensive comparison of airborne and spaceborne SAR and LiDAR estimates of forest structure in the tallest mangrove forest on earth
title_full	Comprehensive comparison of airborne and spaceborne SAR and LiDAR estimates of forest structure in the tallest mangrove forest on earth
title_fullStr	Comprehensive comparison of airborne and spaceborne SAR and LiDAR estimates of forest structure in the tallest mangrove forest on earth
title_full_unstemmed	Comprehensive comparison of airborne and spaceborne SAR and LiDAR estimates of forest structure in the tallest mangrove forest on earth
title_sort	comprehensive comparison of airborne and spaceborne sar and lidar estimates of forest structure in the tallest mangrove forest on earth
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/668ebb11030d48ff84fbfdd5a841e76c
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Comprehensive comparison of airborne and spaceborne SAR and LiDAR estimates of forest structure in the tallest mangrove forest on earth

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