TY - JOUR
T1 - Simulating Global Dynamic Surface Reflectances for Imaging Spectroscopy Spaceborne Missions
T2 - LPJ-PROSAIL
AU - Poulter, Benjamin
AU - Currey, Bryce
AU - Calle, Leonardo
AU - Shiklomanov, Alexey N.
AU - Amaral, Cibele H.
AU - Brookshire, E. N.Jack
AU - Campbell, Petya
AU - Chlus, Adam
AU - Cawse-Nicholson, Kerry
AU - Huemmrich, Fred
AU - Miller, Charles E.
AU - Miner, Kimberley
AU - Pierrat, Zoe
AU - Raiho, Ann M.
AU - Schimel, David
AU - Serbin, Shawn
AU - Smith, William K.
AU - Stavros, Natasha
AU - Stutz, Jochen
AU - Townsend, Phil
AU - Thompson, David R.
AU - Zhang, Zhen
N1 - Funding Information:
We thank J.A. Biederman for their efforts as PI of the RainManSR experimental facility, the source of the semi-arid grassland spectra used in this analysis. We acknowledge support from the NASA Surface Biology and Geology Designated Observable architecture study. B.P. and W.K.S. also acknowledge support from the NASA Carbon Cycle Science program (Grant 80NSSC21K1709). SPS was partially supported by the NASA Surface Biology and Geology Designated Observable architecture study (80GSFC22TA016) and by the United States Department of Energy, Office of Science, through the Department of Energy contract No. DE-SC0012704 to Brookhaven National Laboratory. Part of the research described in this paper was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration. Government sponsorship acknowledged. This material is also based upon work supported by the National Science Foundation Graduate Research Fellowship under Grants 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 National Science Foundation. We thank Teledyne Brown Engineering (TBE) and the German Aerospace Center (DLR) for providing the DESIS images. We acknowledge the PRISMA Products, © of the Italian Space Agency (ASI), delivered under an ASI License to use.
Funding Information:
We thank J.A. Biederman for their efforts as PI of the RainManSR experimental facility, the source of the semi‐arid grassland spectra used in this analysis. We acknowledge support from the NASA Surface Biology and Geology Designated Observable architecture study. B.P. and W.K.S. also acknowledge support from the NASA Carbon Cycle Science program (Grant 80NSSC21K1709). SPS was partially supported by the NASA Surface Biology and Geology Designated Observable architecture study (80GSFC22TA016) and by the United States Department of Energy, Office of Science, through the Department of Energy contract No. DE‐SC0012704 to Brookhaven National Laboratory. Part of the research described in this paper was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration. Government sponsorship acknowledged. This material is also based upon work supported by the National Science Foundation Graduate Research Fellowship under Grants 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 National Science Foundation. We thank Teledyne Brown Engineering (TBE) and the German Aerospace Center (DLR) for providing the DESIS images. We acknowledge the PRISMA Products, © of the Italian Space Agency (ASI), delivered under an ASI License to use.
Publisher Copyright:
© 2023 The Authors. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.
PY - 2023/1
Y1 - 2023/1
N2 - Spectroscopic reflectance data provide novel information on the properties of the Earth's terrestrial and aquatic surfaces. Until recently, imaging spectroscopy missions were dependent mainly on airborne instruments, such as the Next Generation Airborne Visible InfraRed Imaging Spectrometer (AVIRIS-NG), providing limited spatial and temporal observations. Currently, there is an emergence of spaceborne imaging spectroscopy missions, which require advances in end-to-end model support for traceability studies. To provide this support, the LPJ-wsl dynamic global vegetation model is coupled with the canopy radiative transfer model, PROSAIL, to generate global, gridded, daily visible to shortwave infrared (VSWIR) spectra (400–2,500 nm). LPJ-wsl variables are cross-walked to meet required PROSAIL parameters, which include leaf structure, chlorophyll a + b, brown pigment, equivalent water thickness, and dry matter content. Simulated spectra are compared to a boreal forest site, a temperate forest, managed grassland, a dryland and a tropical forest site using reflectance data from tower-mounted, aircraft, and spaceborne imagers. We find that canopy nitrogen and leaf-area index are the most uncertain variables in translating LPJ-wsl to PROSAIL parameters but at first order, LPJ-PROSAIL successfully simulates surface reflectance dynamics. Future work will optimize functional relationships required for improving PROSAIL parameters and include the development of the LPJ-model to represent improvements in leaf water content and canopy nitrogen. The LPJ-PROSAIL model is intended to support missions such as NASA's Surface Biology and Geology and subsequent modeled products related to the carbon cycle and hydrology.
AB - Spectroscopic reflectance data provide novel information on the properties of the Earth's terrestrial and aquatic surfaces. Until recently, imaging spectroscopy missions were dependent mainly on airborne instruments, such as the Next Generation Airborne Visible InfraRed Imaging Spectrometer (AVIRIS-NG), providing limited spatial and temporal observations. Currently, there is an emergence of spaceborne imaging spectroscopy missions, which require advances in end-to-end model support for traceability studies. To provide this support, the LPJ-wsl dynamic global vegetation model is coupled with the canopy radiative transfer model, PROSAIL, to generate global, gridded, daily visible to shortwave infrared (VSWIR) spectra (400–2,500 nm). LPJ-wsl variables are cross-walked to meet required PROSAIL parameters, which include leaf structure, chlorophyll a + b, brown pigment, equivalent water thickness, and dry matter content. Simulated spectra are compared to a boreal forest site, a temperate forest, managed grassland, a dryland and a tropical forest site using reflectance data from tower-mounted, aircraft, and spaceborne imagers. We find that canopy nitrogen and leaf-area index are the most uncertain variables in translating LPJ-wsl to PROSAIL parameters but at first order, LPJ-PROSAIL successfully simulates surface reflectance dynamics. Future work will optimize functional relationships required for improving PROSAIL parameters and include the development of the LPJ-model to represent improvements in leaf water content and canopy nitrogen. The LPJ-PROSAIL model is intended to support missions such as NASA's Surface Biology and Geology and subsequent modeled products related to the carbon cycle and hydrology.
KW - Surface Biology and Geology (SBG)
KW - dynamic global vegetation model
KW - imaging spectroscopy
KW - radiative transfer model
UR - http://www.scopus.com/inward/record.url?scp=85147148841&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85147148841&partnerID=8YFLogxK
U2 - 10.1029/2022JG006935
DO - 10.1029/2022JG006935
M3 - Article
AN - SCOPUS:85147148841
SN - 2169-8953
VL - 128
JO - Journal of Geophysical Research: Biogeosciences
JF - Journal of Geophysical Research: Biogeosciences
IS - 1
M1 - e2022JG006935
ER -